who will jump right into flo-jo here and
I wanted to just start recording so in
case you miss pieces of this or you you
know you know people that wanted to see
this webinar I am recording it so they
can access it after after we're done
here today okay so I'm going to go ahead
and open up flo-jo here and
I know expand this a little bit and I'll
describe a little bit about the
interface here and some of the major
controls within the program the
interface is essentially divided into
three different sections there's the the
upper section here is where all of the
tools and action buttons are and I'll
discuss these in a little more detail
here in a second the second section here
is a groups pane this is where we go to
create essentially subfolders within the
workspace so that we could separate out
our experimental files away from our
control files or perhaps other sets of
experiments so if you have multiple
experiments you can you can essentially
create groups or other subfolders here
that will separate those experiments one
from the other and then the lower
section here this is known as the status
area this is what will populate with all
your FCS files so flo-jo will read three
different types of files it will read an
FCS file which is the FCS standard or
the the flow cytometry standard file and
we also have something called an L MD
file that is a list mode file and we can
also read CSV s and I should say we can
read and mqd files which are files that
are put out by the max quant flow
cytometer anyway let's talk about the
action buttons here at the top for a
second at the very top of your workspace
you'll notice there's this pyramid icon
the pyramid icon has a has a menu if you
just click on it it has a menu to add a
new workspace there are some you know
primarily document associated functions
here so you can open workspaces you can
save and of course you can run through
some print options as well we have undo
and redo buttons here at the top these
are really nice if you make a mistake or
there's something that you know you want
to go back to that that might take you a
little bit while longer than deleting
and re adding and then of course we have
the add samples button here I like to do
a lot of drag and drop when I add
samples and you'll see this in a moment
but you can navigate your filesystem by
just clicking on that
a little tube with the plus by it when
you click that it'll give you a little
prompt here that goes through your file
system create groups this little
bracketed plus that will create those
little subfolders I was talking about
earlier in the workspace and we'll do
that here momentarily
the M that you see here this is kind of
a shaded M this is our compensation
wizard so if you want to generate your
own comp matrix using your single
staying controls you can do it using the
comp wizard here in flo-jo and I'll talk
a little bit about that towards the end
of the webinar today and I'll explain
why when I get there we also have a
table editor this little screen looking
icon this is for creating Excel files or
CSV files you can also create text files
but this is basically where you go to
export all of your statistics so that
you can create bar charts or pie charts
and all types of different types of
graphs maybe in Excel in prison or
something like that the layout editor
this is where we go to create all of our
graphical exports or no graphical images
and I'll talk about this in quite a bit
of detail today because this is a major
major components major feature that we
use a lot within within flo-jo and
during our flow analyses and then we
have this little refresh button here so
on on occasion your your workspace may
slow down or may not calculate
statistics if you just click that little
refresh button it'll refresh the
workspace and should should alleviate a
lot of little you know statistical
calculations that that don't occur okay
another important button here to mention
before we get started as the preferences
the preferences are held underneath the
heart icon here it's on the workspace
itself in the upper right that you can
also find it down here in the navigate
band the preferences are your global
controls for the program so if you like
your gates to have a certain color or a
certain width line width you can make
adjustments here that perm
adjust that for all of your workspaces
so that every time you come into flo-jo
it has the color and the line weight for
example that you want also in terms of
the layout annotation this is a common
question I get a lot how can I remove or
how can I you know add the the white
background on the statistics that are
shown within the graph window itself
well this little layout annotation box
here allows you to choose what you can
what you can do with that little
annotation box inside your gates in the
graph window and of course you can
change the position of where that that
annotation appears okay so there are all
types of preferences here I'm not going
to go through them all of course again
you can find what these preferences do
simply by going to our Doc's site so doc
stuff flo-jo comm will have the details
about what each of these preferences do
and and how to manipulate them okay the
last thing i'll talk about here is the
the flo-jo workspace at the very top
here we have this ribbon the ribbon is
divided by these individual tabs at the
top when i click on the different tabs
you can see that the ribbon underneath
changes and the reason the ribbon
underneath changes is because the bands
that contain the action buttons are
changing from one tab to the next and
they're divided essentially a by
function so underneath the file tab you
have you know the the document band that
allows you to open files and save files
etc underneath the tools tab you have
things like the the biology platform so
you can do cell cycle analyses or
proliferation modeling we also have
boolean gates here as well and then
there's a sample quality check I'll talk
about here in a moment and so on and so
forth through for all the Bands I will
show you some of the major features in
in flo-jo and how to access them as
quickly as possible so sometimes I'll be
jumping through these bands here but
I'll make sure to tell you exactly which
band on using and which tab I'm working
under okay so let's start with let's
start with some data here I have an
amino phenotyping experiment if I open
this folder up you can
see a series of FCS files contained
within it you do not have to drag in the
individual FCS files if you don't want
to you can just drag in the folder that
contains those FCS files and flo-jo will
go ahead and extract all the FCS files
that are contained within them and it'll
also put the folder name that you use to
drag in at the top as a group okay so
you can see here immunophenotype
experiment corresponds to this amino
phenotype the experiment I had in a
folder on my desktop okay so the FCS
files are going to populate here you'll
notice there's three little icons that
sit next to your FCS files the first one
that probably has the most noticeable
difference is the the presence of the
open square or the gray grid the open
square means that these files do not
have a compensation matrix associated
with them okay and if you're running an
experiment you bring in your files and
all your files have an open square okay
that means that each one of those files
do not have a compensation matrix
associated with them now compensation is
important especially when you have two
or more colors that that over that have
overlapping emission spectra okay so if
you have two or more colors and you know
that they those colors overlap like PE
and fitzy for example then you want to
make sure that you run compensation and
flo-jo first and then begin an analyzing
your data okay in my case and in most
cases these days you'll be sitting on
the machine and you will actually run
compensation on the machine yourself so
you run your single stain controls and
then the machine software will actually
create a compensation matrix for you and
usually we'll tether that compensation
matrix to your files and so this is what
we see here beginning at these files
that are labeled FM own and going all
the way down to my file here LD 14 you
can see that there is this gray grid
that's sitting next to the files right
so if I click off this for a second the
gray grid tells you that there is a
compensation matrix associated with this
file if you want to inspect that matrix
just double click
the matrix little icon itself and what
you will notice here is a table on the
top alright that has all the spillover
values for each one of the parameters
into the various detectors and then down
below perhaps more intuitive or more
importantly is an n-by-n plot that shows
you each parameter by all the other
parameters and in the middle it has or
in each plot it has an overlay of what
your current compensation matrix looks
like in this case the acquisition
defined matrix versus uncompensated data
or what your data would look like
without compensation okay and so the way
this works if we toggle this box here
off towards the right and uncheck that
box you'll notice that the blue dots go
away the blue dots represent your
uncompensated data or what the data
would look like without compensation
okay so for example if we go to the
middle of this and by n plot here we can
see that this is pe Texas red versus PE
okay and these two dyes if they're not
compensated would give you cells or you
know events that would look like this
where you get this nice sort of
45-degree angle going through the middle
of the graph what compensation does is
it takes that population that's sort of
on this 45 and then it flattens it out
it either brings it down towards the
x-axis and then sort of makes this
little trumpet formation on the x-axis
or it can also you know move it towards
the y-axis and the whole idea here when
you compensate your data is you
generally want the positive populations
the median of the positive population
here to match up with the median of the
negative population okay and that goes
for the y-axis as well I see I have
another question here so I'm going to
open up the chat real quick question is
my internet too unstable to watch this
live is there a link to record a version
that I could be at a different time yes
so Elinor
we are recording this so as soon as it's
finished what I can do is send you the
link to the webinar we also have
recorded webinars on our website already
especially for this intro to flo-jo so
if you just go to our website and look
for recorded webinars you will see
previously recorded webinar okay we'll
talk more about the compensation matrix
how to edit it and how to create one
towards the end and the reason I'm going
to do it towards the end is because my
comp matrix here looks pretty good that
you know most of my samples here or my
my in the plots essentially show you
know a median positive population that's
roughly equivalent to the median
negative population I don't see anything
that appears askew here and we can
generate our own matrix later on and try
to recapitulate what we've got what
we've got going here the mathematics in
flo-jo and the acquisition software is
exactly the same so what what you use to
generate that matrix it's entirely up to
you alright we've got another question
here
one second Kenya does the user need to
rename the comp files in order to show
the names on the matrix well I'm gonna
say that is really more or less
dependent on how they appear here in the
in the workspace so if you don't label
your your files file names as comp there
are a couple of ways that you can change
this and it might appear in the comp
matrix the way you want it to do that
you have to click on the Preferences
here and you want to go to the workspace
the workspace preference this one on the
far left upper left and this first panel
sample display naming allows you to
change the naming style that flo-jo uses
here of your files so you could try
clicking use short filename or perhaps
well I wouldn't say use full path and
file the use short file name if this
does not alleviate the problem then the
odds are we won't be able to fix
way you name your files using flo-jo
itself we do have another tool called a
D identification utility that you can
run your samples through and it will
rename the files for you so that they
will appear as you want them in flo-jo
and that's a free program you just have
to to contact us to let us know so make
the change here try use short file name
and then click OK
the other alternative is that instead of
the file name perhaps you have a
different keyword that you're recording
your samples under so you could say
keyword combination and then open up
this drop down menu and I would suggest
that you check this option here for tube
names so instead of the file name you
may be using a tube name and you could
also have I've seen it before there's
another there's another keyword here
that you could use and this one is the
dollar sign SRC this stands for the
source sometimes saitama ters use the
source keyword for names that you write
in for tubes so these are these are
three alternatives essentially that you
could use instead of the default that
flo-jo uses here okay and I'll just give
you an idea of what it looks like here
if we change the name and I'll go over
to I'm gonna change it instead of tube
name I'm gonna change it to well ID
because I know this is gonna give an
extreme example and you can see what
happens to my file names as they change
in the workspace okay if I switch to
