> RE: DNA analysis software
>
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> > De Novo Software
> > david.n...@denovosoftware.com
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From: Mitch Haynes <mitchhay...@gmail.com>
Date: Thu, 17 Jan 2008 11:52:56 -0800 (PST)
Local: Thurs, Jan 17 2008 1:52 pm
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RE: gate-specific data cropping
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From: VSH Tech Support <T...@vsh.com>
Date: Fri Feb 16 2007 - 09:01:56 EST
Stevan
At the risk of sounding like a commercial, WinList can do exactly what
you
want. The problem of "sucking up air" or perhaps having a clogged
nozzle at
the end of a run has gotten all of us at one time or another, and then
the
data (most of which is probably fine) appears to be unusable. WinList
addresses this issue with the FTIM parameter, which is basically a
"chronology" parameter defined over 1024 channels. Each event is
assigned
an FTIM channel based on its order in the listmode file, channel zero
having
the first n/1024 events, and channel 1023 having the last n/1024
events.
Displaying a 2P dot plot of FTIM vs. side scatter, for example, will
clearly
show the aberrant events. You may then gate on the "good" events, or
gate
out the "bad" events. Either way, you can salvage an otherwise bad
run.
You can also save the gated listmode using WinList's Save Data Source
option, and it will contain only
the "good" events. Another feature of the Save Data Source option is
the
ability to set the number of events to save in the listmode file,
which at
least partially addresses the desire to save a larger file into
smaller
segments that will each have the same number of events within given
regions,
as you are requesting.
Best regards,
Don
Donald J. Herbert
Technical Support Manager
Verity Software House
-----Original Message-----
From: Stevan Lauriault [mailto:ste...@lauriault.com]
Sent: Friday, February 09, 2007 6:24 PM
To: cyto-inbox
Subject: Re: gate-specific data cropping
Thanks for your very helpful comments. I guess what I am trying to
get
at
is this: is
there any analysis software available that can reduce list mode data
in a
reverse order-specific matter (in reverse sequence)? Correct me if
I'm
wrong, but I believe this function would also help in the event that a
user
lets a sample run dry and sucks up air bubbles, or over collects their
intended gating target (for example, in acquisition and storage, 5000
of
R1).
Thanks,
Stevan
---------- Original Message ----------------------------------
From: "Byron Ellis" <bcel...@stanford.edu>
Date: Wed, 7 Feb 2007 16:21:28 -0800
>On 2/7/07, Stevan Lauriault <ste...@lauriault.com> wrote:
>> Hi and thanks,
>> Since we want to directly compare MFIs (in FL2) between any two
>> subsets (R1 vs. R3)
>that are isolated on a bivariate dot plot (FL1 vs. FL4), doing so in
>separate sample tubes would introduce the extra probability of
>experimental
error between sample tubes.
>Directly comparing the subsets from the same sample tube, and even
>better, the same data set, would eliminate this extra unknown.
>It doesn't necessarily eliminate the unknown, it may just keep you from
>finding out about it. If you were to prepare one sample on Monday, see
[quoted text clipped - 4 lines]
>surprised if that actually happened in your case? Yes.
>Would I do replicates anyway? Yes.
>> Let us say we have acquired 100,000 total events (stained with 3
>> fluorochromes,
[quoted text clipped - 4 lines]
>Within those 100,000 total events, there are 500 of R1, 700 of R2 and
>1200
of R3.
>> If we crop the 100,000 total events to 75,000 total events (from the
>> top in
>stack-collected data), there will become exactly 500 events in the R2
region. If we
crop
>the 100,000 total events to 40,000 total events, there will become 500
events in R3.
>> Now the three populations; R1, R2, and R3 each have exactly 500 total
>> events, and we
>can directly compare MFIs among the subsets that have identical sample
sizes. We could
>also then say that, when comparing means between these subsets under
>identical experimental conditions, Rx gives a consistently higher
fluorescent signal than Ry.
>Well, depending on what you're doing (you've never said how you intend
>to compare means), equal sample sizes is not particularly required so
[quoted text clipped - 4 lines]
>one-sided t-tests essentially, that give you directionality statements
>such as mu_{R_1} > mu_{R_2} ). In this case your assumptions are:
>1. Each group is independent
>2. Normality of group populations (or at least "close enough" to
>Normal) 3. The _population_ variances of the dependent variable for
>each group are equal (or pretty close). (Actually check this. It would
>be unsurprising to encounter large differences in the population
>variances among your different groups).
>Like I say, it depends a bit on what you intend to do for your
>analysis. For example, _two_-way ANOVA actually expects equal sample
>sizes.
>> Is this a reasonable strategy? Is there any software available that
>> can perform this
>function?
>On an FCS file directly? Probably not (neither the manipulation of the
>flow data nor the testing). Once you've got the data out of FCS form
>and appropriately labeled with group membership or split into separate
>files or something similar, then any reasonable statistics package
>(Excel is not included in the list of reasonable statistics packages)
>can perform the statistical tests.
>Personally, I use R (http://www.r-project.org) for analyzing all the
>flow data I have, but it can be intimidating for new users (though
[quoted text clipped - 8 lines]
>expect to be available in the next Bioconductor release (probably
>sometime in April).
>Hope that helps,
>Byron
>> Kind Regards,
>> Stevan Lauriault
>> ---------- Original Message ----------------------------------
>> From: "Byron Ellis" <bcel...@stanford.edu>
>> Date: Tue, 6 Feb 2007 12:17:35 -0800
>> >Speaking as a statistician, I would not count running the same tube
>> >3 times or simply cutting the FCS file (the two are equivalent) as
[quoted text clipped - 5 lines]
>> >biological variability of the cells and a single sample preparation
>> >only
captures the latter.
>> >On 2/5/07, Stevan Lauriault <ste...@lauriault.com> wrote:
>> >> Dear All,
>> >> Question:
>> >> We are isolating leukocyte subsets to measure and compare relative
>> >> levels of
[quoted text clipped - 5 lines]
>> >> statistically analyze the relative mean fluorescence intensities
>> >> of a
biomarker, among the subsets.
>> >> To get statistically comparable sample sizes among these subsets,
>> >> we are running
the
>same
>> >> tube three times and changing the storage criteria to 500 events
[quoted text clipped - 9 lines]
>> >> events, three times to get an identical sample size for all three
>> >> gated subsets
(R1,
>R2,
>> >> and R3).
>> >> Scientifically, this shouldn't be a problem, since flow cytometry
>> >> data is collected randomly within the same sample tube. Not only
[quoted text clipped - 6 lines]
>> >> scientists might be uneasy with the idea of manipulating raw
>> >> list-mode
data.
>> >> However, Since the data is collected randomly from the same
>> >> sample, doing this
[quoted text clipped - 3 lines]
>only
>> >> be cropping (from stack-collected data) the most recent events
collected.
>> >> Currently, we are acquiring 3 different data files for each tube,
>> >> and adjusting the acquisition and storage settings for each
>> >> acquisition. Is there a way to perform a gate-specific data
>> >> cropping function with any current flow cytometry data analysis
software?
