[BioC] RNA degradation (Chris Paulse)
James MacDonald
jmacdon at med.umich.edu
Mon Aug 4 15:11:35 MEST 2003
Rafael should correct me on this if I am wrong, but I think the critical
thing for a RNA degradation plot is that the slopes for all the chips
should be as similar as possible. Not to say that horizontal isn't
ideal, but I have never seen any plots that *were* horizontal
(correction; the slopes for the affy spike-in data set are pretty close
to horizontal, except for the inevitable drop off at the 3' end).
Note too that these plots show more than simple degradation. There is
also the second strand synthesis that proceeds from 3' to 5'. If this
doesn't go to completion, you will also see a slope to the plots.
Also, the G-C sequence code has been released in the gcrma library, so
you can play around with it to see if it helps with the RNA degradation
plots.
Jim
James W. MacDonald
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623
>>> "Chris Paulse" <chrispaulse at hotmail.com> 08/04/03 01:55PM >>>
Thanks. We see this behaviour in almost every array (RGU34a layout).
The
test slides do not show any noticable signs of degradation (test3
layout).
I notice in a set of slides for the recent Milan short course that RNA
degradation is discussed as an effect that could be detected and
corrected
for once the G-C sequence effect is corrected for. Can anyone
(Rafael?)
provide some indication of progress with this? Does the additive model
in
RMA do anything to reduce the variance caused by RNA degradation?
Thanks,
Chris
>From: "Vawter, Marquis" <mvawter at uci.edu>
>To: "'bioconductor at stat.math.ethz.ch'"
<bioconductor at stat.math.ethz.ch>
>Subject: [BioC] RNA degradation (Chris Paulse)
>Date: Mon, 4 Aug 2003 10:03:15 -0700
>
>Hi Chris, we have seen the same phenomenon with affyRNA degradation
plots.
>There is definitely a smooth trend, until the last point. It is very
>reproducible, in fact this position should show the highest intensity
>overall, but shows about 50% of what would be expected.
>Best, Mark
>
>
>-----Original Message-----
>From: bioconductor-request at stat.math.ethz.ch
>[mailto:bioconductor-request at stat.math.ethz.ch]
>Sent: Sunday, August 03, 2003 4:36 PM
>To: bioconductor at stat.math.ethz.ch
>Subject: Bioconductor Digest, Vol 6, Issue 1
>
>
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>Today's Topics:
>
> 1. marrayNorm - Getting Data Out (michael watson (IAH-C))
> 2. RNA degradation (Chris Paulse)
> 3. Repost: marrayNorm 1.1.3 gets stuck (Rob Dunne)
> 4. Re: Spelling mistakes and some questions re limma (Gordon
Smyth)
> 5. Re: RMA t-test (Rafael A. Irizarry)
> 6. Re: Repost: marrayNorm 1.1.3 gets stuck (Gordon Smyth)
>
>
>----------------------------------------------------------------------
>
>Message: 1
>Date: Thu, 31 Jul 2003 11:16:02 +0100
>From: "michael watson (IAH-C)" <michael.watson at bbsrc.ac.uk>
>Subject: [BioC] marrayNorm - Getting Data Out
>To: Bioconductor mailing list <bioconductor at stat.math.ethz.ch>
>Message-ID:
>
><20B7EB075F2D4542AFFAF813E98ACD9301C0099D at cl-exsrv1.irad.bbsrc.ac.uk>
>Content-Type: text/plain; charset="iso-8859-1"
>
>Hi
>
>This sounds kind of stupid, but if I have my data in an marrayNorm
object,
>can anyone give any pointers on how to get it out into, say, a
>tab-delimited
>text file?
>
>Are there any special functions or is it simply write.table() ..??
>
>Thanks
>Mick
>
>
>------------------------------
>
>Message: 2
>Date: Thu, 31 Jul 2003 15:18:25 -0700
>From: "Chris Paulse" <chrispaulse at hotmail.com>
>Subject: [BioC] RNA degradation
>To: bioconductor at stat.math.ethz.ch
>Message-ID: <BAY8-F114Y0OM3G80cE00005707 at hotmail.com>
>Content-Type: text/plain; format=flowed
>
>Hi,
>How much faith should I place in the p-values reported by
>summaryAffyRNAdeg?
>
> The plots of average probe intensity vs probe number (5'<-->3') for
some
>chips I have show a definite positive trend, but usually the last one
or
>two
>
>data points drive the curve negative. Does this correspond to any
known
>phenomenon?
>
>Thanks,
>Chris Paulse
>
>
>------------------------------
>
>Message: 3
>Date: Fri, 1 Aug 2003 08:24:07 +1000 (EST)
>From: Rob Dunne <Rob.Dunne at csiro.au>
>Subject: [BioC] Repost: marrayNorm 1.1.3 gets stuck
>To: bioconductor at stat.math.ethz.ch
>Message-ID: <16169.38663.319920.3044 at pride.nsw.cmis.CSIRO.AU>
>Content-Type: text/plain; charset=us-ascii
>
>Hi List,
>
>Please excuse the repost. No one responded to my
>previous post -- and it seems to me to be quite
>important.