well ID I click OK you can see that
instead of having the file name here now
everything is named via the well ID okay
so you can always change the the way
then file names look in the workspace
and you can sort of course by by the new
name if you want I'm going to set this
back to the default because my files
have a pretty clean name here and it's
easy to easy to work with right to sort
these columns just double click on the
column once or twice right to get it go
ascending to descending or vice versa
in my case I'm probably gonna stick with
this alright so let's let's talk about
the other little icon that we have here
okay so there's a little circle icon
next to your FCS files the circle icon
is what we call our sample quality check
if you double click on this button or
this little badge what happens is it
brings up a little a little menu that
contains on the left-hand pane all of
the files keywords so your FCS files
include a lot of information not just
you know what events you collected and
what colors they were it also includes
information like the date you know the
site ometer that you used when the
analysis began that the order or the
time that the time that the sample was
collected and there's a whole myriad of
other keywords that are incorporated
here and if you annotate your data on
the flow cytometry all of that those
annotations get wrapped into that FCS
file and downstream it lets you you know
sort your samples very easily in flo-jo
and you can create group reports that
are specific to particular groups or
annotations so if you have a drug
concentration or time point something
like that that you add to your
annotation on the machine you can use
that very effectively in flow geo to
create drug or time point specific
reports the reason this is called the
sample quality check is because in the
bottom right you'll see a series of
graphs these little graphs basically
what they're doing is looking for a
drift in signal over time so the x-axis
is actually time and the y-axis is the
parameter that is listed so in this case
the y axis is actually FSC and then the
x axis is time and then you'll see in
within the graph itself there's these
little double dashed lines sort of a
certain distance away from a line that
is going through the middle these double
dashed lines are just the two standard
deviation mark so they mark where two
standard deviations away from the median
line here in the middle is and all
flo-jo is doing is looking to see if any
samples EXCI
these lines okay and the important thing
is when we run our data on the machine
sometimes we encounter a clog right you
put your tube on the machine this
machine immediately gets clogged and you
have to purge purge the valve and then
you have to you know either filter your
sample or centrifuge it a little bit or
sorry vortex it a little bit and then
aspirate it again whenever you run in
into a clog generally speaking you're
gonna get a signal that spikes here
beyond two standard deviations okay and
flo-jo will flag this for you the other
thing that it will do on occasion
sometimes will run a tube on a machine
and will actually start to aspirate
bubbles right we forget the tube is on
there and it starts aspirating you know
a dry tube when it when that happens you
will also get a spike in the data
generally towards the far end of the of
the graph towards the latter part of
your acquisition okay so those are two
occasions that naturally account and
naturally happen in the lab and it's
good to know because we don't want to
include that data in our analysis at the
end so we have a tool here underneath
the tools tab that allows you to quickly
assess you know which files are good and
which files need a second look at the
time axis to you know to preview before
we actually begin our data analysis so
this button is underneath the tools tab
it's contained within the cytometry band
and it's the check sample quality button
okay when you click that button you'll
notice that all those little circles on
the left-hand side fill in with
different colors okay the different
colors are telling you how severe or how
smooth the acquisition was if you have a
blue or a green dot it means you're
within one standard deviation and so the
signal is pretty pretty smooth pretty
nice all the data that I have here for
the most part are pretty good it's a
smooth acquisition okay you can get a
purple dot which means you exceed one
standard deviation but you're also
within two standard deviations so it's a
little rough but it's not terrible and
if you get a red dot it will be
immediately obvious it'll fill the
entire circle here and the red dot means
that you either have a gap you know
you've got a you have a clog that you
encountered or you encountered a bubble
okay and usually those are ones that you
have to go through and inspect and then
just go ahead and open up the file and
find the anomalous section so what I
would do is just open up the file if we
assume for a second that this is a
problematic file it's not because it's
green but let's just make the assumption
for argument's sake here
that this is a problematic file okay you
go here when you open up the graph
window you can click on the little
x-axis drop down menu and change the
axis here over to time and I'm going to
stretch this out a little bit the time
axis basically shows you what we saw in
this panel over here okay so what we've
got in this panel is a sum or a you know
a summary line of what you're seeing in
the graph window itself okay so if you
know from looking at one of these one of
these small graphs here that the spike
exists you know in this case maybe
Alexis 700 you can go ahead and change
the y-axis over to Alexis 700 and see if
there's any anomalies there okay again
in this case my acquisition is really
smooth you don't see the data bouncing
around very much and if I return here to
the side scatter the best I can tell you
here is there's a little bit of an
anomaly here and that you know we
probably slowed down the machine for a
second or two during this acquisition so
if I consider this the the bad section
of my data the anomalous section what I
can do is I can go ahead and create a
gate using the gating tools here up at
the top in this case I'm just gonna use
a rectangle so I just click on it and
then you just click and drag within the
graph window itself you know move the
mouse wherever you want and then it'll
create the gate for you as soon as you
finish all right you get a prompt to
give that gate a name I'll just call
this the time time gate and you can also
stretch this gate so that it goes beyond
the borders
the beyond the borders of the graph
window so you make sure that you you
know you've caught everything here all
right and then there's this little
annotation here that you can't see very
well but I'll move it okay and this is
my time gate shows you the percentage of
events contained within this gate now
flo-jo by default when you create a gate
like this and you double click inside
the gate it's inclusive meaning all the
events that you put in that gate are
gonna be contained within within it okay
but if we assume for a second like we
did in the beginning that this is a this
is a bad file this is an anomalous file
it's got some bad data here and we want
to get rid of this what we can do really
quickly is change this gate the nature
of this gate we can change it from an
inclusive gate to what's called a not
gate so we can dump whatever is in the
middle here and the way to do that
quickly anyway is down here in the
middle of the graph windows drop-down
menus you'll see this active gate option
if you click that a little menu will
open up ok and you'll see immediately
this little events inside option or tick
box if you uncheck that box it changes
the nature of the gate from an inclusive
gay a toward an and gate to a not gate
and now if I double click on this the
downstream population right excludes
that information that was problematic ok
so this is actually a useful gate it's
useful you know not only for chopping
out you know stuff in the time sector
but it's also a useful gate when it
comes to you know creating dump gates or
things of that nature where you
essentially want to exclude the events
that are falling into into that gate
okay now I'm gonna return this gate to
the normal sense and I'll get rid of it
simply because it is you know it's a
decent file decent acquisition there
aren't any problems with the time there
ok so I'm gonna go ahead and select the
gate here in the workspace to delete it
and then I just hit the delete button on
my keyboard I get the prop tier asking
me if I want to delete it and I just say
yes
okay now we've done the sample quality
check we've seen our compensation matrix
and decided that it's satisfactory to
begin our analysis with okay the next
thing that I want to do before I
actually start doing an analysis in
flo-jo is I want to separate out my
files okay so I've got a series of files
here my control files labeled FMO right
these are fluorescents - one controls
these help me to create gates for
various populations in my data set and
then I have my single stain controls
here which allow me to create a comp
matrix okay so on top of that I've got
these experimental files that are all
labeled LD something-or-other
getting LD standing fool or local donor
so what I would like to do is I would
like to sequester my experimental files
away from my control files because in
the end when I generate my reports I
don't want any FMOs you know adding
statistics or creating statistics within
my summary report I just want to know
what happens with my biological samples
that are important for the experiment so
I'm gonna go ahead and create a group
that isolates these experiment files
okay the way to do that is to click the
plus button at the top this little
bracketed + you see and you just say go
ahead and create the group and we're
gonna call this my experiment group okay
and then I'll show you the easy way to
do it you can just simply give it a name
alright and then say create group close
this you'll notice that all my files
suddenly disappear and that's just
because we created this new group here
right it gets placed in the groups pane
and you'll see that the size here which
tells you how many files are contained
within it there aren't any right the all
samples group will always contain
whatever sample you have added to the
workspace in this case we've got 39 in
the comp group will automatically draw
in your comp files the comp group is
there by default in flo-jo so I don't
really have to create a cop group to
separate out those files they're already
there okay
the only other the only other group
I want to create as maybe one for the
FMOs okay so let's start though with the
experiment files we want to bring in
those files that belong in the
experiment group so sort of the the
brute force force method is to go to the
all samples group highlight the samples
that you want in this case all those
that are labeled LD and then we simply
drag and drop this into the experiment
group okay and now the experiment group
picks up those twenty files these are
all experiment files okay and these are
what I'm going to use for my creating of
the vast majority of my reports if we go
back to the all samples group here I do
have another subset of FMOs I would like
to subset these guys out because we're
gonna create gates using the FMO
controls first and then we are going to
apply those gates to the experiment file
so I'm going to go ahead and create this
group another group I'm going to call it
FMO and I'm gonna go ahead and change
the color here or something a little
more appealing and instead of just
creating an empty group I'm actually
going to use this sample inclusion
criteria here and I'm basically going to
tell flo-jo to look for the file name
keyword as you can see here all the
files that are labeled they have
different names and they're pretty
different amongst the different types
the FMOs are labeled FMO and nothing
else contains FMO in it so i can use the
file name keyword alright which is
indicated here by this dollar sign fil
right just a file name look for any file
name that contains the text FMO okay
just use these three boxes and then say
create group and this will automatically
draw in those FML files into that group
so that you don't have to do the
drag-and-drop and the nice thing is if
you save this as a work space or you
save it as a template this group will
forever automatically draw in your FMO
files okay so that you don't have to you
don't have to separate them by hand
every time and if you happen to have
gates here the fmos that you bring in
they'll automatically get sorted and
then we'll pick up the gates that are
ciated with that group I have another
question here I'm going to jump into the
chat real quick and then we're gonna go
to start our analysis okay it says how
how flo-jo knows which samples should be
in a comm folder okay I'll show you real
quick here and how to label the samples
should the samples be named before run
on the instrument I would recommend
pardon me yes I would recommend that you
annotate or at least label your tubes
when you acquire them you should label
the tubes so that you know what they are
downstream it becomes very difficult to
to identify you know
and you know
hour ago Diaz is fantastic Java maybe
you have a you have a Google sheet or an
excel sheet that lists out what the you
know what the acquisitions of it up I
would definitely label your tubes
those caught double click on the
compensation group itself it opens up