>> >> Kind Regards,
>> >> Stevan Lauriault
>> >> ________________________________________________________________
>> >> Sent via the WebMail system at lauriault.com
>> >--
>> >Byron Ellis (byron.el...@gmail.com)
>> >"Oook" -- The Librarian
>> ________________________________________________________________
>> Sent via the WebMail system at lauriault.com
>--
>Byron Ellis (byron.el...@gmail.com)
>"Oook" -- The Librarian
________________________________________________________________
Sent via the WebMail system at lauriault.com
Received on Fri Feb 16 16:38:00 2007
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RE: DNA analysis software
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From: VSH Tech Support <T...@vsh.com>
Date: Wed Feb 21 2007 - 11:29:45 EST
Hello Ibtissam,
ModFit LT, for PC or Mac, has advanced modeling capability for
research
applications in DNA cell cycle analysis. You may use any of the model
templates the program offers, or create your own models for non-
traditional
analysis, including non-mammalian DNA cell cycle studies. ModFit LT
can be
linked to our WinList program to provide a complete cell cycle
analysis on
any number of sub-populations with a single click of a button.
For an overview, visit <http://www.vsh.com/products>
http://www.vsh.com/products .
Best regards,
Don
Donald J. Herbert
Technical Support Manager
Verity Software House
________________________________
From: Ibtissam Abdul-Jabbar [mailto:iajab...@cicr.uq.edu.au]
Sent: Wednesday, February 14, 2007 11:41 PM
To: cyto-inbox
Subject: DNA analysis software
Dear All, before buying software to analyse DNA on PC, I would like to
get
your opinion. I already have ModFit for Macintosh.
What are you using and what do you recommend for research purposes.
Is MultiCycle Av the one of choice?
I appreciate your comments.
Ibtissam A Jabbar (PhD)
Manager of the FACS facilities
Diamantina Institute for Cancer, Immunology and Metabolic Medicine
(DI)
The University of Queensland
Level 4 R Wing
Princess Alexandra Hospital
Ipswich Rd Buranda QLD 4102
Australia
Ph: 07 3240 5945
Fax: 07 3240 5946
Mob: 0401154744
Received on Thu Feb 22 15:18:00 2007
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Re: gate-specific data cropping
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From: WEHICytometry <facs_c...@wehi.EDU.AU>
Date: Mon Feb 12 2007 - 18:25:38 EST
Stevan,
For what it's worth, we have a utility we call Hackit that can crop
cells from the front or back of a FCS file ( see http://
www.wehi.edu.au/cytometry/freesoftware/index.html). We use it for
the tasks you suggest in cleaning up violated data. I don't know
how
useful that would be for your current purpose because it can't do
gating; numbers clipped are total cell numbers. I guess if you knew
the proportions of your gated cells you could eventually clip out
the
file segments you need.
Frank Battye.
On 10/02/2007, at 10:24 AM, Stevan Lauriault wrote:
> Thanks for your very helpful comments. I guess what I am trying to
> get at is this: is
[quoted text clipped - 7 lines]
> example, in acquisition and
> storage, 5000 of R1).
| | << The Cytometry Laboratory
\__/ <<<< The Walter & Eliza Hall Institute
------!!<<<<<< 1G Royal Parade, Parkville
/!!\ <<<< Victoria 3050, Australia
o !! \ << ph: 61_3_9345 2540, fax: 61_3_9347 0852
Received on Tue Feb 13 15:18:00 2007
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Re: gate-specific data cropping
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From: Stevan Lauriault <ste...@lauriault.com>
Date: Fri Feb 09 2007 - 18:24:07 EST
Thanks for your very helpful comments. I guess what I am trying to
get
at is this: is
there any analysis software available that can reduce list mode data
in a reverse
order-specific matter (in reverse sequence)? Correct me if I'm wrong,
but I believe this
function would also help in the event that a user lets a sample run
dry and sucks up air
bubbles, or over collects their intended gating target (for example,
in acquisition and
storage, 5000 of R1).
Thanks,
Stevan
---------- Original Message ----------------------------------
From: "Byron Ellis" <bcel...@stanford.edu>
Date: Wed, 7 Feb 2007 16:21:28 -0800
>On 2/7/07, Stevan Lauriault <ste...@lauriault.com> wrote:
>> Hi and thanks,
>> Since we want to directly compare MFIs (in FL2) between any two subsets (R1 vs. R3)
>that are isolated on a bivariate dot plot (FL1 vs. FL4), doing so in separate sample
>tubes would introduce the extra probability of experimental error between sample tubes.
>Directly comparing the subsets from the same sample tube, and even better, the same data
>set, would eliminate this extra unknown.
>It doesn't necessarily eliminate the unknown, it may just keep you
>from finding out about it. If you were to prepare one sample on
[quoted text clipped - 4 lines]
>would I be surprised if that actually happened in your case? Yes.
>Would I do replicates anyway? Yes.
>> Let us say we have acquired 100,000 total events (stained with 3 fluorochromes,
>measured in FL1, FL2, and FL4 respectively). We are using a bivariate dot plot of FL1
>vs. FL4 in which we are isolating 3 subsets (R1, R2, and R3) based on their relative
>expressions of FL1 vs. FL4. We then want to compare the MFIs, as measured in FL2, among
>these subsets. Within those 100,000 total events, there are 500 of R1, 700 of R2 and
>1200 of R3.
>> If we crop the 100,000 total events to 75,000 total events (from the top in
>stack-collected data), there will become exactly 500 events in the R2 region. If we
crop
>the 100,000 total events to 40,000 total events, there will become 500 events in R3.
>> Now the three populations; R1, R2, and R3 each have exactly 500 total events, and we
>can directly compare MFIs among the subsets that have identical sample sizes. We could
>also then say that, when comparing means between these subsets under identical
>experimental conditions, Rx gives a consistently higher fluorescent signal than Ry.
>Well, depending on what you're doing (you've never said how you intend
>to compare means), equal sample sizes is not particularly required so
[quoted text clipped - 4 lines]
>one-sided t-tests essentially, that give you directionality statements
>such as mu_{R_1} > mu_{R_2} ). In this case your assumptions are:
>1. Each group is independent
>2. Normality of group populations (or at least "close enough" to Normal)
>3. The _population_ variances of the dependent variable for each group
>are equal (or pretty close). (Actually check this. It would be
>unsurprising to encounter large differences in the population
>variances among your different groups).
>Like I say, it depends a bit on what you intend to do for your
>analysis. For example, _two_-way ANOVA actually expects equal sample
>sizes.
>> Is this a reasonable strategy? Is there any software available that can perform this
>function?
>On an FCS file directly? Probably not (neither the manipulation of the
>flow data nor the testing). Once you've got the data out of FCS form
>and appropriately labeled with group membership or split into separate
>files or something similar, then any reasonable statistics package
>(Excel is not included in the list of reasonable statistics packages)
>can perform the statistical tests.
>Personally, I use R (http://www.r-project.org) for analyzing all the
>flow data I have, but it can be intimidating for new users (though
[quoted text clipped - 8 lines]
>expect to be available in the next Bioconductor release (probably
>sometime in April).
