Hello,
By virtue of experiment design we have two populations to analyze on
each of a suite of Genepix microarrays. You can see an example in an
MA plot here (generated using the excellent limma package) :
http://dl.dropbox.com/u/8433654/BE%20T46h%20slide%2052.png
We have been following the steps in the limma user guide, and Ben
Bolstad's helpful notes http://tinyurl.com/7346mh9 All of the
examples we see appear to have just one population to contend with,
which gives us an inkling that we are being naive about our analysis.
We suspect that we'll have to separate the two populations before
normalization and analysis. Are there any guides available for
managing two populations like this?
Thanks!
Ben
Ben Tupper
Bigelow Laboratory for Ocean Sciences
180 McKown Point Rd. P.O. Box 475
West Boothbay Harbor, Maine 04575-0475
http://www.bigelow.org
Dear Ben,
Are you saying that you have deliberately designed two different
populations of probes onto your arrays?
Your MA-plot suggests that there is substantial body of spots on the
array
for which the green channel has failed, hence the 45-degree line at
the
top of the plot. These dots likely represent spots with a normal red
channel value but close to zero for green. Normally this would have a
technical rather than biological cause. An imageplot may help you
identify where the offending spots are on your array.
On the other hand, if you have deliberately spotted your arrays with
two
quite different populations of probes, then they probably need to be
analysed as separate arrays.
Best wishes
Gordon
> Date: Thu, 12 Jan 2012 14:28:36 -0500
> From: Ben Tupper <btupper at="" bigelow.org="">
> To: bioconductor at r-project.org
> Subject: [BioC] Two populations on microarray
>
> Hello,
>
> By virtue of experiment design we have two populations to analyze on
> each of a suite of Genepix microarrays. You can see an example in
an MA
> plot here (generated using the excellent limma package) :
>
> http://dl.dropbox.com/u/8433654/BE%20T46h%20slide%2052.png
>
> We have been following the steps in the limma user guide, and Ben
> Bolstad's helpful notes http://tinyurl.com/7346mh9 All of the
examples
> we see appear to have just one population to contend with, which
gives
> us an inkling that we are being naive about our analysis. We
suspect
> that we'll have to separate the two populations before normalization
and
> analysis. Are there any guides available for managing two
populations
> like this?
>
> Thanks!
> Ben
>
>
> Ben Tupper
> Bigelow Laboratory for Ocean Sciences
> 180 McKown Point Rd. P.O. Box 475
> West Boothbay Harbor, Maine 04575-0475
> http://www.bigelow.org
______________________________________________________________________
The information in this email is confidential and
intend...{{dropped:4}}
Dear Ben,
A typical MA plot has most of the points scattered around the line
M=0. Even if you have 2 populations of probes, the nondifferentially
expressing genes should be in that central ellipse. (The lower
cluster does look somewhat like the typical MA plot for raw data.) I
suggest that you do separate MA plots for each population of probes,
to see if one set of probes failed. Or, as Gordon suggests, a
population for which labelling failed.
--Naomi
At 05:48 PM 1/14/2012, Gordon K Smyth wrote:
>Dear Ben,
>
>Are you saying that you have deliberately designed two different
>populations of probes onto your arrays?
>
>Your MA-plot suggests that there is substantial body of spots on the
>array for which the green channel has failed, hence the 45-degree
>line at the top of the plot. These dots likely represent spots with
>a normal red channel value but close to zero for green. Normally
>this would have a technical rather than biological cause. An
>imageplot may help you identify where the offending spots are on your
array.
>
>On the other hand, if you have deliberately spotted your arrays with
>two quite different populations of probes, then they probably need
>to be analysed as separate arrays.
>
>Best wishes
>Gordon
>
>>Date: Thu, 12 Jan 2012 14:28:36 -0500
>>From: Ben Tupper <btupper at="" bigelow.org="">
>>To: bioconductor at r-project.org
>>Subject: [BioC] Two populations on microarray
>>
>>Hello,
>>
>>By virtue of experiment design we have two populations to analyze
>>on each of a suite of Genepix microarrays. You can see an example
>>in an MA plot here (generated using the excellent limma package) :
>>
>> http://dl.dropbox.com/u/8433654/BE%20T46h%20slide%2052.png
>>
>>We have been following the steps in the limma user guide, and Ben
>>Bolstad's helpful notes http://tinyurl.com/7346mh9 All of the
>>examples we see appear to have just one population to contend with,
>>which gives us an inkling that we are being naive about our
>>analysis. We suspect that we'll have to separate the two
>>populations before normalization and analysis. Are there any
>>guides available for managing two populations like this?