the the group pain or the group menu and
you'll see the settings that are set
here so basically flo-jo is looking for
any file name that contains the word
unstained okay or the file name that
contains comp in it so if you don't have
comp or unstained flo-jo won't be able
to visualizer to see your comp files and
it will automatically drop them there if
you know which you know comp files are
your comp files you can always drag and
drop them as I did with the experiment
group just forcibly add them to this
group or you can add more choices here
and tell it okay I want you know comp my
comp files are labeled something else
maybe they're labeled you know maybe
they're labeled single stain something
like that right you could have single
stain here and you just say apply
changes and then it should draw in those
files if you happen to have any that are
labeled single stain all right so let's
go back to the FMO group and we're gonna
begin our analysis here I'm just gonna
close this graph window for a time being
it's probably gonna be the same one I'm
gonna choose but anyway okay by default
flo-jo is going to show you this graph
window it's a pseudo color plot pseudo
color meaning you're getting density
information in addition to the
fluorescence intensity information right
so the blue dots are essentially where
the fewest numbers of cells are in the
plot and then the red dots are where
most of them are falling so you have
more than one cell that is essentially
being occupied here in the center of
this blob okay and this is because lots
of cells fall into this category here
they're roughly have you know an ambient
fluorescence or scatter forward scatter
of a certain amount and then of course a
corresponding side scatter which places
them here so I have lots and lots of
events that are falling within this this
red zone and then fewer and fewer as I
go out from here
okay in this particular experiment we're
going to be looking at t-cells so the so
the gates that I'm going to create are
gonna be t-cells specific just keep in
mind and you know the analysis that I'm
doing here there are a few you know a
lot of times the the approach to your
analysis may differ and don't worry you
know everybody has their own way of
doing analysis there are some things
that should come first and then other
times there are items that could come
you know could come later or would be
tailored to your specific analysis so
what I'm going to begin with here is a
singlets gate I start with a single
escape because that's how I was taught
so I'm going to begin by creating a gate
here using the polygon tool I should
have mentioned that here at the very top
this one that looks like a broken
pentagon okay or a pac-man if you will a
very square looking pac-man we'll go
ahead and just click that and then click
and drag your mouse to create each each
vertex and basically what I'm gonna do
here after I create the last vertex I'm
gonna go ahead and double click to close
out the gate so you don't actually have
to touch vertices to one another if you
don't want to this will be my singlets
gate and we'll go ahead and click OK and
then what that's going to do right it's
gonna fill in that gate and you can see
here my singlets occupy roughly 96
percent of the events here ok
generally speaking the singlets are
gonna be you know you're gonna see this
sort of 45-degree angle here when you
have forward scatter area versus height
and anything that sort of falls off of
that 45-degree angle here is going to be
doublets ok we can use area versus
height you can use height vs. with you
can use area versus with two twos
distinguish singlets from doublets and
if you actually have side scatters as
well that our area and height you can
also use side scatter to create an
additional single it's gate in my case i
do not have that i only have single side
our gate here and only the area and
height parameters for forward scatter
and so forward scatter we'll stick with
that for our singlets gate you'll notice
that the singlets gate gets placed here
in the workspace as I create the gates
you'll notice that they get they'll get
added here and we'll talk about the
hierarchy here in a second okay from
there I'm going to go ahead and choose
the live dead marker in our case is this
a ard a mean reactive die and I'm gonna
go ahead and create a gate on these
cells the negative cells that are
excluding the dire essentially the cells
that are living okay so these are my
live cells
alright the dead cells are the cells
that pick up the die and then of course
you know we have multiple different
types of populations of cells so
sometimes you know the die can be a
little bit different in terms of how it
binds to the the cell surface of some
types of cells so I'm going to be a
little bit generous with the gate here
okay sometimes these cells that are
spanning the living population and the
dead population might be you know cells
that are beginning to undergo death
right or apoptosis and in other cases it
may just be that you have different cell
types okay so from here
we're gonna double-click on that gate
and then we are gonna go we're gonna
return here to the Florida side scatter
parameters okay and in my case I'm
interested in lymphocytes today
lymphocytes T cells or lymphocytes the
lymphocytes generally occupy a little
bit lower on the scatter parameters and
they're a little bit smaller with
respect to the white blood cells you see
I have this big cloud of probably
granulocytes sitting above my my
lymphocytes here we're not gonna use
those cells and then you may have some
larger cells they're sort of falling off
the the forward scatter edge here and
we're gonna avoid those as well again
I'm gonna choose the polygon tool and go
ahead and create a gate maybe around you
know the cells looks something like this
alright and again I'm not gonna complete
the shape I'm just gonna go ahead and
double click on the last vertex that I
want and that will create that
lymphocytes gate and I'll move that out
of the way for a second you notice how
this little hierarchy is starting to
develop here in my workspace right
singlets I created a single it's gate
first then I created a live gate then I
created a lymphocytes gate the reason
for this hierarchy is just to tell you
that so you understand what the
dependency of each population is okay so
my singlets gate since it's the top gate
will influence anything that's below it
in this case it'll influence both my
life and my lymphocytes so if I actually
come back and I open up my singlets gate
and I move this off of the singlets
population watch what happens to the
graph on the right when I release my
mouse okay here we go alright so as soon
as I release my mouse you see that
there's nothing populating that
lymphocytes gate right as I bring this
back you can start to see data getting
added to right add it to that gate and
so on and so forth okay so any of this
is a property anywhere in flo-jo where
you have gates that are dependent on one
another this is what's going to happen
if you move them around that's what's
going to what's going to occur okay so
the gates are always live and the graph
windows are always live
all right so let's go from here we have
our lymphocytes and we are going to take
a look at CD 3 positive t-cells I'm
gonna put these along the dr parameter
here as well not that it's necessary but
just just because it's a nice one for
illustrating what happens when we want
to change the scaling of our data ok so
here's an instance where I have some
data that look a little bit compressed
right these populations even though I
can separate you know the negative
population from the cd3 positive
population it's a little bit squished
and I might like a little bit more space
between the two okay and in order to
readjust the the AXI scaling here all
you have to do is click on the T button
down at the bottom right so just next to
your X drop down menu is this t button
and the t button if you click on
customize axis will open up a transform
window and from here you can change the
axis scaling now most fluorescent data
that we're going to be looking at today
and and you guys probably all have
already acquired most fluorescent data
is plotted on what's called a by
exponential scale and the by exponential
scale is really nothing more than a
hybrid scale between a log scale off
towards the right and a linear scale off
towards the left the way you can tell
this is by you know by looking at the
tick marks so from 10 to the third to 10
to the fifth and beyond you see how the
tick marks here are uneven they're
unevenly spaced right and they tend to
get compressed as you approach the next
decade it's asterisk of hugger
yes I noticed that the tick marks are
all even right tick marks vacate that
this part of the scale is what is linear
right so as a consequence when you're in
the transform window when you try to
change the scale the by exponential
scale has just just a couple of things
that that are different from you know
changing a straight lager a straight
linear scale you can get rid of the
positive decades pretty easily just by
clicking the plus minus buttons okay if
you want to type in the value the max
value you can do that in the Box down
here okay but for the negative end of
the graph we actually have to use these
two boxes down below okay if you want
extra negative decades pretty
straightforward just slide that off
towards the right and then you'll see
you'll get this extra 10 to the fourth
down here to pull those events if they
happen to be smashed up against the axis
you just pull that pull that slider over
and it'll give you that extra space in
my case I'll leave that alone for the
time being the other one that's not so
intuitive is what's called the width
basis controller this width basis
actually controls the size of the linear
scale so remember minus ten to the third
to positive 10 to the third this is the
linear scale and specifically this
operates you know about the area around
zero here so if I actually move this to
the left you'll see that population
around zero kind of blow up right now if
I move this far enough you'll see events
start to pile up here on the on the y
axis and then I can use that little
extra negative decade slider to sort of
pull those events off if I like okay if
I move this in the opposite direction
right I'm essentially smashing that or
making that population appear a little
bit more squished I want to open it up a
little bit sometimes we have dim markers
that you know you might have some cells
that are weakly positive that you can
separate away from something that's
truly negative and the easiest way to do
that is just to simply play with the
width basis controller here to see if
you can't tease it apart okay so we'll
go ahead and click apply and what this
is going to do is it's going to change
that x-axis right the scale to what we
had done in the transform window and now
if we want
do this for the Y we can do that as well
by clicking the T button there and then
for this guy I'm not going to change it
too much all right might get a rid of
some positive decades space there and
then apply that just stretch it out a
little bit more and now in this case
what I'm going to do is I'm going to go
ahead and separate the the cd3 positive
cells here so I might use a quad we have
a series of quads that are available
we've got curly quads spider quads and
we have the straight quads so I think
these are pretty straightforward right
straight quads like this you can move
the you know vertical or horizontal axes
any way you wish I'm gonna get rid of
the straight quads for the time being
and just mention that we have curly
quads that are kind of nice these guys
what they do is they follow the
spillover so sometimes you'll see these
trumpet shaped populations the nice
thing is this little arm here sort of
follows that trumpet shape so that you
include the samples that that should be
included in that particular population
and exclude the ones that that don't I
might lower this down a little bit I'm
making an estimation of what the spread
would look like out here simply by
looking at the kind of the spread that's
going on with this with this positive
population okay and then from here we're
gonna double click on that third
quadrant okay and we want to now begin
our analysis starting with our CD floors
and our CD AIDS okay this is a CD floor
FM oh so I can set the gate boundary if
I'd like you know on the the CD fours
here somewhere they're gonna fall so
these are going to be my c4 positive
cells
okay now before we march on to isolating
our seats etc what I'm going to do is
I'm going to show you a trick okay over
here on the left hand side we've been
building these gates and now we're
creating FMO gates that we want that
boundary to be we want that boundary to
be fixed essentially for that for that
FMO okay so what we would like to do is
we want to take all of these gates that
we've applied and we want to apply them
to the rest of the samples we have in
this group and eventually we're going to
apply those gates to the experiment
group as well okay but in order to do
this what we can do right is you can
just hold down the shift key and
highlight all of those gates right so
you have all of the gates here
highlighted and what you can do from
here is you can do a drag and drop if
you'd like all right so I just drag and
drop this onto the FMO group and when I
do that all of the gates turn from that
black color to red in this case for the
color of the group right and it applies
those same gates to all of the other