>Hope that helps,
>Byron
>> Kind Regards,
>> Stevan Lauriault
>> ---------- Original Message ----------------------------------
>> From: "Byron Ellis" <bcel...@stanford.edu>
>> Date: Tue, 6 Feb 2007 12:17:35 -0800
>> >Speaking as a statistician, I would not count running the same tube 3
>> >times or simply cutting the FCS file (the two are equivalent) as three
[quoted text clipped - 4 lines]
>> >due to experimental error as well as the biological variability of the
>> >cells and a single sample preparation only captures the latter.
>> >On 2/5/07, Stevan Lauriault <ste...@lauriault.com> wrote:
>> >> Dear All,
>> >> Question:
>> >> We are isolating leukocyte subsets to measure and compare relative levels of
>expression
>> >> of certain antigens. For example, there are three subsets within a bivariate dot
>plot;
>> >> gated on R1, R2 and R3 respectively, and we would like to statistically analyze the
>> >> relative mean fluorescence intensities of a biomarker, among the subsets.
>> >> To get statistically comparable sample sizes among these subsets, we are running
the
>same
>> >> tube three times and changing the storage criteria to 500 events for each subset
[quoted text clipped - 5 lines]
>total
>> >> events, three times to get an identical sample size for all three gated subsets
(R1,
>R2,
>> >> and R3).
>> >> Scientifically, this shouldn't be a problem, since flow cytometry data is collected
>> >> randomly within the same sample tube. Not only could we run one acquisition to get
[quoted text clipped - 3 lines]
>some
>> >> scientists might be uneasy with the idea of manipulating raw list-mode data.
>> >> However, Since the data is collected randomly from the same sample, doing this
>should
>> >> give exactly the same readings as if we just collected less events, since we would
>only
>> >> be cropping (from stack-collected data) the most recent events collected.
>> >> Currently, we are acquiring 3 different data files for each tube, and adjusting the
>> >> acquisition and storage settings for each acquisition. Is there a way to perform a
>> >> gate-specific data cropping function with any current flow cytometry data analysis
>> >> software?
>> >> Kind Regards,
>> >> Stevan Lauriault
>> >> ________________________________________________________________
>> >> Sent via the WebMail system at lauriault.com
>> >--
>> >Byron Ellis (byron.el...@gmail.com)
>> >"Oook" -- The Librarian
>> ________________________________________________________________
>> Sent via the WebMail system at lauriault.com
>--
>Byron Ellis (byron.el...@gmail.com)
>"Oook" -- The Librarian
________________________________________________________________
Sent via the WebMail system at lauriault.com
Received on Mon Feb 12 12:18:00 2007
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RE: gate-specific data cropping
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From: Nebe-Von-Caron, G <g.nebe-von-ca...@unipath.com>
Date: Thu Feb 08 2007 - 09:36:37 EST
The number of events collected will not be the influential thing as
with
a minimum of 500 events you get already a damn good estimate of your
MFI. Just as an educational exercise you should do is to look at MFI
estimate of one population over events. It should indicate that your
estimate if the sample mean after 100 "samples" (each cell being a
sample on its own) is already pretty good. You might want to look at
the
distribution of mean fluorescence or more important of single event
residuals (distance from mean) over time to see if they show a trend
which would indicate an unstable measurement.
In the sample you propose you are more likely to see differences based
on compensation variation between your 3 populations which again is
independent of the number of events looked at if more than 500 have
been
measured. It would indeed be interesting to see how much variation you
get in mfi between independent tubes as you are more likely to
increase
variation by the sample processing than by the measurement.
One control for your experiment would be to test the MFI distribution
by
swapping fluorochromes to demonstrate that you are independent of
compensation and to show that the change in MFI is not dependent of
steric hindrance or FRET, depending of the experimental / instrument
details.
Regards
Gerhard
> -----Original Message-----
> From: Stevan Lauriault [mailto:ste...@lauriault.com]
> Sent: 07 February 2007 15:16
> To: Cytometry Mailing List
> Subject: Re: gate-specific data cropping
> Hi and thanks,
> Since we want to directly compare MFIs (in FL2) between any
> two subsets (R1 vs. R3) that are isolated on a bivariate dot
[quoted text clipped - 3 lines]
> Directly comparing the subsets from the same sample tube, and
> even better, the same data set, would eliminate this extra unknown.
> Let us say we have acquired 100,000 total events (stained
> with 3 fluorochromes, measured in FL1, FL2, and FL4
[quoted text clipped - 4 lines]
> Within those 100,000 total events, there are 500 of R1, 700
> of R2 and 1200 of R3.
> If we crop the 100,000 total events to 75,000 total events
> (from the top in stack-collected data), there will become
> exactly 500 events in the R2 region. If we crop the 100,000
> total events to 40,000 total events, there will become 500
> events in R3.
> Now the three populations; R1, R2, and R3 each have exactly
> 500 total events, and we can directly compare MFIs among the
> subsets that have identical sample sizes. We could also then
> say that, when comparing means between these subsets under
> identical experimental conditions, Rx gives a consistently
> higher fluorescent signal than Ry.
> Is this a reasonable strategy? Is there any software
> available that can perform this
> function?
> Kind Regards,
> Stevan Lauriault
> ---------- Original Message ----------------------------------
> From: "Byron Ellis" <bcel...@stanford.edu>
> Date: Tue, 6 Feb 2007 12:17:35 -0800
> >Speaking as a statistician, I would not count running the
> same tube 3
[quoted text clipped - 8 lines]
> >to experimental error as well as the biological variability of the
> >cells and a single sample preparation only captures the latter.
> >On 2/5/07, Stevan Lauriault <ste...@lauriault.com> wrote:
> >> Dear All,
> >> Question:
> >> We are isolating leukocyte subsets to measure and compare relative
> >> levels of
[quoted text clipped - 7 lines]
> intensities of a
> >> biomarker, among the subsets.
> >> To get statistically comparable sample sizes among these
> subsets, we
[quoted text clipped - 17 lines]
> R2,
> >> and R3).
> >> Scientifically, this shouldn't be a problem, since flow cytometry
> >> data is collected randomly within the same sample tube. Not only
[quoted text clipped - 5 lines]
> >> can see why some scientists might be uneasy with the idea of
> >> manipulating raw list-mode data.
> >> However, Since the data is collected randomly from the
> same sample,
[quoted text clipped - 3 lines]
> >> be cropping (from stack-collected data) the most recent events
> >> collected.
> >> Currently, we are acquiring 3 different data files for
> each tube, and
[quoted text clipped - 3 lines]
> function with
> >> any current flow cytometry data analysis software?
> >> Kind Regards,
> >> Stevan Lauriault
> >> ________________________________________________________________
> >> Sent via the WebMail system at lauriault.com
> >--
> >Byron Ellis (byron.el...@gmail.com)
> >"Oook" -- The Librarian
> ________________________________________________________________
> Sent via the WebMail system at lauriault.com
Received on Thu Feb 8 14:38:00 2007
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Re: gate-specific data cropping
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From: Byron Ellis <bcel...@stanford.edu>
Date: Wed Feb 07 2007 - 19:21:28 EST
On 2/7/07, Stevan Lauriault <ste...@lauriault.com> wrote:
> Hi and thanks,
> Since we want to directly compare MFIs (in FL2) between any two subsets (R1 vs. R3)
that are isolated on a bivariate dot plot (FL1 vs. FL4), doing so in
separate sample
tubes would introduce the extra probability of experimental error
between sample tubes.