>>
>>Thanks!
>>Ben
>>
>>
>>Ben Tupper
>>Bigelow Laboratory for Ocean Sciences
>>180 McKown Point Rd. P.O. Box 475
>>West Boothbay Harbor, Maine 04575-0475
>>http://www.bigelow.org
>
>_____________________________________________________________________
_
>The information in this email is confidential and
inten...{{dropped:11}}
Dear Naomi, Gordon and Ben,
Thank you for your replies to Ben TupperÂ’s (and my) question.
We are using spotted oligonucleotide microarrays containing probes for
both
host and virus genes. In our experiment we had cultures grown under
high
and low phosphate conditions, inoculated with 2 different viruses
(separately) or kept virus-free, in triplicate. RNA purified from
those
cultures at different time points was fluorescently labeled (with Cy-
dyes)
and hybridized onto the microarray slides. You can see a flow chart of
our
experimental design here:
http://dl.dropbox.com/u/8433654/design-concept.pdf
One slide contains 2 samples which had different experimental
treatments.
Each sample was split into 3, labeled (dye swap) and hybridized onto 3
different microarray slides in combination with another sample to
allow
technical replication.
I quantified labeling efficiency prior to hybridizing the samples onto
the
microarray slide, for both dyes I got between 30 and 60 dye molecules
per
1000 nt (what is the range indicated by the manufacturer for good
labeling). Also we produced FB plots for the green and the red
channels,
both had similar z-range and saturation range, which we interpreted as
a
proof of good labeling (?). See example:
http://dl.dropbox.com/u/8433654/R-G-imageplot.png
Both MA clusters that we observe contain a mixture of both host and
virus
probes, ruling out that one complete set of probes failed. Naomi
mentioned
that the nondifferentially expressing genes should cluster around M=0,
so
does that mean that the top cluster corresponds to differentially
expressed
genes?
We used GenePix Pro to scan and analyze the microarrays. Could we use
the
normalization function in the software (normalize the data in each
image so
that the mean of the median of ratios of all features is equal to 1)
as an
alternative to MA? Or would that simply hide the problem? And then do
normalization between arrays using the quantile method?
Thanks,
Joaquin
> > From: Naomi Altman <naomi@stat.psu.edu>
> > Date: January 18, 2012 9:56:45 AM EST
> > To: Gordon K Smyth <smyth@wehi.edu.au>, Ben Tupper
<btupper@bigelow.org>
> > Cc: Bioconductor mailing list <bioconductor@r-project.org>
> > Subject: Re: [BioC] Two populations on microarray
> >
> > Dear Ben,
> > A typical MA plot has most of the points scattered around the line
M=0.
> Even if you have 2 populations of probes, the nondifferentially
expressing
> genes should be in that central ellipse. (The lower cluster does
look
> somewhat like the typical MA plot for raw data.) I suggest that you
do
> separate MA plots for each population of probes, to see if one set
of
> probes failed. Or, as Gordon suggests, a population for which
labelling
> failed.
> >
> > --Naomi
> >
> >
> > At 05:48 PM 1/14/2012, Gordon K Smyth wrote:
> >> Dear Ben,
> >>
> >> Are you saying that you have deliberately designed two different
> populations of probes onto your arrays?
> >>
> >> Your MA-plot suggests that there is substantial body of spots on
the
> array for which the green channel has failed, hence the 45-degree
line at
> the top of the plot. These dots likely represent spots with a
normal red
> channel value but close to zero for green. Normally this would have
a
> technical rather than biological cause. An imageplot may help you
identify
> where the offending spots are on your array.
> >>
> >> On the other hand, if you have deliberately spotted your arrays
with
> two quite different populations of probes, then they probably need
to be
> analysed as separate arrays.
