[BioC] P value for each probe

[Suresh Gopalan]

That's right Kanan.  Unless of course you want to do the analysis completely 
with probe level data.  In which case you may get some pinters in the 
article "ResurfP: a response surface aided parametric test for identifying 
differentials in GeneChip based oligonucleotide array experiments" in the 
deposited research section of Genome Biology: 
http://genomebiology.com/preprint/.  The URL for the full article that 
partially address this question and of selecting threshold in probe-level 
analysis of GeneChip arrays (or identification of differentials when 
studying other features using multiple independent measurements) can be 
found at  http://genomebiology.com/2004/5/11/P14 .

Suresh

----- Original Message ----- 
From: "Matthew Hannah" <Hannah at mpimp-golm.mpg.de>
To: <bioconductor at stat.math.ethz.ch>
Sent: Wednesday, October 06, 2004 9:47 AM
Subject: [BioC] P value for each probe


> Kanan,
>
> I think you are possibly getting confused. There is no such thing as a
> p-value for each probe. Maybe you are thinking of the mas5
> present/absent call p-values which can be obtained for each probeset. In
> which case you want this function from the affy package -
> mas5calls(Data)
>
> If you want to find out more about pm, mm, probesets etc... try calling
> the html help from R using
> help.start()
> and browsing the help for the affy package, also perhaps try some of
> these
> http://www.bioconductor.org/labmat.html
>
> Some of the affymetrix literature from their website also explains what
> stats mas5 uses.
>
> Also a minor point
> eset <- rma(Data)
> is redundant in your example below. pm is extracted from Data, not eset.
>
> HTH,
> Matt
>
>
> #####
>
>
> Bioconductor users,
>
>
> I have four CEL files from Affymetrix Mouse Array 430_2 and am trying to
> get
> the p values per probe. I would like to write this out into a tab
> delimited
> text file. Where am I stalling? This is what I've done:
>
>
> Change dir(to where CEL files are saved)
> Data <- ReadAffy()
> eset <- rma(Data)
> my.pm.data <- pm(Data)
> write.table (my.pm.data, file = "pmprobes3.csv", sep = ",", col.names =
> TRUE,
> row.names = probeNames(Data))
>
> This result is the following:
>
> Probe Sam1 Sam2 Sam3 Sam4
> 1415670_at01 340 383 376 320
> 1415670_at02 794 932 734 697
> 1415670_at03 1117 1366 1013 932
> 1415670_at04 97 97 148 94
> 1415670_at05 387 405 367 402
> 1415670_at06 485 553 391 343
> 1415670_at07 458 509 410 385
> 1415670_at08 507 684 616 545
> 1415670_at09 311 392 576 463
> 1415670_at10 691 822 688 588
> 1415670_at11 512 726 3201 2317
> 1415671_at01 1230 1212 873 770
> 1415671_at02 886 877 794 729
> 1415671_at03 1472 1682 1263 1152
> 1415671_at04 1171 1214 948 914
> 1415671_at05 390 479 435 396
> 1415671_at06 462 513 423 389
> 1415671_at07 987 1151 1102 815
> 1415671_at08 992 1066 1203 1013
> 1415671_at09 489 534 501 385
> 1415671_at10 401 509 379 293
> 1415671_at11 1443 1686 1410 1215
>
> Each gene has 11 pm probes.
> How can I get the p-value for each probe?
>
> Please help me out and thanks in advanced!
>
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