Directly comparing the subsets from the same sample tube, and even
better, the same data
set, would eliminate this extra unknown.
It doesn't necessarily eliminate the unknown, it may just keep you
from finding out about it. If you were to prepare one sample on
Monday, see significant differences, celebrate, etc and then on
Wednesday prepare another sample where you didn't you'd probably want
to know that (and figure out why). Simply taking the FACS tube off the
cytometer and putting it back on won't give you that information. Now,
would I be surprised if that actually happened in your case? Yes.
Would I do replicates anyway? Yes.
> Let us say we have acquired 100,000 total events (stained with 3 fluorochromes,
measured in FL1, FL2, and FL4 respectively). We are using a bivariate
dot plot of FL1
vs. FL4 in which we are isolating 3 subsets (R1, R2, and R3) based on
their relative
expressions of FL1 vs. FL4. We then want to compare the MFIs, as
measured in FL2, among
these subsets. Within those 100,000 total events, there are 500 of
R1, 700 of R2 and
1200 of R3.
> If we crop the 100,000 total events to 75,000 total events (from the top in
stack-collected data), there will become exactly 500 events in the R2
region. If we crop
the 100,000 total events to 40,000 total events, there will become 500
events in R3.
> Now the three populations; R1, R2, and R3 each have exactly 500 total events, and we
can directly compare MFIs among the subsets that have identical sample
sizes. We could
also then say that, when comparing means between these subsets under
identical
experimental conditions, Rx gives a consistently higher fluorescent
signal than Ry.
Well, depending on what you're doing (you've never said how you intend
to compare means), equal sample sizes is not particularly required so
there's no particular reason to cut the data to obtain equal sample
sizes. For example, one-way ANOVA (or one-way ANOVA with repeated
measure in the event that you chose to do _real_ replicates), which
simply says "they're different" (there are other tests, variants of
one-sided t-tests essentially, that give you directionality statements
such as mu_{R_1} > mu_{R_2} ). In this case your assumptions are:
1. Each group is independent
2. Normality of group populations (or at least "close enough" to
Normal)
3. The _population_ variances of the dependent variable for each group
are equal (or pretty close). (Actually check this. It would be
unsurprising to encounter large differences in the population
variances among your different groups).
Like I say, it depends a bit on what you intend to do for your
analysis. For example, _two_-way ANOVA actually expects equal sample
sizes.
> Is this a reasonable strategy? Is there any software available that can perform this
function?
On an FCS file directly? Probably not (neither the manipulation of the
flow data nor the testing). Once you've got the data out of FCS form
and appropriately labeled with group membership or split into separate
files or something similar, then any reasonable statistics package
(Excel is not included in the list of reasonable statistics packages)
can perform the statistical tests.
Personally, I use R (http://www.r-project.org) for analyzing all the
flow data I have, but it can be intimidating for new users (though
extremely powerful once you learn to use it). There are two packages
in R for manipulating flow data at the moment (prada and rflowcyt),
available through the Bioconductor Project
(http://www.bioconductor.org) that can actually read in and manipulate
FCS data directly or slightly manipulated data from say FlowJo (so you
can do your gating there for example). I'm also part of a group made
up of the people who did rflowcyt and prada that are making a combined
package of the best bits of both (and some other new bits) that we
expect to be available in the next Bioconductor release (probably
sometime in April).
Hope that helps,
Byron
> Kind Regards,
> Stevan Lauriault
> ---------- Original Message ----------------------------------
> From: "Byron Ellis" <bcel...@stanford.edu>
> Date: Tue, 6 Feb 2007 12:17:35 -0800
> >Speaking as a statistician, I would not count running the same tube 3
> >times or simply cutting the FCS file (the two are equivalent) as three
[quoted text clipped - 4 lines]
> >due to experimental error as well as the biological variability of the
> >cells and a single sample preparation only captures the latter.
> >On 2/5/07, Stevan Lauriault <ste...@lauriault.com> wrote:
> >> Dear All,
> >> Question:
> >> We are isolating leukocyte subsets to measure and compare relative levels of
expression
> >> of certain antigens. For example, there are three subsets within a bivariate dot
plot;
> >> gated on R1, R2 and R3 respectively, and we would like to statistically analyze the
> >> relative mean fluorescence intensities of a biomarker, among the subsets.
> >> To get statistically comparable sample sizes among these subsets, we are running the
same
> >> tube three times and changing the storage criteria to 500 events for each subset
> >> (example, the first run is 500 events of R1, the second 500 of R2, and the third is
500
> >> of R3). Instead of repeating the same tube three times, and wasting valuable
sample, it
> >> seems like a good idea to "crop" a preexisting data file of, for example, 100,000
total
> >> events, three times to get an identical sample size for all three gated subsets (R1,
R2,
> >> and R3).
> >> Scientifically, this shouldn't be a problem, since flow cytometry data is collected
> >> randomly within the same sample tube. Not only could we run one acquisition to get
> >> different monocyte subset populations, but also to statistically compare constant
numbers
> >> of monocytes, PMNs, lymphocytes, lymphocyte subsets, etc. However, I can see why
some
> >> scientists might be uneasy with the idea of manipulating raw list-mode data.
> >> However, Since the data is collected randomly from the same sample, doing this
should
> >> give exactly the same readings as if we just collected less events, since we would
only
> >> be cropping (from stack-collected data) the most recent events collected.
> >> Currently, we are acquiring 3 different data files for each tube, and adjusting the
> >> acquisition and storage settings for each acquisition. Is there a way to perform a
> >> gate-specific data cropping function with any current flow cytometry data analysis
> >> software?
> >> Kind Regards,
> >> Stevan Lauriault
> >> ________________________________________________________________
> >> Sent via the WebMail system at lauriault.com
> >--
> >Byron Ellis (byron.el...@gmail.com)
> >"Oook" -- The Librarian
> ________________________________________________________________
> Sent via the WebMail system at lauriault.com
--
Byron Ellis (byron.el...@gmail.com)
"Oook" -- The Librarian
Received on Thu Feb 8 14:58:00 2007
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Re: gate-specific data cropping
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From: Stevan Lauriault <ste...@lauriault.com>
Date: Wed Feb 07 2007 - 10:16:03 EST
Hi and thanks,
Since we want to directly compare MFIs (in FL2) between any two
subsets (R1 vs. R3) that
are isolated on a bivariate dot plot (FL1 vs. FL4), doing so in
separate sample tubes
would introduce the extra probability of experimental error between
sample tubes.
Directly comparing the subsets from the same sample tube, and even
better, the same data
set, would eliminate this extra unknown.
Let us say we have acquired 100,000 total events (stained with 3
fluorochromes, measured
in FL1, FL2, and FL4 respectively). We are using a bivariate dot plot
of FL1 vs. FL4 in
which we are isolating 3 subsets (R1, R2, and R3) based on their
relative expressions of
FL1 vs. FL4. We then want to compare the MFIs, as measured in FL2,
among these subsets.