> >>
> >> Best wishes
> >> Gordon
> >>
> >>> Date: Thu, 12 Jan 2012 14:28:36 -0500
> >>> From: Ben Tupper <btupper@bigelow.org>
> >>> To: bioconductor@r-project.org
> >>> Subject: [BioC] Two populations on microarray
> >>>
> >>> Hello,
> >>>
> >>> By virtue of experiment design we have two populations to
analyze on
> each of a suite of Genepix microarrays. You can see an example in
an MA
> plot here (generated using the excellent limma package) :
> >>>
> >>>
http://dl.dropbox.com/u/8433654/BE%20T46h%20slide%2052.png
> >>>
> >>> We have been following the steps in the limma user guide, and
Ben
> Bolstad's helpful notes http://tinyurl.com/7346mh9 All of the
examples we
> see appear to have just one population to contend with, which gives
us an
> inkling that we are being naive about our analysis. We suspect that
we'll
> have to separate the two populations before normalization and
analysis.
> Are there any guides available for managing two populations like
this?
> >>>
> >>> Thanks!
> >>> Ben
> >>>
> >>>
>
>
[[alternative HTML version deleted]]
Dear Joaquin,
What I had in mind was that you would make a vector z which takes
values
TRUE or FALSE depending on whether each probe on the array belongs to
group 1 or group 2 according to your MA plot. Then
imageplot(z,layout,low="white",high="blue")
There is no way for you normalize out this problem, and certainly not
within the limited capabilities of GenePix software.
Best wishes
Gordon
---------------------------------------------
Professor Gordon K Smyth,
Bioinformatics Division,
Walter and Eliza Hall Institute of Medical Research,
1G Royal Parade, Parkville, Vic 3052, Australia.
smyth at wehi.edu.au
http://www.wehi.edu.auhttp://www.statsci.org/smyth
On Thu, 19 Jan 2012, Joaquin Martinez wrote:
> Dear Naomi, Gordon and Ben,
>
>
>
> Thank you for your replies to Ben Tupper?s (and my) question.
>
>
>
> We are using spotted oligonucleotide microarrays containing probes
for both
> host and virus genes. In our experiment we had cultures grown under
high
> and low phosphate conditions, inoculated with 2 different viruses
> (separately) or kept virus-free, in triplicate. RNA purified from
those
> cultures at different time points was fluorescently labeled (with
Cy-dyes)
> and hybridized onto the microarray slides. You can see a flow chart
of our
> experimental design here:
>
> http://dl.dropbox.com/u/8433654/design-concept.pdf
>
>
>
> One slide contains 2 samples which had different experimental
treatments.
> Each sample was split into 3, labeled (dye swap) and hybridized onto
3
> different microarray slides in combination with another sample to
allow
> technical replication.
>
>
>
> I quantified labeling efficiency prior to hybridizing the samples
onto the
> microarray slide, for both dyes I got between 30 and 60 dye
molecules per
> 1000 nt (what is the range indicated by the manufacturer for good
> labeling). Also we produced FB plots for the green and the red
channels,
> both had similar z-range and saturation range, which we interpreted
as a
> proof of good labeling (?). See example:
>
> http://dl.dropbox.com/u/8433654/R-G-imageplot.png
>
>
>
> Both MA clusters that we observe contain a mixture of both host and
virus
> probes, ruling out that one complete set of probes failed. Naomi
mentioned
> that the nondifferentially expressing genes should cluster around
M=0, so
> does that mean that the top cluster corresponds to differentially
expressed
> genes?
>
>
>
> We used GenePix Pro to scan and analyze the microarrays. Could we
use the
> normalization function in the software (normalize the data in each
image so
> that the mean of the median of ratios of all features is equal to 1)
as an
> alternative to MA? Or would that simply hide the problem? And then
do
> normalization between arrays using the quantile method?
>
>
> Thanks,
>
> Joaquin
>
>
>
>>> From: Naomi Altman <naomi at="" stat.psu.edu="">
>>> Date: January 18, 2012 9:56:45 AM EST
>>> To: Gordon K Smyth <smyth at="" wehi.edu.au="">, Ben Tupper <btupper at="" bigelow.org="">
>>> Cc: Bioconductor mailing list <bioconductor at="" r-project.org="">
>>> Subject: Re: [BioC] Two populations on microarray
>>>
>>> Dear Ben,
>>> A typical MA plot has most of the points scattered around the line
M=0.