samples that I have in that group okay
I'm going to show you another trick here
in a moment that will kind of nullify
that drag and drop and I'll explain why
I like it better momentarily
okay so let's also let's also go up into
our looks it well let's just go back to
our third quadrant here and we're going
to go ahead and create the gate on our
cd8 cells as well all right so I don't
know maybe make that cutoff right around
10 to the 3rd cd8 positive cells whoops
add the 8 there
okay and now when I come back you'll see
I have this new gate added all right
it's in black everything else is in red
okay if I want to quickly add this to
the growing tree that I have here I
don't want to I could do it via
drag-and-drop right I could go here and
say oh okay the cd8 is lives under
quadrant three bla bla bla I have to
drag and drop it there okay that gets a
little tedious the quick way to do this
it's just a simply right-click or
control-click on the gate that you want
to transfer to the
it's an option down here I'll copy
analysis to group okay this is the
shortcut for this is ctrl shift G or
command shift G all right so I'll go
ahead and say copy analysis to group and
that will transfer that cd8 positive
gate to the correct location on the
growing tree okay and the nice thing
about that is if you have multiple gates
that you are creating and they're in
different spots in the tree you can
highlight them all individually and use
that and we'll do that actually with
some statistics here momentarily okay so
we have our cd8 positive gates now I am
going to look at some readouts for
activation of cd8 positive T cells okay
one is going to be the production of
interferon so I'm going to come to my FM
oh that does not contain interferon open
up that cd8 positive population and I'm
going to change that x-axis here over to
interferon and I'm just going to create
a gate here that abuts the negative
population right so I know here that
anything that falls in side this gate
gonna be my interferon positive
all right so if I come back to the
workspace here you see that interferon
I'm going to go ahead and right click
and say copy that analysis to the group
okay so that everything picks that gate
up and now I march on to the next
readout we have this sample where no
that does not contain perforin okay
perforin is another molecule we're going
to use as a readout or cd8 activity and
so I'm going to change the x-axis on
this sample to perforin and then we'll
go ahead and create that per friend gate
same thing right click ctrl click and
say copy analysis to group or ctrl shift
G I would normally be doing ctrl shift G
but because you can't see my actions I'm
going to continuously right click and
choose that option
okay the last FMO that we're going to
use here is the phospho work FMO we
click on the drop down menu and we
change this over to Fausto okay and then
again I just create a gate here this
says P perc plus alright and then I say
ctrl shift G or copy analysis to group
alright so I have my gating tree I have
all the readouts that I want set by the
FMO controls okay and I want to
sometimes you know when you're looking
at these readout populations you want to
know what their MFI is okay and MFI is a
there's a very common statistic in flow
cytometry stands for median fluorescent
intensity or perhaps the geometric mean
of clearance its intensity okay we
usually use the geometric mean or the
median to describe to describe data that
are plotted on a logarithmic scale okay
when we want to tell people where the
center where the center of this
population happens to be okay we do not
want to use the mean so sometimes people
will say n fi stands for mean
fluorescent intensity and they may end
up actually using the mean statistic you
do not want to use the mean because a
single outlier right a single cell that
might populate out here will skew that
mean statistic very hard to the right
and it'll tell you that oh you know
you'll think that the central that the
vast majority of this population is
actually out here towards ten to the
fifth if a single cell is here same
thing if there's one cell that's that's
super negative in your gate and your
population is hanging around you know
the positive end if you use the mean
statistic it's going to skew it very
hard towards the left so we like to use
what are called robust statistics in
flow cytometry that includes the median
or the
geometric mean okay the median is the
50% line 50% of the data are above the
median 50% of the data are below the
median okay so it's a very good
indicator of central tendency and the
geometric mean is calculated as the nth
root of the product of all the
components within the gate that you
specify so that too is going to be a
statistic that resists the influence of
outliers okay so what I would recommend
that that you do is use the the MFI use
the median or the geometric mean okay do
not use the mean statistic all right so
let's go ahead and add some stats here
real quick again the quick way to do
this is to right click on the sample
that you've you've highlighted you can
also go to the workspace tab here and
you'll notice there's this statistics
band you can say add statistic it opens
up the same menu all right so I come
here say add statistic I'm gonna say
median
the population that we're wanting to add
that median to should be listed here
okay it's the interferon positive
population which is what I want then the
next thing I have to do is just tell it
which parameter interferon is being
measured on in this case PE sy7 okay so
once I have those three components I
just click Add and it'll add that stat
node to the workspace now I can just
without exiting out of the menu I can
actually just click the drop down menu
and say oh I want to do this also for
the phospho population okay so change
the population over to phospho or we
keep this as median but the parameter
changes here to alexa 488 okay because
that's what I have my phosphoric on let
me add that and then let's change this
over to our perforin positive population
as well okay so median again population
in this case is perforin and the
parameter is going to be PE click Add
okay now we have these three statistics
I want to add them to the chain so that
all samples get that statistic I'm going
to hold down the command key I'm on a
Mac but if you're on a PC it would be
the control key
okay so I highlight these three and now
again all I'm gonna do is right-click
and say copy analysis to group okay so
it makes sure that all of the other
samples pick up that stat node and
you'll see those stat nodes are also
going to take on that red color and
we're just about ready to jump into the
layout editor and start looking at some
of our plots and see what the outcome of
our experiment was okay but before I do
that I'm going to talk a little bit
about the behavior of these gates after
they've been copied to the group okay so
if I just let me close this population
here and I'm gonna work with what we
have in the first sample just so you can
see it easier okay I'm gonna change this
over to interferon and you can see the
gate okay so I have this interferon gate
right my positive gate that I'd set up
by that FMO control if I click on the
gate and I actually move it in this
sample you'll notice that the interferon
gate here changes from the red color
right to black this is telling you that
this gates position is different than
its neighbor okay so the second sample
that I have here you see the interferon
gate is in red but the one up here is in
black this is just telling you that this
gate is different in terms of its
position versus the the other guy so
what we're gonna do here if we want this
gate to go back to how it was before
okay just select the gate either in the
workspace or in the graph window itself
and it's a little counterintuitive but
hit the delete button okay when you hit
delete you get this prompt kind of
erroneously telling you you're gonna
delete your population just say yes and
what I'm gonna do here is I'm gonna move
the graph into view so you can see what
happens when I click yes here and when I
click yes that gate snaps back to the
new position if I move that gate and I
decide you know what this is a better
position for the rest of my samples and
I want to copy that across it's the same
operation as we did when we first
created that gate okay so I move the
gate and now I could say I highlight the
interferon gate here and I could say
okay go ahead and just copy that
analysis to the group
okay and it'll tell me that we already
have a gate do I want to replace it just
say yes okay and now it will update that
gates position for all other samples and
to inspect that you'll see there's these
green arrow keys on the graph window
it's a quick way to kind of march on two
different samples very quickly right
the gates position has been updated
alright so now that we have now that we
have that accomplished the next thing
that we want to do is simply go ahead
and copy these gates to my experiment
group okay and the quick way to do this
without sort of highlighting all of
these guys is just collapse the gate you
see these little black arrows that are
next to your populations if you just
click on them it will expand or contract
the area underneath them okay in your
case what you want to do is just click
the top gate okay not the not the sample
at the top but just the top gate
collapse it and then just drag and drop
that gate onto the experiment group okay
and then that will force all of those
gates to be added to the experiment
group they'll come in collapsed but
don't worry
underneath the edit tab here you have
another function that allows you to
expand these guys right or collapse them
okay so you can expand collapse you can
even collapse or expand selections as
well I'm gonna leave them expanded for
the time being okay we're gonna jump
into the layout editor and before we go
there I'm gonna go ahead and go to the
configure tab and I'm just gonna hide
the stat notes okay I'd like to hide the
stats so that I have an easy way to work
with my populations all right so I
collapse those and now time for the
layout editor
okay the layout editor is where we're
gonna go to create all of our graphical
reports we got all our gates set up
according to our controls now we just
want to create a report and look at you
know which samples responded to our
stimulation or not in my experiment here
I'll explain a little bit about what's
going on we have four samples in each
group essentially each stimulation group
okay the first sample is a non
stimulated sample then I have a
20-minute stim a 1-hour stim and a
two-hour stem okay and then it just
changes over to the next patient so the
patient number two has a non-stem
situation a 20-minute a one hour and a
two our patient number four same thing
non-stem two
one hour two hour okay so it repeats
every four samples so what I'm gonna do
here is I'm gonna take in one of my
terminal dates
okay you can bring in any gates that you
want I have to say at this point in the
analysis it's really up to you what you
want to display and how you want to
display it I'm going to show you some
shortcuts that will hopefully save you
some time okay so I start with the
terminal gate or one of the gates that
I'm using to evaluate whether or not the
sample has actually responded to my
stimulus okay in my case instead of
dragging in all the parental gates and
looking at them in the same context what
I'm gonna do is I'm gonna go ahead and
take this plot when I brought it in here
and I'm going to right-click or
control-click on the plot in the layout
editor and that gives me a drop down
menu okay within that drop down menu
there's an option here for ancestry if
you click on the ancestry button what
this will do is it'll actually show you
a panel that you can increase the size
of you can manipulate here right it'll
show you a panel that contains all of
the gates that you had used right to
create that final terminal population in
the end right so includes all the
important gates that are pertinent to
this population that I'm looking at here
you can bring in your own parental gates
if you want and then arrange them
different ways but I prefer the ancestry
panel because it shows me everything
that's relevant I'm going to delete this
for a second I'm going to show you
another very useful tool that is also
here in the right-click menu and when
you right-click just underneath ancestry
is a back gating panel okay so the back
gating option this will open up the back
gating panel you can adjust the dot size
which is what I recommend here so I say
show large dots when I right-click on
the panel and what this does it will and
enlarge the size of the red dots for
back gating okay so what's going on in
back gating and flo-jo version 10 anyway
we used to have back gating in in the
graph window itself but in version 9 or
a version 10 it's actually here in the
layout editor okay so we have a gate
here right this is our terminal gate
that defines what cells are for
simplicity's sake we're gonna say they
are interferon positive but technically
they are both interferon and cd8
positive but we're gonna use this
terminal gate this one that we have here
this is our what we're saying is
interferon positive all the events that
fall within this gate are gonna be red
that's why they have these red dots
right now as we walk back through the
analysis we're essentially projecting
this terminal gate right backwards
throughout the rest of our analyses so
when I go back to my cd8 positive gate
