[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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