Within those 100,000 total events, there are 500 of R1, 700 of R2 and
1200 of R3.
If we crop the 100,000 total events to 75,000 total events (from the
top in
stack-collected data), there will become exactly 500 events in the R2
region. If we crop
the 100,000 total events to 40,000 total events, there will become 500
events in R3.
Now the three populations; R1, R2, and R3 each have exactly 500 total
events, and we can
directly compare MFIs among the subsets that have identical sample
sizes. We could also
then say that, when comparing means between these subsets under
identical experimental
conditions, Rx gives a consistently higher fluorescent signal than Ry.
Is this a reasonable strategy? Is there any software available that
can perform this
function?
Kind Regards,
Stevan Lauriault
---------- Original Message ----------------------------------
From: "Byron Ellis" <bcel...@stanford.edu>
Date: Tue, 6 Feb 2007 12:17:35 -0800
>Speaking as a statistician, I would not count running the same tube 3
>times or simply cutting the FCS file (the two are equivalent) as three
[quoted text clipped - 4 lines]
>due to experimental error as well as the biological variability of the
>cells and a single sample preparation only captures the latter.
>On 2/5/07, Stevan Lauriault <ste...@lauriault.com> wrote:
>> Dear All,
>> Question:
>> We are isolating leukocyte subsets to measure and compare relative levels of
expression
>> of certain antigens. For example, there are three subsets within a bivariate dot
plot;
>> gated on R1, R2 and R3 respectively, and we would like to statistically analyze the
>> relative mean fluorescence intensities of a biomarker, among the subsets.
>> To get statistically comparable sample sizes among these subsets, we are running the
same
>> tube three times and changing the storage criteria to 500 events for each subset
>> (example, the first run is 500 events of R1, the second 500 of R2, and the third is
500
>> of R3). Instead of repeating the same tube three times, and wasting valuable sample,
it
>> seems like a good idea to "crop" a preexisting data file of, for example, 100,000
total
>> events, three times to get an identical sample size for all three gated subsets (R1,
R2,
>> and R3).
>> Scientifically, this shouldn't be a problem, since flow cytometry data is collected
>> randomly within the same sample tube. Not only could we run one acquisition to get
>> different monocyte subset populations, but also to statistically compare constant
numbers
>> of monocytes, PMNs, lymphocytes, lymphocyte subsets, etc. However, I can see why some
>> scientists might be uneasy with the idea of manipulating raw list-mode data.
>> However, Since the data is collected randomly from the same sample, doing this should
>> give exactly the same readings as if we just collected less events, since we would
only
>> be cropping (from stack-collected data) the most recent events collected.
>> Currently, we are acquiring 3 different data files for each tube, and adjusting the
>> acquisition and storage settings for each acquisition. Is there a way to perform a
>> gate-specific data cropping function with any current flow cytometry data analysis
>> software?
>> Kind Regards,
>> Stevan Lauriault
>> ________________________________________________________________
>> Sent via the WebMail system at lauriault.com
>--
>Byron Ellis (byron.el...@gmail.com)
>"Oook" -- The Librarian
________________________________________________________________
Sent via the WebMail system at lauriault.com
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Re: gate-specific data cropping
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From: Byron Ellis <bcel...@stanford.edu>
Date: Tue Feb 06 2007 - 15:17:35 EST
Speaking as a statistician, I would not count running the same tube 3
times or simply cutting the FCS file (the two are equivalent) as three
replicates so I wouldn't do either to achieve what you want (though I
can imagine situations where you would resample to calculate
statistics). To get three replicates you would have to prepare three
separate samples---you're interested in the variability of the mean
due to experimental error as well as the biological variability of the
cells and a single sample preparation only captures the latter.
On 2/5/07, Stevan Lauriault <ste...@lauriault.com> wrote:
> Dear All,
> Question:
> We are isolating leukocyte subsets to measure and compare relative levels of expression
> of certain antigens. For example, there are three subsets within a bivariate dot plot;
> gated on R1, R2 and R3 respectively, and we would like to statistically analyze the
> relative mean fluorescence intensities of a biomarker, among the subsets.
> To get statistically comparable sample sizes among these subsets, we are running the
same
> tube three times and changing the storage criteria to 500 events for each subset
> (example, the first run is 500 events of R1, the second 500 of R2, and the third is 500
> of R3). Instead of repeating the same tube three times, and wasting valuable sample,
it
> seems like a good idea to "crop" a preexisting data file of, for example, 100,000 total
> events, three times to get an identical sample size for all three gated subsets (R1,
R2,
> and R3).
> Scientifically, this shouldn't be a problem, since flow cytometry data is collected
> randomly within the same sample tube. Not only could we run one acquisition to get
> different monocyte subset populations, but also to statistically compare constant
numbers
> of monocytes, PMNs, lymphocytes, lymphocyte subsets, etc. However, I can see why some
> scientists might be uneasy with the idea of manipulating raw list-mode data.
> However, Since the data is collected randomly from the same sample, doing this should
> give exactly the same readings as if we just collected less events, since we would only
> be cropping (from stack-collected data) the most recent events collected.
> Currently, we are acquiring 3 different data files for each tube, and adjusting the
> acquisition and storage settings for each acquisition. Is there a way to perform a
> gate-specific data cropping function with any current flow cytometry data analysis
> software?
> Kind Regards,
> Stevan Lauriault
> ________________________________________________________________
> Sent via the WebMail system at lauriault.com
--
Byron Ellis (byron.el...@gmail.com)
"Oook" -- The Librarian
Received on Wed Feb 7 18:58:00 2007
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Re: gate-specific data cropping
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From: Eric Van Buren <eric.vanbu...@wayne.edu>
Date: Wed Feb 07 2007 - 10:57:01 EST
Stevan,
It's not exactly what you're looking for, but the easiest "off the
shelf" solution may
be to acquire time as a parameter. Or, if your software allows, use
the simulated time
parameter. Gate on time empirically to produce the the desired number
of events in
each region.
As you say, the sampling is random, so it shouldn't matter which "time
slice" you choose.
However, to keep a uniform protocol you may want to always start your
time gate with time
equals zero, i.e. starting at the beginning of the list mode file.
This should minimize
any time-related artifacts, such as sample settling, sample/sheath dye
equilibrium,
exposure to room light, temperature, etc.
--Eric
>Dear All,
>Question:
>We are isolating leukocyte subsets to measure and compare relative levels of expression
>of certain antigens. For example, there are three subsets within a bivariate dot plot;
>gated on R1, R2 and R3 respectively, and we would like to statistically analyze the
>relative mean fluorescence intensities of a biomarker, among the subsets.
>To get statistically comparable sample sizes among these subsets, we are running the
same
>tube three times and changing the storage criteria to 500 events for each subset
>(example, the first run is 500 events of R1, the second 500 of R2, and the third is 500
>of R3). Instead of repeating the same tube three times, and wasting valuable sample, it
>seems like a good idea to "crop" a preexisting data file of, for example, 100,000 total
>events, three times to get an identical sample size for all three gated subsets (R1, R2,
>and R3).