or the gate that defines my cd8 positive
cells you notice there's a whole bunch
of red dots inside that gate which is
good okay and there are some cells
though that are sort of trickling out
you see these red dots that are outside
of those cd8 positive the cd8 positive
gate that I created these red dots are
cells that are interferon positive but
are not being included in the statistic
down here
not ending up in this terminal gate
that's essentially what the red dots are
telling you okay usually this is not a
concern when you see just a few red dots
falling outside of the the gate right if
there was a cluster here you might want
to come back and expand that cd8
positive gate to include those guys okay
in our case it's not too drastic you
know there's a few cells here and there
and of course there's a certain subset
of cd4 expressing cd8 expressing T cells
that are probably a different
compartment altogether and they too seem
to express interferon and I wouldn't
necessarily extend this gate to go you
know horizontally across the screen here
because I would I'd be including those
cells that are also expressing cd4 to
some extent okay if I walk this back
another step we went after the cd3
positive cells again you see a nice red
cluster here which is good right
but in the cd3 negative compartment
being the quadrant just to the left
there's another cluster of cells right
this is immediately telling us that
there are non T cells in our experiment
that are interferon positive okay so
there are other types of cells that
apparently can express interferon and
I'm not an immunologist but what from
what I've heard other types of cells
like monocytes or NK cells can actually
express interferon as well and so that's
probably why we're getting these red
dots here okay we obviously have some CD
threes there dr+ that are also
expressing cd8 and interferon to some
extent and there's a few that are in the
CD three- dr parameter as well okay and
so on and so forth as you walk back
through the analysis here it just gives
you an idea you know where where those
positive cells lie and whether or not
your gates that are you're using to
capture them are generous enough or not
okay so that's that's essentially
backdating in flo-jo version ten one
thing I should note again is in the
layout editor here all of your gates are
live okay so if I happen to go back
and change the position of that
interferon positive gate right this one
that we're looking at here in the layout
editor got to do a little window
management here I apologize I'll try and
straddle these two so that you can see
what happens when I change that gate so
I'm gonna go down to the bottom here
this graph and this graph are the same
okay so if I come here and I move this
gate over right it's going to update and
then it's also going to update the back
gated populations right the more more
events that we sort of get closer to the
negative here the more red dots you're
going to see and all of the other gates
right so let's take a look here if I
move this watch what happens if I move
this off further towards the right you
see how everything starts to decrease
alright that makes sense
only the super positive cells you know
are ending up in there and then as we go
towards the negative they increase and
of course if we include some negative
events here we're definitely going to
pick up a bunch of others other types of
cells okay so the gates in the layout
editor are live that means that the
layout editor is constantly crunching
looking back at your gates positions
here okay and it will reflect whatever
the most recent changes to the gates are
okay and again since I moved that gate
you'll see that the color has turned
turns from green to black so I'm gonna
go ahead and just return that gate to
its original position I'm gonna say I
hit the delete button and I'm gonna say
yes that snaps the gate back into that
original position all right so let's
come back to the layout editor here
we'll talk about a little bit about
reports and then we'll talk about a more
complicated layout here in a moment okay
so what I'm gonna do is I'll go ahead
and ctrl-c ctrl-v I'll create a separate
panel here and I'm gonna return this guy
I'll make one ancestry and then I'll
have the other one as back gating so
that you can have them side-by-side
right you see it you see how I have
those two panels there okay now you'll
see a whole bunch of these dashed lines
throughout the layout editor all these
do is arrange your page you know so that
you can get your graphs onto you know
onto a single page rather than multiple
pages or having them sort of scattered
about in different orientations
okay so just scroll your mouse over the
intersection between those two lines and
you'll see where the arrow turns into a
plus that's telling you that you can now
manipulate those lines and you can make
anything a landscape or portrait if you
would like okay and the zoom buttons
down here at the bottom help me zoom in
or zoom out to show you guys everything
that we have here in the layout editor
okay now another menu that I haven't
shown you yet is what we call the graph
definition window okay any time you want
to change the labels of the you know of
the of the annotations here if you don't
want this to be comp PE blah blah blah
interferon and you just want it to be
interferon you can override it here I'll
show you how to do that momentarily also
the axes tix if you want to color them
or you want to get rid of them
if you don't like this annotation box
you can get rid of all of that stuff in
what's called a graph definition window
to access that you double click on the
graph and it opens up this menu ok so
there's a right-click menu on the on the
plot and then there's a double click
menu the double click menu affects the
you know the the essentially the
visualization of the plot here okay we
can change the plot type from pseudo
color to anything else like a contour
plot maybe if you want to look at it
that way of course you can show outliers
and you can do all kinds of other things
here that you can also do within the
within the graph window okay so you
could do like a pseudo color smooth
rather than pseudo color dot plot etc
okay on top of that you can change any
of the axes you can change them here or
you can right-click on the axes on the
plot itself to change them over to
something else okay as far as the
annotations are concerned as I mentioned
if you don't like this annotation box
you can unclick uncheck that box click
apply oh you know get rid of it okay if
you don't like the you know population
names or any of the other annotations
that are in the graph you can go ahead
and uncheck these and and then click
apply if we don't want the axes there
all right click that and it dumps
everything if you want to override what
flo-jo has here right and we don't want
to call this comp PE sy7 we want to call
it just interferon right in the x-axis
pane type in interferon for y-axis you
can type in cd8 right then click apply
and it'll replace that okay do this
first so when you bring your plots in
here in the layout editor do these two
the first sets of graphs that you do you
only have to bring in the graphs from
the first sample don't bring in the
graphs from all other samples just
bringing it in from the from the first
okay and I'll explain why in a second
okay then you have fonts and any have
legend annotation so I'm not really
going to talk about these too much but
you know if you want to change the font
color or font size of course you can do
it will see the legend here in a moment
when we create an overlay so I won't
spend any time talking about that but
those those are the controls for them
okay as we did in the workspace we just
created gates on one sample then we drag
and drop to the group and it applied
those gates to everything else okay same
thing in the layout editor we just bring
in you know the sets of gates from that
first sample that we want and then we
just click the batch button to show us
the report for everything that we have
here in our entire experiment okay or in
our experiment group okay so I brought
in that interferon positive population
I've got the answer C and back gating
panels now I just want to create a
report and see what the rest of my
samples look like okay all I have to do
at that point is click the batch button
here I'm just going to make an
adjustment so that you guys can see it
easier I'm going to put it
and one column going down okay and then
I'm going to leave this alone where it
says new layout and I just click the
batch button here and that acts the same
way that the drag-and-drop of the gates
does we click the batch button and then
it shows me okay here's sample number
one right and I have sample number two
it's gates right sample number three
right here we've got some response to
interferon apparently or at least
interferon is being made right sample
number four another one that's got
response to interferon
all right sample five six seven so on
and so forth throughout my experiment
everything is produced here okay and
again this batch report the gates are
live so if I move any of the gates this
batch report gets updated as well
alright so that's a simple batch a
couple of things I'll mention here when
you have a batch output you can save
this entire image right all these guys
that we have here you can save this
entire image if you want go to the file
tab
maybe you're producing figures this is
actually what I recommend if you're
going to produce figures for a paper go
to the file tab go to export image all
rights under the document ban here
and you'll see you have a whole bunch of
image types that you can save as okay
the first four I would not use for
publications simply because the
resolution is not that high okay PDF is
okay PDF gives you 300 dpi that's you
know that's going to be what the
journals want many TIFF is also 300 dpi
what the journals will want and then SVG
this is my favorite SVG stands for
scalable vector graphic what this does
is it allows you when you open an SVG
file up in Adobe Illustrator or Inkscape
there are several other programs that
will open SVG's but when you open up the
SVG you can actually ungroup all of the
objects here so if you need to
manipulate the axes you know a certain
way or you know there's things that you
don't like about how flo-jo produces a
plot maybe you want to get rid of the
lines that surround the plot you can do
that easily if you export as an SVG and
then you open it up in Adobe Illustrator
it's very easy to manipulate downstream
the other thing that's nice about SVG is
that you can expand or contract the
image without losing resolution so you
can expand it to a certain size then
save it at that size to get that
resolution the required resolution for
publication so I highly recommend that
when you're in the layout editor go
ahead and create your layouts then batch
the layouts okay and in the batched
report you can go ahead to the file tab
here and say export image save as SVG
okay the other option that you have
available here there's several different
ways to get outputs from the flo-jo
layout editor okay I showed you what's
underneath the file tab here directly
from the layout your initial layout you
can come here to this little drop down
menu where it says new layouts okay you
can also batch here to printer you can
batch the PowerPoint if you want if you
bash the PowerPoint all of the objects
are going to be treated as an image so
you won't be able to ungroup objects
unfortunately
okay so batching the PowerPoint you get
a slide for each sample and each sample
should be you know each sample should be
its own page essentially you can also
batch here directly to
PDF if you want batch the printer is
nice simply because when you click this
it gives you a nice little you know the
printer spool menu it allows you to tile
your samples in a different way so if
you want to add rows here and different
columns you know you can you can kind of
arrange it here the way you want and
then when you go to print you have the
option to save this as a PDF right or
you can print it of course and then show
the boss or whatever you know you have a
hard copy of it so it allows you to do
three different things all in one menu
option and I think it's a very very
useful one all right that PDF saving as
well will cause you to get 300 dpi so if
you're going to make the figure that's a
really good choice as well alright so
let's take another look at this let's do
a little bit more complicated of a of a
layout right we want to compare let's
say samples one two three and four to
one another and then we want to batch
that okay so what we're gonna do here is
we're gonna create a new layout by
clicking on the plus and then I'm gonna
go ahead and again I'm going to take
that interferon positive population I
have to admit the interferon positive
population is the most interesting of
the three of the three stim or the three
out redoubts that we have so I'm going
to be using those two to go ahead and
create these reports but just keep in
mind you can do you know you can drag
anything you want and look at it any way
you want in the in flo-jo okay so
brought in the interferon positive
population now I want to compare it to
you know the interferon positive
population from samples two three and
four just come back into the workspace
and then either drag it onto the you
know the layout editor itself or drag on
top of the plot when dragging from the
layout or from the workspace okay I'm
going to create an overlay here and
