[BioC] RNA degradation (Chris Paulse)
Rafael A. Irizarry
ririzarr at jhsph.edu
Mon Aug 4 17:02:12 MEST 2003
i have to take a second look athos milan slides but its possible you
misinterpreted them. we dont expect gc content and location
to be confounded so i dont see how correcting for gc-content could help
here. the robust fitting of the linear model may help, as probes with more
variance usually result in more "outliers" and thus are counted less.
On Mon, 4 Aug 2003, Chris Paulse wrote:
> 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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> >Bioconductor at stat.math.ethz.ch
> >https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
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> >
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