>Scientifically, this shouldn't be a problem, since flow cytometry data is collected
>randomly within the same sample tube. Not only could we run one acquisition to get
>different monocyte subset populations, but also to statistically compare constant
numbers
>of monocytes, PMNs, lymphocytes, lymphocyte subsets, etc. However, I can see why some
>scientists might be uneasy with the idea of manipulating raw list-mode data.
>However, Since the data is collected randomly from the same sample, doing this should
>give exactly the same readings as if we just collected less events, since we would only
>be cropping (from stack-collected data) the most recent events collected.
>Currently, we are acquiring 3 different data files for each tube, and adjusting the
>acquisition and storage settings for each acquisition. Is there a way to perform a
>gate-specific data cropping function with any current flow cytometry data analysis
>software?
>Kind Regards,
>Stevan Lauriault
>________________________________________________________________
>Sent via the WebMail system at lauriault.com
Eric Van Buren <eric.vanbu...@wayne.edu>
Manager, Flow Cytometry Core Facility
Karmanos Cancer Institute
Detroit, Michigan, USA
Received on Wed Feb 7 18:38:01 2007
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gate-specific data cropping
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From: Stevan Lauriault <ste...@lauriault.com>
Date: Mon Feb 05 2007 - 13:56:18 EST
Dear All,
Question:
We are isolating leukocyte subsets to measure and compare relative
levels of expression
of certain antigens. For example, there are three subsets within a
bivariate dot plot;
gated on R1, R2 and R3 respectively, and we would like to
statistically analyze the
relative mean fluorescence intensities of a biomarker, among the
subsets.
To get statistically comparable sample sizes among these subsets, we
are running the same
tube three times and changing the storage criteria to 500 events for
each subset
(example, the first run is 500 events of R1, the second 500 of R2, and
the third is 500
of R3). Instead of repeating the same tube three times, and wasting
valuable sample, it
seems like a good idea to "crop" a preexisting data file of, for
example, 100,000 total
events, three times to get an identical sample size for all three
gated subsets (R1, R2,
and R3).
Scientifically, this shouldn't be a problem, since flow cytometry data
is collected
randomly within the same sample tube. Not only could we run one
acquisition to get
different monocyte subset populations, but also to statistically
compare constant numbers
of monocytes, PMNs, lymphocytes, lymphocyte subsets, etc. However, I
can see why some
scientists might be uneasy with the idea of manipulating raw list-mode
data.
However, Since the data is collected randomly from the same sample,
doing this should
give exactly the same readings as if we just collected less events,
since we would only
be cropping (from stack-collected data) the most recent events
collected.
Currently, we are acquiring 3 different data files for each tube, and
adjusting the
acquisition and storage settings for each acquisition. Is there a way
to perform a
gate-specific data cropping function with any current flow cytometry
data analysis
software?
Kind Regards,
Stevan Lauriault
________________________________________________________________
Sent via the WebMail system at lauriault.com
Received on Tue Feb 6 13:18:00 2007
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RE: DNA analysis software
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From: Novo, David <david.n...@denovosoftware.com>
Date: Fri Feb 16 2007 - 19:05:22 EST
Hello Ibtissam,
Multicycle is a very commonly used DNA analysis program. It can
automatically detect the number of aneuploid populations that you have
(if any) and runs them through several different models with different
fitting parameters to help you determine which is the best one for
your
data. It also has a wide range of debris and aggregate compensation to
allow it to be used with a wide variety of sample preparation methods.
Multicycle has just been incorporated as a plug in module to FCS
Express, so that you get the benefits of the high end DNA analysis as
well as the ease of use and gating/presentation abilities of FCS
Express. It really makes DNA analysis a snap.
There is some information available at
http://www.denovosoftware.com/site/Multicycleplugin.shtml
-Dave
-----------------------------------
David Novo
President
De Novo Software
david.n...@denovosoftware.com
________________________________
From: Ibtissam Abdul-Jabbar [mailto:iajab...@cicr.uq.edu.au]
Sent: Wednesday, February 14, 2007 8:41 PM
To: cyto-inbox
Subject: DNA analysis software
Dear All, before buying software to analyse DNA on PC, I would like to
get your opinion. I already have ModFit for Macintosh.
What are you using and what do you recommend for research purposes.
Is MultiCycle Av the one of choice?
I appreciate your comments.
Ibtissam A Jabbar (PhD)
Manager of the FACS facilities
Diamantina Institute for Cancer, Immunology and Metabolic Medicine
(DI)
The University of Queensland
Level 4 R Wing
Princess Alexandra Hospital
Ipswich Rd Buranda QLD 4102
Australia
Ph: 07 3240 5945
Fax: 07 3240 5946
Mob: 0401154744
Received on Mon Feb 19 13:38:00 2007
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DNA analysis software
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From: Ibtissam Abdul-Jabbar <iajab...@cicr.uq.edu.au>
Date: Wed Feb 14 2007 - 23:41:15 EST
Dear All, before buying software to analyse DNA on PC, I would like to
get your opinion. I already have ModFit for Macintosh.
What are you using and what do you recommend for research purposes.
Is MultiCycle Av the one of choice?
I appreciate your comments.
Ibtissam A Jabbar (PhD)
Manager of the FACS facilities
Diamantina Institute for Cancer, Immunology and Metabolic Medicine
(DI)
The University of Queensland
Level 4 R Wing
Princess Alexandra Hospital
Ipswich Rd Buranda QLD 4102
Australia
Ph: 07 3240 5945
Fax: 07 3240 5946
Mob: 0401154744
Received on Thu Feb 15 12:38:00 2007
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FACSCalibur - developing software for Macintosh
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From: Simon Crase <Simon.Cr...@invetech.com.au>
Date: Tue Feb 13 2007 - 16:32:34 EST
I've developed software to analyze data from a FACSCalibur, and our
client has asked whether we can port it to run on the FACSCalibur
itself. I understand the FACSCalibur includes a Macintosh. I'm
interested in knowing whether anyone has done this before, especially
with Java, and what pitfalls they encountered.
Simon A. Crase
Invetech Pty Ltd
Private Bag 44
495 Blackburn Road
Mount Waverley Vic 3149
Phone: 61 3 9211 7933
Mobile: 0424 782 725
Fax: 61 3 9211 7702 (facsimile)
e-mail: simon.cr...@invetech.com.au
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Flow analysis software
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From: Xiangle Sun <sunxian...@yahoo.com>
Date: Wed Sep 12 2007 - 17:12:44 EDT
Hi, Flowers,
We just got BD LSRII flow cytometer with FACSDiva
software. I know Flowjo is a popular software and some
people use FlowJo instead of FACSDiva to do data
analysis even it comes with instrument.
My questions are:
1. What are the advantages of FlowJo and FACSDiva.
Then is it worth of purchasing FlowJo to do analysis?
2. How about the feature of FlowJo and FACSDiva on DNA
cycle analysis?
3. Are there any other better analysis softwares?
either for multicolor phenotyping, DNA cycle or both?
Any comments that based on your experience will be
greatly appreciated!