you'll notice that as I create these
layers new colors will be added to that
plot that we have here in the layout
editor and so on sample number three I'm
going to drag that I can drag and drop
it directly onto that plot if I want but
if you can't see the plot don't worry
go ahead and drag and drop it on to the
layout editor itself and then when
you're in position in the layout editor
just drag and drop it on top can you
create an overlay like that we can
rearrange this legend so that's a little
more I don't know in a better more
manageable position okay and now we have
this overlay between our 1st 2nd 3rd and
4th samples that represents my non-stem
my 1-hour my 2-hour and my 20-minute
stem okay sometimes looking at a dot
plot is not the most effective way to
see whether or not something has
responded to stimulus right so let's go
ahead and change this let's make it a
histogram
okay so simply right-click on the
parameter itself ok or control-click if
you're on a Mac and then say histogram
from the drop down menu options it
changes it over to a histogram right
away and you'll notice that the samples
are smashed on top of one another right
again this is not the most intuitive way
to to visualize stimulation alright so
what we're going to do here is again
we're gonna right click on the histogram
plot itself okay and now this gives us
another the same right-click menu except
it's a little bit extended right and
then at the very bottom I hope you all
can see this at the very bottom is an
option where it says histograms and this
will allow you to offset the histograms
ok I'm going to go ahead and choose the
full offset there that'll produce that
histogram plot where all the peaks are
sort of offset from one another
okay and the other thing I should
mention here while I'm on that
histograms menu you can also do
something called a stagger offset or a
half offset okay the stagger offset I
like because it looks really cool
okay it may not be so academically
important but I love the way it looks
okay so you can do that the other thing
that you can do here a lot of times with
our histograms you see how there's these
really tiny Peaks for the negative
population or the the samples that are
actually not responding to the stimulus
you can adjust the scaling here so that
you you normalize by the mode or what we
used to call the percent of max if you
double-click on the plot right we come
back to that graph definition window go
to the specified tab here and you'll see
this y-axis option okay this is only
available when you're looking at
histograms flo-jo Auto scales the data
okay but what you can do here is you can
change this over to modal click apply
and then that will bring up that
negative population so that they're
comparable to what you're seeing in the
samples that are responding okay and if
you want to look at this in the full
offset that give you a better idea of
what it looks like okay so these Peaks
have been brought up as a result of
normalizing to the mode okay so we have
that plot this is essentially what we
want and then we just want to batch this
for all of our other samples okay you'll
notice that when I come up here the
batch outputs are all grayed out anytime
you put two samples over you know in an
overlay with one another you have to
change the batch options and since this
is intro to flo-jo
I'll tell you the easiest way to make
this work for you is to change the
iteration options from off to something
called panel when you do this so
opens a box here asking you how many
samples you want overlaid with one
another okay and at this point you just
tell it for at least in my case it's
four if you had only two you would bump
this up to two maybe but in my case it's
four when I put four back in you see
that my graph restores itself and now
the batch operations are functional
again again I'll go ahead and produce
the batch report into a single column
going down just so it's easy for you to
see okay we create the batch report Izu
min here right and I have patient number
ones data is all together that's the one
we created now we have patient number
two
all right patient number four patient
number 12 patient number 14 so on and so
forth okay and again I can save this as
an SVG I can save it as a PNG blah blah
blah there's so many different types SVG
is my favorite okay followed by PDF and
TIFF because these guys give you good
immediate resolution if your figures are
ready to go okay but SVG is awesome you
can ungroup and manipulate it any way
you want in Illustrator or Inkscape and
get your stuff you know get your stuff
going there are several other tools in
in the layout editor here and I'm just
gonna mention one real quick and then
we'll move on to the table editor
because it's going a little bit long
okay if I right click on the plot itself
you can see this option here for make
multigraph overlays you have an option
here to show n by n plots okay this goes
for any graph it doesn't have to be an
overlay it doesn't even have to be a
histogram can be any plot that you have
you can always show an N by n end by n
plots super cool it shows you you know
every parameter that you have in the
experiment by every other parameter so
we're looking at these populations here
the interferon positive populations but
we're looking across all of the other
markers that we have so sometimes you
might see a population actually pop out
you know your interferon positive
population might also be performed
positive you know or a phospho worth
positive something like that
when you're looking at that n by n so
the N by n is a really nice way to kind
of judge what's happening on along other
parameters that aren't immediately
apparent in the graphs that you're
looking at here that you've dragged in
okay so that's the that's the layout
editor there's a whole bunch of other
tools that we cover in a more advanced
session but for the most part this
should get you this should get you going
when you're doing interest sample
comparisons or you're just trying to
create simple batched outputs okay so
I'm gonna go ahead and close this and
we're gonna go next to the to the table
editor and in order to do that I'm going
to return to the configure tab I'm gonna
return those stat nodes to the workspace
because the table editor well for the
most part
likes statistic nodes it'll take
population notes but statistic nodes are
probably the ones that you want to drag
into the table table editor most often
okay so we're gonna come here the table
editor 6 neck next to the layout editor
we click that little screen okay and I'm
gonna move this off towards the right
and now you just drag in those stat
nodes okay you can bring in to
populations as well so I might bring in
those CD fours and CD eights as well
drag-and-drop them just directly into
that table editor alright here we go now
all of our statistics are listed here
okay and by default
flo-jo any any population node that you
bring in is always going to show you the
frequency of the parents so basically
the statistic that you see in this
column here right cd8 positive it's
telling you the frequency of the parents
so the frequency of CD 3 positives is
essentially 19 we have our cd8 positive
cells represent roughly 19% of all CD 3
positives that we outlined in the gate
above CD fours or 77% etc that's
essentially the statistic that's being
brought here when you drag in the stat
node or sorry the population node and
the stats on the other hand these stat
nodes are including the MFI or the
median for the various the various
readouts that we have all right now you
can quickly create a table if you want I
like to make my tables look really slick
so if you come over here to the
visualize tab what I recommend that you
do is highlight
the statistics that you want heat mapped
in my case I'm holding down the shift
key to highlight everything and then I'm
gonna go ahead and click heat map here
right and then what I'm gonna do is I'm
gonna click the little cog button okay
that little batch button it's the same
button that we had in the layout editor
click on that and boom the table pops up
and you get a nice little heat map here
of that of your statistics okay so
immediately I can see if I ignore the
first two columns this is just
percentage of CD floors and CD a it's
not really informative right but if I
look at the my median of my interferon
okay again the way the samples are
arranged is non-stem twenty minute one
hour one hour two hour right so it for
interferon you can see that the colors
are relatively cool for though non-stem
and the 20 minute stem all right but
after one hour and two hour the
interferon pops up quite a bit and you
can see here that it increases at least
an order of magnitude right we go from
the hundreds into the thousands okay and
that pattern repeats four samples for
samples number two for twelve and
fourteen right it's essentially the same
band pattern first two stim conditions
not much one hour and two our stem is
plenty enough to get some interferon
produced
okay what about phospho work we look at
phospho work here earth essentially has
this opposite kinetics of course
non-stem nothing's going on but within
20 minutes right that 20 minute stem is
actually the peaks in time because we
get a high high production of phospho
work here and then it seems to dampen
after one and two hours it doesn't
return to baseline but it starts to
decrease okay same thing with samples 2
4 12 and 14 right this allows you to
quickly see you know whether or not your
system is is responding what's happening
okay in contrast perforin is all over
the place
perforin really doesn't change too much
with respect to stimulation there's a
little bit of an increase here after one
and two hours in the first page
but for the most part most patients seem
to differ in their perforin expression
by patient rather than by stim condition
so it's more or less I would consider it
more or less a constitutive marker than
one that's actually responding to our
our stimulus okay so another thing you
can do here is double click on any given
column and you can rearrange the stats
from high to low low to high alright
doesn't matter which one if you want it
to go back the way it was before just
simply double click on the name column
here and it'll rearrange them in the
original sort order you can copy and
paste this directly to excel if you'd
like you can also go to the table editor
tab this is a default tab and you can
change this menu option from display 2
to file and then underneath the to file
drop-down menu here you have a whole
bunch of options right you can create a
CSV a text or an excel file there are
some other options but these three by by
and large are the most popular select
what file type you want give it a
destination when you click that button
it asks you for a file name i can call
it jack's table and i put it on the
desktop or somewhere where you know and
then make sure you just click that cog
button ok and when you do that you'll
hear that little chime it'll actually
produce the table on your desktop in my
case hopefully i dumped it on my desktop
and i can show you that it's there ok
apparently i did not so it's not there
but don't worry just tell it where you
want it to go and it should end up there
ok because we're a little bit long on
time i'm going to cut out the table
editor section here and i'm going to
talk briefly about compensation and how
to create a comp matrix in flo-jo now we
have a more detailed discussion of
compensation coming up on the third
Thursday of this month so the next
webinar that we have for flo-jo this
month is going to be discussing
compensation all together ok what I'll
talk to you about today is basically the
basic operation of the comp wizard and
how you essentially would use it and
then next or two weeks from now they're
going to talk a little bit more in depth
about the platform ok by default as I
said flo-jo looks for any file labeled
or unstained and it gets those files
dumped here into the comp group only the
comp group is the one that's able to
activate the comp wizard okay you can
create your own gates if you'd like but
the comp wizard will do it for you so I
usually just click the cop wizard here
you click that rainbow n at the top
right and it goes through each one of
your parameters here and it'll go ahead
and create all the states that it sees
that are necessary for compensation okay
and then it'll open up this little
window off towards the right here this
pane okay this is the comp wizard window
or the comp wizard itself okay all we're
doing here is making sure that the
parameter name matches up with the
sample name right Aard matches with a
ard and therefore you get a green dot
okay PAP ch7 matches with a pc h7 here
in the file name therefore you get a
green dot we go down to pack blue here
you see that file name is labeled P to
be PB right the parameter name is
labeled Pacific blue you get this yellow
dot so there's a little mismatch in the
naming scheme between the file name and
the parameter name and that's what gives
you a yellow dot okay these dot colors
don't tell you anything about the
quality of the matrix they're just
telling you whether or not the parameter
name is matched up to the sample name
okay now each single stain control has
to have a negative population and a
positive population and that's basically
what flo-jo is doing here it's creating
a gate for the negative population for
this particular sample or this
particular parameter okay creates a
negative population for a ard and it
labels what it is here okay the positive
