[BioC] how to rank affy probesets by their probe-effect magnitude

[James W. MacDonald]

Hi Robert,

On 3/5/2012 1:22 PM, Robert Castelo wrote:
> dear list,
>
> i'm searching for a way to rank affy probesets from classical 3' affy
> arrays by their probe effect magnitude. i mean that i would like to know
> if a probeset is has a larger probe-specific effect than another one.
>
> i guess the solution should be in the affyPLM package since if i do
>
> library(affy)
> library(affyPLM)
>
> ab<- ReadAffy()
> pset<- fitPLM(ab)
>
>
> i obtain an object (pset) of the PLMset class which contains slots
> 'probe.coefs' and 'se.probe.coefs', where each is a list as many keys as
> probesets and where each probeset contains information on the probe
> effect of each probe within the probeset:
>
> head(names(pset at probe.coefs))
> [1] "1000_at"   "1001_at"   "1002_f_at" "1003_s_at" "1004_at"
> "1005_at"
> head(names(pset at se.probe.coefs))
> [1] "1000_at"   "1001_at"   "1002_f_at" "1003_s_at" "1004_at"
> "1005_at"
>
> pset at probe.coefs[[1]]
>               Overall
> probe_1   0.97287528
> probe_2   0.61454806
> probe_3  -2.81701693
> probe_4   1.68063395
> probe_5  -3.31991235
> probe_6   1.56657388
> probe_7  -3.30256264
> probe_8  -1.99431231
> probe_9  -0.35200585
> probe_10 -0.49024387
> probe_11 -1.09087811
> probe_12  0.22008832
> probe_13  2.54263342
> probe_14  3.71106614
> probe_15  2.12580554
> probe_16 -0.06729251
>
> pset at se.probe.coefs[[1]]
>              Overall
> probe_1  0.06124122
> probe_2  0.06039453
> probe_3  0.06180433
> probe_4  0.05948503
> probe_5  0.06727454
> probe_6  0.06016827
> probe_7  0.06233682
> probe_8  0.06791376
> probe_9  0.05960599
> probe_10 0.05963511
> probe_11 0.05868359
> probe_12 0.06046023
> probe_13 0.05885199
> probe_14 0.05829506
> probe_15 0.05837877
> probe_16 0.06340662
>
> however, i'm unsure how to proceed from now on to decide whether a
> particular probeset is more "affected" by probe-specific effects than
> other probeset. any suggestion would be highly appreciated,

I'm not sure what you are looking to do with these data, but remember 
that the probe-specific effects in RMA are estimated as a nuisance 
variable, which are then excluded from computation of the expression 
value. So by definition the probesets should not be affected by 
probe-specific effects.

Best,

Jim


>
> thanks,
> robert.
>
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-- 
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
4225 Roosevelt Way NE, # 100
Seattle WA 98105-6099