Xiangle Sun
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Received on Thu Sep 13 11:18:00 2007
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RE: CFSE proliferation software
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From: user facs_copy <facs_c...@wehi.EDU.AU>
Date: Wed Sep 19 2007 - 02:03:28 EDT
Michael,
Depends what you mean by "analyze". If you mean just to extract cell
numbers at each division state, we use our own Weasel program for that
(see http://www.wehi.edu.au/cytometry/WEASELv2.html , scroll to the
bottom
of the page). We also have a proliferation modelling program,
CytonCalculator, that can take that proliferation data and fit a model
calculation to it (see
http://www.wehi.edu.au/WEHI_Groups/indexworkgroups.php?id=115 for the
entry point that describes the process). CytonCalculator may be
downloaded free. You'll find the download link on that page.
Frank Battye.
> From: Kalos, Michael
> Sent: Thursday, September 13, 2007 5:39 PM
> No doubt this has been brought up before: I am looking for software
> recommendations to analyze data for measuring proliferation using CFSE.
> Our data is acquired on an FC500 and our computers are PC-based.
| | < The Cytometry Laboratory
\__/ <<<<< The Walter & Eliza Hall Institute
------!!<<<<<<<< Post Office, Royal Melbourne Hospital
/!!\ <<<<< Victoria 3050, Australia
o !! \ < ph: 61_3_9345 2541, fax: 61_3_9347 0852
Received on Wed Sep 19 11:38:00 2007
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RE: CFSE proliferation software
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From: <moo...@mail.MED.UPENN.EDU>
Date: Mon Sep 17 2007 - 19:20:03 EDT
I also agree. We do a lot of proliferation studies and have found
that
Proliferation Wizard on Modfit is very good.
Jonni
Quoting James F George <jgeo...@uab.edu>:
> I have found the Modfit software from Verity to be quite useful for
> this, and it integrates with Winlist rather nicely, if you have it. Don
> at Verity has been very helpful over the years in helping us implement
> the software for routine analyses.
> I highly recommend this company.
> I have no financial interest in Verity. I am just a long-time user.
> James F. George, PhD | Professor
> Division of Cardiothoracic Surgery | University of Alabama at
> Birmingham
> 701 South 19th St. | Birmingham, AL 35294
> Phone: (205) 934-4261 | Fax: (205) 975-0085
> Email: jgeo...@uab.edu <mailto:jgeo...@uab.edu>
> UAB HEALTH SYSTEM
> Medicine that touches the world
buybroker@yahoo.com - 01 Feb 2008 04:18 GMT
On Jan 31, 6:39 pm, buybro...@yahoo.com wrote:
> > RE: DNA analysis software
>
[quoted text clipped - 258 lines]
>
> - Show quoted text -
DNA SOFTWARE MESSAGES WERE TO BE DELETED
THE SMALL COMPANY MAY JUST BE KANECKI ASSOCIATES INC. THAT DISCOVERED
THE PURDUE CYTOMETRY MAIL LIST AFTER BEING CALLED SCAMMERS BY J PAUL
ROBINSON FOR INTRODUCING NEW SOFTWARE SENT TO ROBERT MURPHY! DID
ROBERT MURPHY GET THE EMAIL OR DID J PAUL ROBINSON INTERCEPT HIS
EMAIL?
> PURDUE CYTOMETRY AND J PAUL ROBINSON HAS CONTROLED THE MARKET OF
> SOFTWARE!
> HOW PURDUE TAKES ADVANTAGE OF THE CYTOMETRY MAIL LIST AND YES THE TALK
> ABOUT HOW TO FILTER MAIL...KEEP THE SMALL COMPANIES OUT!
> READ ABOUT HOW PURDUE KEEPS ALL SOFTWARE SALES AND VENDORS WITHIN YES
> THEY TALK ABOUT FILTERING THE MAIL LIST AND VENDORS!
The Purdue Cytometry Mail List Evidence is being DELETED..
DO NOT LET THEM DESTROY THE EVIDENCE
From: J. Paul Robinson <j...@flowcyt.cyto.purdue.edu>
Date: Fri Dec 28 2007 - 13:43:46 EST
Beware, the end is nigh!
No, not an apocalyptic prediction - but 2007 is definitely coming to
an
end. Not before time I would say - it s been a busy year. But I have
some strong words to end the year and I am going to say them!! Of
course
you don t have to read them!
Cytometry is now 40 years old and it s been sort of decaying a bit.
Wake up people - times are changing - look at all
these new small companies trying to stick their noses in "our" field!
Wake up people - times are changing - look at all
these new small companies trying to stick their noses in "our" field!
Wake up people - times are changing - look at all
these new small companies trying to stick their noses in "our" field!
Wake up people - times are changing - look at all
these new small companies trying to stick their noses in "our" field!
Wake up people - times are changing - look at all
these new small companies trying to stick their noses in "our" field!
Wake up people - times are changing - look at all
these new small companies trying to stick their noses in "our" field!
***************************************************************************
**********************************************
THE SMALL COMPANY MAY JUST BE KANECKI ASSOCIATES INC. THAT DISCOVERED
THE PURDUE CYTOMETRY MAIL LIST AFTER BEING CALLED SCAMMERS BY J PAUL
ROBINSON FOR INTRODUCING NEW SOFTWARE SENT TO ROBERT MURPHY! DID
ROBERT MURPHY GET THE EMAIL OR DID J PAUL ROBINSON INTERCEPT HIS
EMAIL?
WHY ARE THE LINKS DISCOVERED BEING REMOVED AND ARTICLES TOO?
GOOGLE EXPOSES THE TRUTH BY POSTING THE UNFILTERED RECORDS...READ
ARTICLES HOW PURDUE DISCUSSES HOW TO **FILTER** THE MAIL LIST AND
KEEP
VENDORS OUT!
***************************************************************************
**************************************************
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CD-
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PC, I suggest you contact Verity Software (207-729-6767) . I
quickly ...
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Purdue Cytometry Mailing List: RE: utility software to convert fcs1.0
to fcs2.0
... Purdue Cytometry Mailing List: RE: utility software to convert
fcs1.0 to fcs2.0 ... Since you are using the PC, I suggest you
contact
Verity Software (207-729-6767) . I quickly tried this function this
AM ...
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Purdue Cytometry Mailing List: FW: FCS file transfer between BD Diva
(PC) and CellQuest ( ...
... Purdue Cytometry Mailing List: FW: FCS file transfer between ...
morphosys.com> Date: Thu Nov 08 2007 - 07:14:16 EST ...
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Purdue Cytometry Mailing List: RE: 2008 NW Regional Cytometry Meeting
announcement
... Purdue Cytometry Mailing List: RE: 2008 NW Regional Cytometry
Meeting announcement ... Bioscience, Miltenyi Biotec, MDA Analytical
Technologies, Partec, Tree Star, Union Biometrica, and Verity
Software
House. ...
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Purdue Cytometry Mailing List: New England Cytometry Meeting
Registration Reminder
... Purdue Cytometry Mailing List: New England Cytometry Meeting
Registration Reminder ... speakers this year: ... C. Bruce Bagwell,
MD, Ph.D. - Verity Software House "Probability State Models: A new
paradigm for cytometry analysis ...