>
>The problem is the new marrayNorm 1.1.3
>(installed with bioconductor 1.2) -- which seems to get
>stuck in an endless loop
>
>
>marrayNorm 1.1.3 (installed with bioconductor 1.2)
> > unix.time(experiment1.norm<-maNorm(experiment1, norm="loess"))
>Timing stopped at: 8874.73 19.65 10289.06 0 0
>
>ie I interrupted the process -
>but with marrayNorm 1.1.1 reinstalled
>
> marrayNorm 1.1.1
> > unix.time(experiment1.norm<-maNorm(experiment1, norm="loess"))
>[1] 803.99 29.73 843.40 0.00 0.00
>
>
>
>is there a known problem with this package?
>
> bye
> rob
>
>--
>Rob Dunne Fax: +61 2 9325 3200 Tel: +61 2 9325 3263
>CSIRO Mathematical and Information Sciences +61 2 9325 3100
>Locked Bag 17, North Ryde, New South Wales, Australia, 1670
>http://matilda.vu.edu.au/~dunne Email: Rob.Dunne at csiro.au
>
> Java has certainly revolutionized marketing and litigation.
>
>
>------------------------------
>
>Message: 4
>Date: Fri, 01 Aug 2003 12:09:54 +1000
>From: Gordon Smyth <smyth at wehi.edu.au>
>Subject: [BioC] Re: Spelling mistakes and some questions re limma
>To: "Dave Waddell" <dwaddell at nutecsciences.com>
>Cc: BioC Mailing List <bioconductor at stat.math.ethz.ch>
>Message-ID: <5.2.0.9.1.20030801111855.00aed328 at imaphost.wehi.edu.au>
>Content-Type: text/plain; charset="us-ascii"; format=flowed
>
>Dear Dave,
>
>At 10:45 PM 31/07/2003, Dave Waddell wrote:
> >You have a couple of spelling mistakes in the page:
> >
>
><http://bioinf.wehi.edu.au/limma/library/limma/html/5linearmodels.html>http
>://bioinf.wehi.edu.au/limma/library/limma/html/5linearmodels.html
> >
> >estime and explanded
>
>Thanks for letting me know. These typos have been corrected in later
>versions of limma.
>
> >Can you point me to a place that would more fully explain the
design
> >matrix and contrasts with respect to 2-colour dye experiments?
>
>My best suggestion at this time is:
>
>Yang, Y. H., and Speed, T. P. (2003). Design and analysis of
comparative
>microarray experiments. In T. P. Speed (ed.), Statistical Analysis of
Gene
>Expression Microarray Data. Chapman & Hall/CRC Press, pages 35-91.
>
>But basically limma is breaking new ground here so there are no good
>references for this stuff apart from the User's Guide itself. I am
working
>on providing more user friendly interfaces to create design and
contrast
>matrices and more documentation, but obviously these things take time.
In
>the meantime, a local statistician would be able to give you some
help. Or
>you could ask for help on bioconductor about specific designs.
>
> > In some Bioconductor packages, the design matrix appears to be
> > applicable to the Cy3/Cy5 experiment as a whole and in others to
the
> > individual Cy3 and Cy5 experiments.
>
>I am not clear what you mean here. As far as I know, limma is the
only
>package to have the concept of a design matrix and limma is designed
to
>analyze the whole experiment at once. Other packages basically assume
you
>are making only one comparison usually with replicate arrays.
>
> > It is very confusing. In addition, the meaning of a contrasts
matrix
>and
> > how to put one together is not very clear. Both of these values,
if
> > applied incorrectly, would appear to me (as a non-statistician
assigned
> > to put together a package) to completely change the results.
>
>Yes, this is true.
>
> > Finally, can you tell me how limma handles control spots?
>
>The only explicit handling of control spots in limma is in the plotMA
>function. I assume that you will leave the control spots in during
the
>normalization (perhaps using weights to downweight ratio controls
spots or
>to upweight MSP titration spots) and you will remove them before
doing
>inference about differential expression. There are subsetting commands
to
>make removing control spots easy.
>
> >Thanks for a great package, Dave.
>
>Thanks for your comments.
>
>Gordon
>
>
>------------------------------
>
>Message: 5
>Date: Thu, 31 Jul 2003 22:31:13 -0400 (EDT)
>From: "Rafael A. Irizarry" <ririzarr at jhsph.edu>
>Subject: Re: [BioC] RMA t-test
>To: James MacDonald <jmacdon at med.umich.edu>
>Cc: bioconductor at stat.math.ethz.ch, dgrigor1 at jhmi.edu
>Message-ID:
> <Pine.GSO.4.10.10307312222420.8322-100000 at athena.biostat.jhsph.edu>
>Content-Type: TEXT/PLAIN; charset=US-ASCII
>
>hi! fyi, all the ROC curves in the NAR paper comparing expression
measures
>was done on 1-1 comps (i.e. 2 chips). rma seems to perform weel
>according to these curves. notice that if you only have one
>chip median polish turns into a median which in my opinion is not a
>terrible thing to use.