>> Even if you have 2 populations of probes, the nondifferentially
expressing
>> genes should be in that central ellipse. (The lower cluster does
look
>> somewhat like the typical MA plot for raw data.) I suggest that
you do
>> separate MA plots for each population of probes, to see if one set
of
>> probes failed. Or, as Gordon suggests, a population for which
labelling
>> failed.
>>>
>>> --Naomi
>>>
>>>
>>> At 05:48 PM 1/14/2012, Gordon K Smyth wrote:
>>>> Dear Ben,
>>>>
>>>> Are you saying that you have deliberately designed two different
>> populations of probes onto your arrays?
>>>>
>>>> Your MA-plot suggests that there is substantial body of spots on
the
>> array for which the green channel has failed, hence the 45-degree
line at
>> the top of the plot. These dots likely represent spots with a
normal red
>> channel value but close to zero for green. Normally this would
have a
>> technical rather than biological cause. An imageplot may help you
identify
>> where the offending spots are on your array.
>>>>
>>>> On the other hand, if you have deliberately spotted your arrays
with
>> two quite different populations of probes, then they probably need
to be
>> analysed as separate arrays.
>>>>
>>>> Best wishes
>>>> Gordon
>>>>
>>>>> Date: Thu, 12 Jan 2012 14:28:36 -0500
>>>>> From: Ben Tupper <btupper at="" bigelow.org="">
>>>>> To: bioconductor at r-project.org
>>>>> Subject: [BioC] Two populations on microarray
>>>>>
>>>>> Hello,
>>>>>
>>>>> By virtue of experiment design we have two populations to
analyze on
>> each of a suite of Genepix microarrays. You can see an example in
an MA
>> plot here (generated using the excellent limma package) :
>>>>>
>>>>>
http://dl.dropbox.com/u/8433654/BE%20T46h%20slide%2052.png
>>>>>
>>>>> We have been following the steps in the limma user guide, and
Ben
>> Bolstad's helpful notes http://tinyurl.com/7346mh9 All of the
examples we
>> see appear to have just one population to contend with, which gives
us an
>> inkling that we are being naive about our analysis. We suspect
that we'll
>> have to separate the two populations before normalization and
analysis.
>> Are there any guides available for managing two populations like
this?
>>>>>
>>>>> Thanks!
>>>>> Ben
>>>>>
>>>>>
>>
>>
>
______________________________________________________________________
The information in this email is confidential and
intend...{{dropped:5}}
I agree with Gordon.
I doubt that the double cloud has anything to do with differential
expression. There is something odd going on technically. The usual
types of normalization are not going to fix the problem.
--Naomi
At 12:03 AM 1/20/2012, Gordon K Smyth wrote:
>Dear Joaquin,
>
>What I had in mind was that you would make a vector z which takes
>values TRUE or FALSE depending on whether each probe on the array
>belongs to group 1 or group 2 according to your MA plot. Then
>
> imageplot(z,layout,low="white",high="blue")
>
>There is no way for you normalize out this problem, and certainly not
>within the limited capabilities of GenePix software.
>
>Best wishes
>Gordon
>
>---------------------------------------------
>Professor Gordon K Smyth,
>Bioinformatics Division,
>Walter and Eliza Hall Institute of Medical Research,
>1G Royal Parade, Parkville, Vic 3052, Australia.
>smyth at wehi.edu.au
>http://www.wehi.edu.au
>http://www.statsci.org/smyth
>
>
>On Thu, 19 Jan 2012, Joaquin Martinez wrote:
>
>>Dear Naomi, Gordon and Ben,
>>
>>
>>
>>Thank you for your replies to Ben Tupper's (and my) question.
>>
>>
>>
>>We are using spotted oligonucleotide microarrays containing probes
for both
>>host and virus genes. In our experiment we had cultures grown under
high
>>and low phosphate conditions, inoculated with 2 different viruses
>>(separately) or kept virus-free, in triplicate. RNA purified from
those
>>cultures at different time points was fluorescently labeled (with
Cy-dyes)
>>and hybridized onto the microarray slides. You can see a flow chart
of our
>>experimental design here:
>>
>>http://dl.dropbox.com/u/8433654/design-concept.pdf
>>
>>
>>
>>One slide contains 2 samples which had different experimental
treatments.
>>Each sample was split into 3, labeled (dye swap) and hybridized onto
3
>>different microarray slides in combination with another sample to
allow
>>technical replication.