population is in the column to the right
this is the same thing parameter Aard
but it's the positive gate okay this
information translates to the panels
that you see down below okay in the
panel down below you see the Aard
parameter that we're looking at okay so
this is the parameter that is being
measured
aarg right the plot on the left is
written in blue the blue writing here is
corresponding to this
gate name so bead comps us unstained
blah blah blah right is written here as
well that's just telling you what flo-jo
is using as the negative gate or the
negative the negative population for a
ard okay
on the right you'll see another dot plot
right this one is the positive gate so
this is the ard positive gate it's
written in green here this is
essentially these two guys are the same
and that's all it's translating to and
then the graph that you see in the
middle here all this is is an overlay
between this negative population and the
positive population along the a ard
parameter right it's a histogram so
these are counts on the left a ard on
the runner on the x-axis okay so this
first gate here that or the the setup
that we have here is a problem and I
like this dataset because it shows some
of the problems that you have when you
run the wizard and what you have to do
in order to fix them okay when it comes
to single stain controls you never want
to use beads as a negative and cells as
a positive or beads as a positive in
cells as a negative okay then that
violates one of the rules of
compensation which is make sure that the
autofluorescence of your negative
population is the same auto you know has
the same autofluorescence of the
positive population what that translates
to is if you're using beads here you
need to use beads here okay so beats for
negative beads for positive if you're
using cells for negative you need cells
for positive that's basically what that
translates to okay so you never want
cells on one side here and beads on the
other okay so that's a problem that we
need to fix we need to tell flo-jo hey
don't use beads here you need to use
cells okay so that's one problem another
problem is you'll notice that in the
overlay here or the histogram right the
blue peak which corresponds to the
negative population this is right about
where it should be right around zero
okay but the positive peak which is
outlined in green is very close to that
zero
right it's just almost overlapping with
it you're single staying controls should
be bright or at least as bright as you
know the the brightest event that you
have in your data set and obviously we
have dead cells in this experiment but
you know the control that we're using
here is not capturing them and that's
why our positive peak is almost almost
over the the negative peak right so we
basically need separation you should see
separation between the positive and
negative if you look at the sample down
below for a pc h7 you see the negative
peak and the positive peak have a decent
amount of separation between the two you
have almost ten to the fourth out here
and zero over here so almost almost four
logs okay in this case there's hardly
anything separating them well if we
inspect the gate that's being used to
generate this histogram you can see that
that gate is placed over an healthy
population of lymphocytes
scatter ah he's here alright these guys
pretty well waste what we want to do is
we want to capture dead cells though
because dead cells are what are going to
be positive for Aard and so the first
thing we're gonna fix here is that that
histogram and the way to do that is just
double click on the graph itself okay
and now what we're gonna do is we're
going to just move that gate off to the
10:30 11:00 o'clock position here all
right when I do that you notice that
that histogram right suddenly has a
positive peak here out towards the right
and the range gate jumps okay which is
good that's what we want okay dead cells
are gonna be in the lower when I say the
lower left or sometimes creep up a
little bit here in the side scatter they
generally tend to increase inside
scatter as opposed to the the standard
lymphocyte okay so a little bit higher
side scatter move that gate off to the
left we finally get some positivity here
all right so problem number one is
solved for the time being now we just
want to swap this out with we want to
use essentially cells here instead of
beads and what I would like to do is I
would like to use this gate on the cells
I would like to use that for the
negative as well but I would like to use
unstained cells as my negative so if I
come back into the workspace
I can find my Aard sample that is cells
so cell comps these are my cells they're
to be being used there's the size gate
that we just moved okay that's the size
gate that flo-jo is using for the
positive I just want to use that same
size gate but I want to use it for my
unstained cells so you can see here I
have a cell comps us cells us sing or
unstained I head and just simply copy
this gate that I have the size gate here
I'm just going to drag and drop it below
right that unstained sample now it says
cell comps you
blah blah blah and I have that sighs
gate there okay now all you have to do
to override what flo-jo is using here is
just drag and drop this onto the column
all right or that's on to the the the
cell that represents that negative
population okay when I do that you can
see that blue highlight around the cell
that I'm going to drop it on and I'm
going to drop it on that first one
because this is the Aard but go ahead
and drop that all right and it really
places what the wizard had okay so now
I'm using unstained cells with a gate in
roughly the same spot
the right I have a nice negative peak
separated away from my positive peak and
ever I
[Music]
now I just have to scroll through and
make sure that beads beads these are on
the Left beads are on the right and that
there's separation between it too okay
here's another problem
I've got Alexis 647 this was a channel
or a detector that was left open we
didn't actually have a flora chrome here
but flo-jo erroneously picks this guy up
and it puts unstained beads as the
sample control here okay so if I just
come here where it says elected 647 you
can see it's labeled blank click on that
little drop down menu and I can get rid
of it okay I want to remove that
parameter from the analysis okay here's
another instance Alexis 700 now we've
got beads on the left cells on the right
this is not correct okay but for the
interest of time all I'm going to do is
adjust this matrix or adjust this gate
here this is not correct for generating
a matrix but just in the interest of
time I don't want to waste any more time
kind of spending time correcting this
this matrix the rest of the samples look
okay all I would have to do here is swap
out the positive and the are sorry the
the negative gate but the nice thing is
we'll actually get to see what this does
to our data
okay so now let's assume for a second my
incorrect comp matrix that I have here I
want to apply it to my sample so if I go
to the experiment group you see how that
gray grid is there telling me that's the
current matrix that I have then the one
that I'm making right now is called
compensation and it's gonna have a red
color associated with it okay if I want
to apply this matrix click on the apply
to group choose the group you want to
apply it to if I say experiments the
minute I do that that gray grid changes
from gray to red reflecting this color
okay now if I want to return these
samples back to the acquisition defined
matrix right I can double click the grid
here right which does the same thing as
clicking the view matrix button over
here they do the same thing bring you
the same menu ok so if you accidentally
close the wizard window don't be afraid
just double click on the the grey grid
or the colored grid and it'll bring you
to the menu that you need to use ok so
now we want to go back to our
acquisition to find matrix we just
select it here right the one in gray and
then the trick here is to click the m
button click it and drag it click and
drag the M button on to the experiment
group or the all samples group or
whatever you want okay if you want to do
it so that you have a few files that
have one matrix and then other files
that have other matrices you can go
ahead and just drag the matrix onto an
individual file alright and then this
way you can see you have one that's got
red and the other one that's got gray
okay so the group dragging it to the
group adds it to all the samples
dragging it to an individual file just
takes it to that file all right now what
if you want to change these numbers that
are involved here right you don't like
the numbers you want to change them out
well you can click the edit button here
when you have the matrix selected click
Edit it gives you a warning don't do
this you shouldn't change these numbers
okay that's wise advice manipulating
these numbers brings in your own
subjectivity and scientifically it is
not correct okay you the way this table
is generated is by a mathematical
algorithm if your comps are not working
out well you have to consider either the
comp is not good or the panel that
you're working with needs to be
rethought okay so we're going to go
ahead and say yes and that will produce
a copy of that initial matrix that we
had and it's in the copy here that we
can go ahead and change values around
okay so I'm gonna go ahead and enter an
extreme value here for Alexa 700 into
APC h7 I hit the number 90 then I hit
enter right and you can see how I
overcompensate here along this this is
going to be the Alexus APC sorry the ABC
h7 parameter you can see how it
overcompensates right we got events now
that are crashing into the axis okay and
when I hit enter it will also update the
group to actually pick up that that
matrix okay if you want to go back again
let's say click that red click that end
button and then go back to the
experiment group and drop the end button
on okay if you want to save the matrix
go ahead and click Save
I highly recommend you save it as this
flo-jo matrix file that way you know you
save the matrix and when you bring in
samples from this let's say a replicate
experiment but it was done on a
different day you can bring in that
flo-jo matrix file for the original
experiment so that you don't have to
regenerate that that matrix that you did
the day before
okay you can just save it and then apply
it and then just make sure you give it a
name and what you're going to be looking
for when you try to bring it in the next
day is a dot MTX file okay so if you're
if you're you've got this menu open and
you want to bring in matrix that you've
already saved you go ahead and click the
plus button down here at the bottom and
say from file and then when you do that
it'll bring up this file navigation
window and you'll see this dot MTX right
is what you basically want to bring in
you say open and then it will go ahead
and add that it'll go ahead and add that
matrix to the list here it just so
happens that that compensation copy file
that I had was named the same as the one
I had here so it labels it here with a -
one
okay and again once it's listed here
just match the color with what you want
and then drag and drop that end button
onto the experiment group okay the last
thing I'll mention is saving your work
you can save it as a workspace file
which is the most common or you can save
it as a template file I recommend either
workspace or template template all it
does is strip the information about the
FCS files but it keeps all of the group
information and it keeps all of the
gates and all of your reports so you can
use it you know with new files on the
next day really great if you're doing a
lot of repetitive experiments workspace
will retain the file location
okay so just keep in mind that when you
save as a workspace file
flo-jo doesn't actually embed the FCS
files here it just remembers where on
your hard drive those FCS files are
located and when you open it up it it
tries to access those files so if you
move your FCS files into a new location
after creating the workspace
you will have to reassociate those FCS
files with the workspace Atta when you
open it up and you'll see a whole bunch
of red X is going through your workspace
all you have to do to remedy down is
just drag and drop those FCS files on to
the workspace and it will resolve itself
so what I recommend that you do when you
save as workspace is just make sure that
you save the FCS files and the workspace
file in the same folder and that way you
know if you happen to move things around
put stuff on the server blah blah blah
you can always find the workspace files
with their pertinent FCS files then it
helps you to share it too
okay with that I'm gonna open it up to
questions and I'm gonna consider that
the end there are some stuff here
questions I guess in the Q&A box I've
actually never used the Q&A box before
so this is the first time and I
apologize for not having opened it
sooner but we did answer questions in a
chat box so let's see start with number
one let's see we have do we need to put
a single stank single staining control
into compensation yes you do if you are
going to create
compensation matrix if you're not going
to create a compensation matrix it
really doesn't matter where you put the
comp control the reason I created my
experiment group and my my FMO groups is
just so that I can create gates and
reports that are specific to those files
and not have those files show up in my
reports imagine on your graphical