>
>as for t-tests with two arrays all you could use for estimating
>variability (denominator in the t-test) are the residuals from the
median
>polish fit. these have (at least) two problemsB
>1) as james points out they have no information about biological
>variation
>2) its not clear what the statistical properites of these residuals
are.
>the se estimate one gets with expresso-rma are given only as an
ad-hoc
>estimate of uncertainty of the expression estimates due to
technology.
>
>hope this helps,
>rafael
>On Mon, 28 Jul 2003, James MacDonald wrote:
>
> > I would be cautious about using RMA with only two chips. You will
be
> > estimating the probe-specific intensity with only two observations,
so
> > it is doubtful that the estimate will be very accurate. I recall
reading
> > somewhere that a good minimum number of chips is around 5-6 for
RMA.
> >
> > As for a t-test with only one observation per group, this is not
> > possible. How are you going to estimate the variance for each
group?
> > Without replication all you can do is ratios, and you are then
stuck
> > with the assumption that large ratios equal significant
differences.
> >
> > Jim
> >
> >
> >
> >
> > James W. MacDonald
> > Affymetrix and cDNA Microarray Core
> > University of Michigan Cancer Center
> > 1500 E. Medical Center Drive
> > 7410 CCGC
> > Ann Arbor MI 48109
> > 734-647-5623
> >
> > >>> DMITRY GRIGORYEV <dgrigor1 at jhmi.edu> 07/28/03 12:08PM >>>
> > Hi everyone.
> >
> > One quick question.
> > When I run RMA on just two chips, how could I conduct pairwise
t-test
> > for each probe set between these chips?
> >
> > Thank you
> >
> > Dima
> >
> > _______________________________________________
> > Bioconductor mailing list
> > Bioconductor at stat.math.ethz.ch
> > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
> >
> > _______________________________________________
> > Bioconductor mailing list
> > Bioconductor at stat.math.ethz.ch
> > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
> >
>
>
>------------------------------
>
>Message: 6
>Date: Fri, 01 Aug 2003 15:30:19 +1000
>From: Gordon Smyth <smyth at wehi.edu.au>
>Subject: Re: [BioC] Repost: marrayNorm 1.1.3 gets stuck
>To: Rob.Dunne at csiro.au
>Cc: BioC Mailing List <bioconductor at stat.math.ethz.ch>
>Message-ID: <5.2.1.1.1.20030801151709.00b1ee48 at imaphost.wehi.edu.au>
>Content-Type: text/plain; charset="us-ascii"; format=flowed
>
>
> >Hi List,
> >
> >Please excuse the repost. No one responded to my
> >previous post -- and it seems to me to be quite
> >important.
> >
> >The problem is the new marrayNorm 1.1.3
> >(installed with bioconductor 1.2) -- which seems to get
> >stuck in an endless loop
>
>It isn't in an endless loop, it's just very slow.
>
>The problem is the loess function. If you use family="symmetric" and
>iterations=4 to get a robust loess curve rather than just least
squares,
>then the function is quite slow with lots of data and you get heaps
of
>warnings associated with memory limits and the use of a k-d tree. If
you
>use surface="direct" to avoid the k-d tree and stop the warnings, then
the
>function is very slow indeed with lots of points. You see the result
below
>when you try to run it on 30,000 data points.
>
>Versions of marrayNorm prior to 1.1.3 used least squares for the
loess
>curves - much quicker but not ideal as a normalization tool.
>
>I have used some tricks to avoid this sort of speed degradation in
the
>limma package. I believe that Jean is in the process of implementing
to
>same sort of thing in the marrayNorm package.
>
>Regards
>Gordon
>
> >marrayNorm 1.1.3 (installed with bioconductor 1.2)
> > > unix.time(experiment1.norm<-maNorm(experiment1, norm="loess"))
> >Timing stopped at: 8874.73 19.65 10289.06 0 0
> >
> >ie I interrupted the process -
> >but with marrayNorm 1.1.1 reinstalled
> >
> > marrayNorm 1.1.1
> > > unix.time(experiment1.norm<-maNorm(experiment1, norm="loess"))
> >[1] 803.99 29.73 843.40 0.00 0.00
> >
> >
> >
> >is there a known problem with this package?
> >
> > bye
> > rob
> >
> >--
> >Rob Dunne Fax: +61 2 9325 3200 Tel: +61 2 9325 3263
> >CSIRO Mathematical and Information Sciences +61 2 9325 3100
> >Locked Bag 17, North Ryde, New South Wales, Australia, 1670
> ><http://matilda.vu.edu.au/~dunne>http://matilda.vu.edu.au/~dunne
Email:
>
><https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor>Rob.Dunne
at
> >csiro.au
>
>
>------------------------------
>
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