[BioC] how to rank affy probesets by their probe-effect magnitude
Robert Castelo
robert.castelo at upf.edu
Mon Mar 5 19:22:24 CET 2012
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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