>>
>>
>>
>>I quantified labeling efficiency prior to hybridizing the samples
onto the
>>microarray slide, for both dyes I got between 30 and 60 dye
molecules per
>>1000 nt (what is the range indicated by the manufacturer for good
>>labeling). Also we produced FB plots for the green and the red
channels,
>>both had similar z-range and saturation range, which we interpreted
as a
>>proof of good labeling (?). See example:
>>
>>http://dl.dropbox.com/u/8433654/R-G-imageplot.png
>>
>>
>>
>>Both MA clusters that we observe contain a mixture of both host and
virus
>>probes, ruling out that one complete set of probes failed. Naomi
mentioned
>>that the nondifferentially expressing genes should cluster around
M=0, so
>>does that mean that the top cluster corresponds to differentially
expressed
>>genes?
>>
>>
>>
>>We used GenePix Pro to scan and analyze the microarrays. Could we
use the
>>normalization function in the software (normalize the data in each
image so
>>that the mean of the median of ratios of all features is equal to 1)
as an
>>alternative to MA? Or would that simply hide the problem? And then
do
>>normalization between arrays using the quantile method?
>>
>>
>>Thanks,
>>
>>Joaquin
>>
>>
>>
>>>>From: Naomi Altman <naomi at="" stat.psu.edu="">
>>>>Date: January 18, 2012 9:56:45 AM EST
>>>>To: Gordon K Smyth <smyth at="" wehi.edu.au="">, Ben Tupper <btupper at="" bigelow.org="">
>>>>Cc: Bioconductor mailing list <bioconductor at="" r-project.org="">
>>>>Subject: Re: [BioC] Two populations on microarray
>>>>
>>>>Dear Ben,
>>>>A typical MA plot has most of the points scattered around the line
M=0.
>>> Even if you have 2 populations of probes, the nondifferentially
expressing
>>>genes should be in that central ellipse. (The lower cluster does
look
>>>somewhat like the typical MA plot for raw data.) I suggest that
you do
>>>separate MA plots for each population of probes, to see if one set
of
>>>probes failed. Or, as Gordon suggests, a population for which
labelling
>>>failed.
>>>>
>>>>--Naomi
>>>>
>>>>
>>>>At 05:48 PM 1/14/2012, Gordon K Smyth wrote:
>>>>>Dear Ben,
>>>>>
>>>>>Are you saying that you have deliberately designed two different
>>>populations of probes onto your arrays?
>>>>>
>>>>>Your MA-plot suggests that there is substantial body of spots on
the
>>>array for which the green channel has failed, hence the 45-degree
line at
>>>the top of the plot. These dots likely represent spots with a
normal red
>>>channel value but close to zero for green. Normally this would
have a
>>>technical rather than biological cause. An imageplot may help you
identify
>>>where the offending spots are on your array.
>>>>>
>>>>>On the other hand, if you have deliberately spotted your arrays
with
>>>two quite different populations of probes, then they probably need
to be
>>>analysed as separate arrays.
>>>>>
>>>>>Best wishes
>>>>>Gordon
>>>>>
>>>>>>Date: Thu, 12 Jan 2012 14:28:36 -0500
>>>>>>From: Ben Tupper <btupper at="" bigelow.org="">
>>>>>>To: bioconductor at r-project.org
>>>>>>Subject: [BioC] Two populations on microarray
>>>>>>
>>>>>>Hello,
>>>>>>
>>>>>>By virtue of experiment design we have two populations to
analyze on
>>>each of a suite of Genepix microarrays. You can see an example in
an MA
>>>plot here (generated using the excellent limma package) :
>>>>>>
>>>>>>
http://dl.dropbox.com/u/8433654/BE%20T46h%20slide%2052.png
>>>>>>
>>>>>>We have been following the steps in the limma user guide, and
Ben
>>>Bolstad's helpful notes http://tinyurl.com/7346mh9 All of the
examples we
>>>see appear to have just one population to contend with, which gives
us an
>>>inkling that we are being naive about our analysis. We suspect
that we'll
>>>have to separate the two populations before normalization and
analysis.
>>> Are there any guides available for managing two populations like
this?
>>>>>>
>>>>>>Thanks!
>>>>>>Ben
>>>>>>
>>>
>
>_____________________________________________________________________
_
>The information in this email is confidential and
inten...{{dropped:9}}