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

[Matthew McCall]

Robert,

I'm not sure exactly what you're after, but you might want to look at
the hgu133afrmavecs and hgu133plus2frmavecs data packages. The
probe-effect (probeVec), within-batch residual variance
(probeVarWithin), the between-batch residual variance
(probeVarBetween), and the within probeset standard deviation
(probesetSD) have all been computed using a large biologically diverse
data set.

Best,
Matt

On Mon, Mar 5, 2012 at 1:22 PM, Robert Castelo <robert.castelo at upf.edu> 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,
>
> thanks,
> robert.
>
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-- 
Matthew N McCall, PhD
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