Hi Nick:
You are right. There is something weird about your data. Did you
generate a simple pairwise plot (MvA or a simply scatter plot) of any
pair of the arrays?
From the SAM output, it seems that there is no differentially
expressed
genes. FDR are all close to 1, no matter what delta is, which means
100
percent identified (called) genes are false positive.
There is only 18 called genes, even though delta is already very
small,
and the falsely identified one become larger than identified genes!
Simon
Message: 3
Date: Thu, 22 Dec 2005 11:51:55 -0600
From: "Ettinger, Nicholas" <nicholas-ettinger@uiowa.edu>
Subject: [BioC] Newbie question regarding SAM analysis
To: <bioconductor at="" stat.math.ethz.ch="">
Message-ID:
<a4aa05ce92dacc43886d133db94a926e218cd063 at="" medicine-="" exch1.medicine.uiowa.edu="">
Content-Type: text/plain
Hello all!
This is my first post. Any help or suggestions would be greatly
appreciated!
I am trying to analyze 8 arrays (4 untreated, 4 treated; paired &
alternating) with SAM.
When I read the vignettes from 'siggenes' and looked at the sample
diagrams, I was expecting to see my 'Called' column go from some
number
much closer to the number of probes on the hgu133probe2 Affy gene chip
(something like 50,000 I think) down to zero. Why does it only start
at
18?
I am thoroughly confused by that.
Thanks for any suggestions!!
Happy Holidays to all!!
---Nick Ettinger
University of Iowa
Here is my code:
TotalData <- ReadAffy()
chipnumber <- length(sampleNames(TotalData))
chipnames <- sampleNames(TotalData)
eset_rma <- rma(TotalData)
K <- chipnumber/2
eset.cl <- rep(1:K, e = 2) * rep(c(-1, 1), K)
eset.gnames <- geneNames(TotalData)
sam.out <- sam(eset_rma, eset.cl, rand = 123, gene.names =
eset.gnames)
sam.out
SAM Analysis for the Two-Class Paired Case
Delta p0 False Called FDR
1 0.1 0.986 44.500 18 1
2 0.3 0.986 28.250 13 1
3 0.4 0.986 3.688 2 1
4 0.6 0.986 1.062 1 1
5 0.8 0.986 1.062 1 1
6 1.0 0.986 1.062 1 1
7 1.1 0.986 1.062 1 1
8 1.3 0.986 1.062 1 1
9 1.5 0.986 1.062 1 1
10 1.6 0.986 1.062 1 1
summary(sam.out)
SAM Analysis for the Two-Class Paired Case
s0 = 0.0646 (The 10 % quantile of the s values.)
Number of permutations: 16 (complete permutation)
MEAN number of falsely called genes is computed.
Delta p0 False Called FDR cutlow
cutup
j2 j1
1 0.1 0.986 44.500 18 1 -4.503 6.912
16 54674
2 0.3 0.986 28.250 13 1 -5.004 6.912
11 54674
3 0.4 0.986 3.688 2 1 -7.102 Inf
2 54676
4 0.6 0.986 1.062 1 1 -8.690 Inf
1 54676
5 0.8 0.986 1.062 1 1 -8.690 Inf
1 54676
6 1.0 0.986 1.062 1 1 -8.690 Inf
1 54676
7 1.1 0.986 1.062 1 1 -8.690 Inf
1 54676
8 1.3 0.986 1.062 1 1 -8.690 Inf
1 54676
9 1.5 0.986 1.062 1 1 -8.690 Inf
1 54676
10 1.6 0.986 1.062 1 1 -8.690 Inf
1 5 4676