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Purdue Cytometry Mailing List: New England Cytometry Annual Meeting
Registration and Hotel ...
... Purdue Cytometry Mailing List: New England Cytometry Annual
Meeting Registration and Hotel Information ... year: ... C. Bruce
Bagwell, MD, Ph.D. - Verity Software House "Probability State Models:
A new paradigm for cytometry ...
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Purdue Cytometry Mailing List: SUMMARY of Responses: Biexponential
Plots and CSFE
... Purdue Cytometry Mailing List: SUMMARY of Responses:
Biexponential
Plots and CSFE ... FCS3.0 digital data was presented by Mark Munson
of
Verity Software House (makers of Modfit). Thanks Mark, it worked
great ...
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Purdue Cytometry Mailing List: Invitation for Vendor Sponsorship for
the New England ...
... to announce the New England Cytometry Users Group Fall meeting;
Current Concepts in Flow and Image Cytometry which will be held
October ... Bruce Bagwell, MD, Ph.D. - Verity Software House http://www.vsh.com
...
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Purdue Cytometry Mailing List: RE: CFSE graphs (UNCLASSIFIED)
... Verity's MODFIT software has a very nice tool for
proliferation ... Stelekati [mailto:e...@fz-borstel.de] >>>Sent:
Monday, March 26, 2007 6:58 AM >>>To: Cytometry Mailing List
>>>Subject: CFSE graphs >>> >>>Dear all, >>>I want to ...
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Purdue Cytometry Mailing List: Applications Specialist - iCyt -
... Purdue Cytometry Mailing List: Applications Specialist - iCyt ...
Sponsored by: The National Flow Cytometry Resource (NFCR) and Verity
Software House ...
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Purdue Cytometry Mailing List: By Date
... Purdue Cytometry Mailing List: By Date ... RE: DIVA SOFTWARE ON
INTEL CORE 2 DUO PROCESSOR Guy Hermans ...
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Purdue Cytometry Mailing List: By Author
... Re: Free Flow Cytometry Analysis software? (Fri Apr 14 2006 -
02:56:18 EDT) ... CORRECTION- Chesapeake Cytometry Consortium (Thu
Sep
07 2006 - 12:20:05 EDT) ...
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Purdue Cytometry Mailing List: RE: Partec CyFlow ML? (was Re:
Analyzers)
... Purdue Cytometry Mailing List: RE: Partec CyFlow ML? (was Re:
Analyzers) ... Received on Fri Nov 30 18:07:07 2007 ...
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Purdue Cytometry Mailing List: RE: Cytometry software for linux
... Purdue Cytometry Mailing List: RE: Cytometry software for
linux ... ugr.es] > Sent: Monday, September 10, 2007 12:28 PM > To:
Cytometry Mailing List > Subject: Cytometry software ...
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Purdue Cytometry Mailing List: Re: Summary and replies on PCH101
... Purdue Cytometry Mailing List: Re: Summary and replies on
PCH101 ... From: clare Rogers <rog...@med.umich.edu> Date: Fri Sep 07
2007 - 17:04:21 EDT ...
http://flowcyt.cyto.purdue.edu/hmarchiv/Current/1350.htm - 13.3KB
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Purdue Cytometry Mailing List: For Sale BD FACSVantage with DiVa
option
... Purdue Cytometry Mailing List: For Sale BD FACSVantage with DiVa
option ... ml tubes -- PC and Mac computers with all original BD
software (DiVa [PC] and CELLQuest [Mac.]) NOTE: I will only
guarantee ...
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Purdue Cytometry Mailing List: BD bead array software and FC500s
... Purdue Cytometry Mailing List: BD bead array software and
FC500s ... From: Stephen Taylor - Porton Down
<Stephen.Tay...@hpa.org.uk> Date: Thu Aug 16 2007 - 07:01:09 EDT ...
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Purdue Cytometry Mailing List: RE: Upgrading Computers and BD
Software
... Purdue Cytometry Mailing List: RE: Upgrading Computers and BD
Software ... utoronto.ca> > To: Cytometry Mailing List
<cytome...@flowcyt.cyto.purdue.edu> > Date: 8/13/2007 ...
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Purdue Cytometry Mailing List: FACSort for sale.
... Purdue Cytometry Mailing List: FACSort for sale. ... Blue laser
and sorting option (bought in Oct. 1997) with Cellquest software
installed in Power Macintosh computer. The laser current is around
5.70Amps ...
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Purdue Cytometry Mailing List: By Date
... Purdue Cytometry Mailing List: By Date ... Summarize "Free
software" Dorte Christiansen (Fri Dec 12 2003 - 07:45:44 EST) ...
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Purdue Cytometry Mailing List: By Author
... Purdue Cytometry Mailing List: By Author ... Flow facility, again
(Fri Dec 04 1998 - 03:50:07 EST) ... Flow facility (Mon Nov 23 1998 -
07:07:29 EST) ...
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Purdue Cytometry Mailing List: By Date
... Purdue Cytometry Mailing List: By Date ... PML protein Jan Nelson
(Wed Dec 16 1998 - 16:56:58 EST) ... Permeabilization and Anti-
Coagulants Vincent Falco (Wed Dec 16 1998 - 09:07:16 EST) ...
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Purdue Cytometry Mailing List: By Subject
... Purdue Cytometry Mailing List: By Subject ... owner-cytometry
(Wed
Jun 07 2006 - 10:19:50 EDT) ...
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Purdue Cytometry Mailing List: By Subject
... Purdue Cytometry Mailing List: By Subject ... Rosie Clarke (Fri
Feb 07 2003 - 07:14:11 EST) ...
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Purdue Cytometry Mailing List: By Author
... Re: Réf. : Free software? (Fri Dec 19 2003 - 22:39:46 EST) ... UV
vs Krypton UV (Thu Feb 20 2003 - 19:09:39 EST) ... RE: malignant
plasma cell detection by flow cytometry (Fri Feb 07 2003 - 19:48:43
EST) ...
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Purdue Cytometry Mailing List: By Date
... Purdue Cytometry Mailing List: By Date ... Thu Dec 16 2004 -
07:07:48 EST ...
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Purdue Cytometry Mailing List: By Author
... Purdue Cytometry Mailing List: By Author ... Re: OS9+Cellquest
(Tue Mar 07 2000 - 08:07:34 EST) ...
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Purdue Cytometry Mailing List: By Date
... Purdue Cytometry Mailing List: By Date ... Thu Dec 21 2000 -
07:29:44 EST ...
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Purdue Cytometry Mailing List: By Subject
... Purdue Cytometry Mailing List: By Subject ... JSC-SD) (Wed Sep 06
2000 - 08:37:10 EST) ... Walker, Don (SEA) (Thu Aug 31 2000 -
14:09:16
EST) ... Palkowetz, Kimberly H. (Tue Aug 29 2000 - 07:49:22 EST) ...
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Purdue Cytometry Mailing List: By Date
... Purdue Cytometry Mailing List: By Date ... Sales position in
Germany Brian Hall (Thu Dec 18 1997 - 12:23:18 EST) ...
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