[BioC] warnings from li wong summary method in expresso
James W. MacDonald
jmacdon at med.umich.edu
Wed Jan 31 18:14:07 CET 2007
Hi Marco,
marco zucchelli wrote:
> Laurent,
>
> according to affy vignette and MBEI paper of Li and Wong >10 arrays should
> be enough.
> Anyway I tried to process my arrays with dChip and there I get no warnings
> at all.
>
> I also exported the expression values from dChip in a text file and loaded
> them into R.
>
> Even if expression values cannot be compared I applied the same LIMMA
> analysis to both the
> expression values form expresso and dChip and the results are pretty
> different. For example I tried 12 arrays in couples of 2 duplicates
> (i.e. 6 tissues) and from LIMMA I got the following up-down regulated
> patterns (1=up, -1=down).
>
> dCHIP
>
> T2-T1 T3-T2 T4-T3 T5-T4 T6-T5 counts
> [1,] 0 0 0 0 0 51742
> [2,] 0 0 0 0 1 1199
> [3,] 0 0 0 0 -1 616
> [4,] 0 0 -1 0 0 607
> [5,] 0 0 1 0 0 201
> [6,] 0 0 1 0 -1 101
> [7,] 0 0 0 1 -1 71
> [8,] 0 0 -1 0 1 27
> [9,] 0 0 0 1 0 20
> ....
> ....
>
> expresso
>
> T2-T1 T3-T2 T4-T3 T5-T4 T6-T5 counts
> [1,] 0 0 0 0 0 46464
> [2,] 0 0 0 0 1 2299
> [3,] 0 0 0 0 -1 1715
> [4,] 0 0 -1 0 0 1164
> [5,] 0 0 1 0 0 691
> [6,] 0 0 0 1 0 409
> [7,] 0 0 -1 0 1 344
> [8,] 0 0 1 0 -1 340
> [9,] 0 0 0 -1 0 316
> ....
> ....
> ....
>
>
> I would have expected smaller differences, or am I out fishing ?
You have to understand that dChip is closed-source software, so we don't
really know how Cheng Li implemented things. All we can do is take what
he has said and make assumptions where he has not been completely
descriptive. The same is true of the implementation of MAS5 in the affy
package. The end results are usually close (very close in the case of
MAS5), but not exactly the same.
If you really want dChip expression values, then your best bet is to use
dChip.
Best,
Jim
>
> I wonder you or someone else on the mailing list has any experience of this
> ...
>
>
> Marco
>
>
>
>
>
>
> On 1/31/07, lgautier at altern.org <lgautier at altern.org> wrote:
>
>>
>> Marco,
>>
>>
>> If I remember correctly, dChip authors were talking more of having
>> at least 25 chips. Obviously the number either 10, 16, 25 is not
>> a hard threshold, as the convergence depends on the very numerical
>> values.
>>
>> Knowing what are the probes failing is possible. A quick-but-dirty
>> way is to only edit the function
>> "generateExprVal.method.liwong".
>>
>> Try:
>> generateExprVal.method.liwong2 <- edit(generateExprVal.method.liwong)
>>
>> and edit the code as:
>>
>> probes <- t(probes)
>> if (ncol(probes) == 1) {
>> warning("method liwong unsuitable when only one probe pair")
>> list(exprs=as.vector(probes),se.exprs=rep(NA,length(probes)))
>> }
>> else {
>> tmp <- fit.li.wong(probes, ...)
>> if ( !tmp$convergence1 & !tmp$convergence2) {
>> id <- get("id", envir=parent.frame(3))
>> print(id)
>> }
>> list(exprs=tmp$theta,se.exprs=tmp$sigma.theta)
>> }
>>
>>
>> (the only change is near the end).
>>
>> Now you can use the summary method "liwong2" in place of "liwong".
>>
>> You can hack this to your specific need (and want to store the 'id'
>> into a variable in you global workspace for example).
>>
>>
>>
>> Hoping this helps,
>>
>>
>> Laurent
>>
>>
>>
>>
>>
>>
>> > James,
>> >
>> > I am actually using 16 hgu133plus2 arrays, so I find it a little
>> strange.
>> >
>> > Is there any way to know which probes failed (and how many totally) ?
>> >
>> > Does anybody know if dChip is still freely available? Seems like there
>> is
>> > no
>> > link anymore
>> > on the home page... I would like to cross check if the warnings are
>> coming
>> > up there as well
>> >
>> > Cherrs
>> >
>> > Marco
>> >
>> >
>> > On 1/25/07, James W. MacDonald <jmacdon at med.umich.edu> wrote:
>> >>
>> >> Hi Marco,
>> >>
>> >> marco zucchelli wrote:
>> >> > Hi,
>> >> >
>> >> > I am using in R the dChip method to normalize and summarize my
>> micro
>> >> > arrays.
>> >> > I tried several times and I always get warnings. What this does
>> mean?
>> >> Are
>> >> > the expression levels
>> >> > returned reliable anyway ?
>> >>
>> >> If you don't have enough samples, the LiWong method won't converge for
>> >> some of your probesets. Lack of convergence is usually not a good
>> thing.
>> >> I think the recommendation for using LiWong is to have at least 10 or
>> 15
>> >> samples.
>> >>
>> >> You might consider using a different method to summarize your data.
>> >>
>> >> Best,
>> >>
>> >> Jim
>> >>
>> >>
>> >> >
>> >> > I use R2.4.1 on linux redhat
>> >> >
>> >> > Marco
>> >> >
>> >> >
>> >> > eset <- expresso(hum.brain.embryo, bg.correct =
>> >> > FALSE,normalize.method="invariantset",
>> >> > pmcorrect.method = "pmonly",summary.method="liwong")
>> >> > normalization: invariantset
>> >> > PM/MM correction : pmonly
>> >> > expression values: liwong
>> >> > normalizing...done.
>> >> > 54675 ids to be processed
>> >> > | |
>> >> > |####################|
>> >> > There were 50 or more warnings (use warnings() to see the first 50)
>> >> >
>> >> > Warning messages:
>> >> > 1: No convergence achieved in outlier loop
>> >> > in: fit.li.wong(probes, ...)
>> >> > 2: No convergence achieved in outlier loop
>> >> > in: fit.li.wong(probes, ...)
>> >> > 3: No convergence achieved in outlier loop
>> >> > in: fit.li.wong(probes, ...)
>> >> > 4: No convergence achieved in outlier loop
>> >> > in: fit.li.wong(probes, ...)
>> >> >
>> >> > [[alternative HTML version deleted]]
>> >> >
>> >> > _______________________________________________
>> >> > Bioconductor mailing list
>> >> > Bioconductor at stat.math.ethz.ch
>> >> > https://stat.ethz.ch/mailman/listinfo/bioconductor
>> >> > Search the archives:
>> >> http://news.gmane.org/gmane.science.biology.informatics.conductor
>> >>
>> >>
>> >> --
>> >> James W. MacDonald, M.S.
>> >> Biostatistician
>> >> Affymetrix and cDNA Microarray Core
>> >> University of Michigan Cancer Center
>> >> 1500 E. Medical Center Drive
>> >> 7410 CCGC
>> >> Ann Arbor MI 48109
>> >> 734-647-5623
>> >>
>> >>
>> >> **********************************************************
>> >> Electronic Mail is not secure, may not be read every day, and should
>> not
>> >> be used for urgent or sensitive issues.
>> >>
>> >
>> > [[alternative HTML version deleted]]
>> >
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>> >
>> >
>> >
>>
>>
>>
>
--
James W. MacDonald, M.S.
Biostatistician
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623
**********************************************************
Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues.
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