[BioC] Extremely low p-values in limma
Muller, Pie
Pie.Muller at liverpool.ac.uk
Mon Sep 17 12:13:46 CEST 2007
Dear all
I am analysing data obtained from an experiment with an interwoven loop design using limma. The design and the code are listed below. Many of our probes show extremely low adjusted p-values with values low as 1.748434e-71. Hence, I was wondering whether my code somehow treats technical replication as independent ones, or whether such low p-values could be genuine. Has anyone any ideas?
Many thanks for your suggestions!
Pie
My experimental design:
We have 3 groups, A, B and C with 5 biological (independent) replicates for each group (15 RNA targets in total). The RNA's were co-hybridised to a two colour array whereby each target was twice labelled with Cy3 and twice with Cy5 in the following way:
File Cy3 Cy5
File1 A1 C2
File2 A1 B1
File3 A2 C3
File4 A2 B2
File5 A3 C4
File6 A3 B3
File7 A4 C5
File8 A4 B4
File9 A5 C1
File10 A5 B5
File11 B1 A3
File12 B1 C1
File13 B2 C2
File14 B2 A4
File15 B3 C3
File16 B3 A5
File17 B4 C4
File18 B4 A1
File19 B5 C5
File20 B5 A2
File21 C1 A2
File22 C1 B3
File23 C2 A3
File24 C2 B4
File25 C3 A4
File26 C3 B5
File27 C4 A5
File28 C4 B1
File29 C5 A1
File30 C5 B2
My code for fitting the linear model:
design=modelMatrix(targets, ref="A1")
cor=duplicateCorrelation(MA, design, ndups=4, spacing=1, weights=w)
fit=lmFit(MA, cor=cor$consensus.correlation, design, ndups=4, spacing=1, weights=w)
cont.matrix=makeContrasts(AvsB=(A2+A3+A4+A5-B1-B2-B3-B4-B5)/5, AvsC=(A2+A3+A4+A5-C1-C2-C3-C4-C5)/5, CvsB=(C1+C2+C3+C4+C5-B1-B2-B3-B4-B5)/5, levels=design)
fit2=contrasts.fit(fit, cont.matrix)
fit2=eBayes(fit2)
topTable(fit2, coef="AvsB", adjust.method="fdr", sort.by="p")
-------------------------------------
Dr Pie Müller
Vector Group
Liverpool School of Tropical Medicine
Pembroke Place
Liverpool
L3 5QA
UK
Tel +44(0) 151 705 3225
Fax +44(0) 151 705 3369
http://www.liv.ac.uk/lstm
http://www.ivcc.com
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