reports you don't want to see your
single stain controls mixed in with your
you know with your experiment files your
single stain controls are for
compensation not for you know not for
analysis
okay so it's up to you but I would put
them in the comp if they're not there
automatically ok so we have another
question that says in flo-jo it won't
let me look at ancestry and back gating
at the same time that's correct you have
to duplicate the graph so make make one
graph duplicate it and then put an
ancestry on one and then back gating on
the other if it's still not letting you
do that I would highly recommend that
either we do a screen share after this
webinar or you contact tech support and
just tell them what you're trying to
what you're trying to do and why it's
not working we will of course ask you
for a file to help us try and reproduce
that error another question here is
let's see ok the batch button doesn't
show up at all on my screen flo-jo 10 on
a PC ok I've got a I've got a resume I
have a I have a solution for you and
that is for the person that doesn't see
the batch button show up at all what
needs to happen is you have your your
your preferences file is is not good and
so basically what you want to do there's
a couple ways you can do this go ahead
and click on your preferences heart icon
in the workspace or anywhere you can
access it and then come down here to the
button that says reset click reset go
ahead and click OK quit out a flo-jo and
then
restart flo-jo and see if the batch
button appears it should appear because
this will essentially refresh your
preferences and and renew that file if
it doesn't we're gonna have to go ahead
and forcibly delete your preferences
file from your system okay but usually
when you start not seeing things on the
on the on flo-jo itself it just means
that you need to delete your preferences
file and start up flo-jo again it should
be fine okay just make sure when you
delete that if you delete the
Preferences file that you delete it
while flo-jo you have to quit flo-jo
first and then go ahead and delete it
from the hard drive okay so another
person asks do we have to include FMOs
in each experiment analysis well I would
say that you know Mario rotor would most
likely say yes because in each analysis
that you're going to be doing you are
going to evaluate some sort of output
some sort of readout and now the
question becomes well where is the
boundary between positive and negative
right how do we know that this
population is positive versus negative
now some populations it's quite obvious
right our CD 3s for example we had a
nice CD three separation away from the
CD three negatives but that population
is not a read out population right so we
could say that you know for CD 3s you
probably don't need probably don't need
an MMO but like I did for my interferon
my phospho Eric and my perforin gates
right those are my readouts and for the
readout populations I would say you
probably want to use an MMO it's going
to give you the best it's gonna give you
the most accurate statistic with respect
to which samples or which cells are
positive for responding to a particular
stimulus or drug or whatever the time
point happens to be the fmos are great
gating controls for that purpose okay
and they show you the boundary between
positive and negative and they're
statistically going to give you the best
the best output
okay of course there is an unstained
sample and all staying one so so okay so
it also the FMO - the interesting thing
here is it kind of depends on how
complicated the experiment is if you
only have two colors you don't need an F
remote control because technically
you're at the mo is the single stain
control okay but if you have I would say
if you have three or more colors you
should be using an MMO especially if
you're looking at a you know you're
using dyes that have significant
spillover into you know into the same
detector okay the reason is the
population the negative population will
actually be a little bit more inflated
compared to the single staying negative
control so if we just look at the single
stain negative control and the FMO
control for say a three color experiment
the FMO controls negative bounds are
going to be a little bit higher than
they are for the single stain control so
what does that mean when we get to your
experiment right if you use that single
stain control it means that in the end
you're under estimating the number of
negative events or overestimating the
number of positive events that are
falling into your date okay it might not
affect the the MFI so much again it
depends but the percentages are
certainly going to be going to be
different so I would i would recommend
FMOs and I hate to say it I know flow
cytometry it's one of those techniques
where there's more control samples than
there are experimental samples that's
probably the most Oh a grating
components of flow cytometry but but you
know you get a heck of a lot of you get
a heck of a lot of data out of flow
cytometry and you know in order to do it
correctly you need to have all the
proper controls and that includes FMOs
so i would i would highly recommend it
you're never going to you're never going
to be sorry if you run your f of
no controls okay
this question here about do we need to
adjust the compensation matrix at all
after it is generated no you do not have
to well do you have to adjust the
compensation matrix well so again what
you mean I think by adjusting the
compensation matrix and pardon me if I'm
making the wrong assumption but I'm
assuming that you mean do you need to
come in here and adjust these numbers I
would not adjust the numbers in a
compensation matrix simply because the
minute I create my own numbers here even
though it makes the populations look
pretty
it adds my own subjectivity and it
doesn't reflect the true being the true
system okay so I wouldn't I would not
adjust the cop matrix values I would go
back to my single stain controls so if I
had a problem with my comp matrix I
would go back to my single stain
controls run the wizard and an attempt
to get a better matrix or one that you
know again has has populations that the
positive population here the median of
the positive matches the median of the
negative population but I would not go
in here and change the numbers if you do
go in there and change the numbers when
you go to publish you better tell people
that that's what you did because
reproducibility in these types of
experiments is extremely difficult if
you come in here and you you're changing
these values and then somebody goes and
tries to repeat what you're doing and
they don't change the values and then
they say hey what gives you know I
wasn't able to get the same results as
so-and-so
okay so let's see here another question
is do you need to adjust the gates for
the compensation matrix yes I would say
a lot of times you do have to adjust the
gates I'm assuming these are the gates
for the gates that are relative to
creating the comp matrix right we went
through this comp wizard and we we
adjusted several components right there
were initially in the ARD gate here you
know this was in the positive I you know
I moved I had to move that size gate
over in order to get some positivity
sometimes the ranged gate in flo-jo here
will be something like this where it'll
include the negative peak you'll have to
definitely come in here and adjust that
gate okay if you have a multi-modal
population just choose the most positive
population okay and the because what
we're trying to do here is we're trying
to get separation right between a
negative and the positive so when you
have cells that you're using for
compensation use the most positive use
the most positive peak if there aren't
enough cells in that peak then walk this
gate backwards until you get a
sufficient number so I would say you
know generally speaking if you've got
about 10 to 15% of events or more you're
doing pretty well but again that depends
on what your total numbers are if it's
10 to 15% of you know a thousand events
you might want to consider upping that
percentage to 250 percent or more
okay so with the singles single staying
controls it's it's it's dependent on
both percentage and numbers of events
all right let's see what is the FMO
control the ethanol control is something
called the fluorescence minus 1 so the
FMO what this is is let's say you have
an experiment that it has only three
colors right let's say the experiment
has fitzy PE and AP AP see you will have
three FML controls one FMO control is a
tube that contains fitzy and PE but no
AP see the next tube is going to contain
a PC and PE but no fitzy and then the
third tube is going to contain fitzy no
PE and it will also contain a PC
okay so FM o stands for flashes
flourescence -1 if you actually type
inflorescence -1 or FM o control into
google you'll see a bunch of tables and
a bunch of articles that are written
about it there's also something called
the purdue list we're a bunch of flow
cytometry questions you can ask
questions to flow cytometry experts that
do various analyses in different fields
and it's a great great resource if
you're starting an experiment that you
are really unfamiliar with and wants
some help that is called the purdue list
and it comes from the purdue university
so if you just type in Purdue list maybe
cytometry it'll pop up you just register
it's totally free and and it's a great
resource to ask the public at large for
tips and tricks on how to run your flow
cytometry experiments how to set up
controls all that kind of stuff for
analysis there's a number of you know
there's a number of resources we have on
our website that will help you with that
but Purdue lists will also help you with
that as well ok we have another question
on the chat box so I'm sort of
straddling here the chat box as well as
the Q&A boxes so I'm trying to to
straddle both ok so that was not a
question that was just to thank you all
right well you're very welcome again if
you guys have any more questions you can
either use the Q&A box here or the chat
box I'm watching them both but if not I
want to say thank you all for attending
and you know my email is simply Jack at
Flo Jo comms pretty simple pretty small
company and also please you know if you
have trouble just go ahead and and email
tech support at Flo Jo comm and if you
have any other questions you know if
you've got science questions or whatnot
feel free to email me I like talking
tech so any anything that that you have
in mind by all means go ahead and let me
know if I don't see another question pop
up in either box I am going to go ahead
and wrap this up
and we will have the
according of this website or of this
website of this webinar on our website
within well definitely within 24 hours I
think it'll be within the hour so if you
missed anything or would like to you
know review by all means you can access
it and of course if you want to share it
that would be that would be great too
alright we've got another question here
yes it says when you see all staining
fail completely when you've when you've
successfully used the antibodies
antibodies before what could it be
okay so there's a number of things here
but the organic dyes that are used that
are attached to your antibodies right
are extremely sensitive to light heat
and even you know over time because
they're in solution you know mm-hmm the
water molecule salt molecules everything
that you have in a solution those atoms
or molecules are bouncing into one
another over time and so eventually you
know given given enough time they will
actually degrade now you have some dyes
that are much more sensitive than others
and those are the tandem dyes the tandem
dyes are extremely sensitive to light
temperature and time so with tandem dyes
you have to be very careful you have to
use the dyes within the allotted time
and you always always always have to run
your single stain controls with those
tandem dyes every time you run an
experiment because you cannot count on
the tandem dyes to have the same
fluorescence day-to-day means just
simply because that's a you know it's a
it's a component of the of the reagent
itself now other things that could cause
the staining is staining to fail
completely I mean if you're using the
same protocol let's say that that it
worked the first time but it didn't work
the second time I'm gonna make the
assumption then that you use the same
buffer conditions use the same salt
conditions the the other thing it could
be is just simply that the organic dye I
and you know was exposed to light or to
room temperature for too long and now it
doesn't light up one
way to kind of test whether it's the
epitope binding or not is you have a
couple options right you could actually
try a Western blot for the antigen that
that you're looking for or you could try
using a secondary antibody to that
primary that you have that you know has
a you know a fit C or some good good
marker associated with it and if the
secondary shows up but your primary you
know your primary doesn't then that
means just that your organic dye
associated with that antibody has
probably probably gone bad
you
all right so again just looking for
questions in either the chat box so the
QA
and if not I am going to bid you all a
wonderful afternoon and again please
check out our website and if you want to
use any of our new tools just go ahead
and download the latest version of
flo-jo or download SeatGeek
or sign up for a flo-jo envoy trial and
I will bid you adieu all right thank you
all have a great day
you