[BioC] P value for each probe

[kvyas]

Matthew and Suresh,

Thank you very much for the pointers. I will be sure to attempt them.

Kanan



>===== Original Message From Suresh Gopalan <gopalans2 at hotmail.com> =====
>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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