[BioC] thanks diferent pvalues for a treatment when other contrasts areremoved from targets file
Agnieszka Zmienko
akisiel at ibch.poznan.pl
Wed Feb 18 11:36:38 CET 2009
Hi Jim!
Thanks for explanation. Its very helpful.
Agnieszka
At 16:31 2009-02-17, James MacDonald wrote:
>Hi Agnieszka,
>
>Neither approach is more correct than the other, but the second is very
>likely to be more powerful.
>
>In either case the numerator of the contrast will be the same. However,
>the denominator of the contrast is based on the intra-group variability
>for all of the groups in your linear model. So if you only include the
>first treatment comparison in your model then the denominator will be
>based on just those two groups. If you use all 20 of your slides, then
>you increase the amount of data that can be used to compute the
>intra-group variability.
>
>Since the accuracy of a variance estimate is dependent on the amount of
>data (it gets more accurate as you increase the amount of data used),
>you will probably have more power to detect differences if you include
>all the data in your linear model. And more power is usually considered
>to be better.
>
>Best,
>
>Jim
>
>
>James W. MacDonald, M.S.
>Biostatistician
>Hildebrandt Lab
>8220D MSRB III
>1150 W. Medical Center Drive
>Ann Arbor MI 48109-0646
>734-936-8662
> >>> Agnieszka Zmienko <akisiel at ibch.poznan.pl> 02/17/09 9:05 AM >>>
>Hi!
>
>I am "pure" biologist so I strictly follow the
>limma userguide commands in my analysis but I have a problem.
>I have a set of microarrays with a common control
>channel. I have 4 biological replicates of each
>experiment. If I perform the simplest possible
>analysis for the first treatment
>(wt.NaCl/wt.pool) using only files
>043,046,048,077 as targets ("targetsA.txt"), I
>obtain different adjusted p.values (and different
>topTable) comparing to analysis with all twenty
>input files ("targetsB.txt") and extracting
>wt.NaCl contrast. Why? Which topTable is correct?
>
>
>Agnieszka
>
>
>Here are my targets files and the codes:
>
>TargetsA.txt
>
>SlideNumber Name FileName Cy3 Cy5
>43 wt.Na1 043.gpr wt.pool wt.NaCl
>46 wt.Na2 046.gpr wt.pool wt.NaCl
>48 wt.Na3 048.gpr wt.pool wt.NaCl
>77 wt.Na4 077.gpr wt.pool wt.NaCl
>
>TargetsB.txt
>
>SlideNumber Name FileName Cy3 Cy5
>43 wt.Na1 043.gpr wt.pool wt.NaCl
>46 wt.Na2 046.gpr wt.pool wt.NaCl
>48 wt.Na3 048.gpr wt.pool wt.NaCl
>77 wt.Na4 077.gpr wt.pool wt.NaCl
>44 wt.Cd1 044.gpr wt.pool wt.CdCl2
>47 wt.Cd2 047.gpr wt.pool wt.CdCl2
>49 wt.Cd3 049.gpr wt.pool wt.CdCl2
>78 wt.Cd4 078.gpr wt.pool wt.CdCl2
>75 mu1.U1 075.gpr wt.pool mu1.U
>70 mu1.U2 070.gpr wt.pool mu1.U
>71 mu1.U3 071.gpr wt.pool mu1.U
>80 mu1.U4 080.gpr wt.pool mu1.U
>67 mu2.U1 067.gpr wt.pool mu2.U
>74 mu2.U2 074.gpr wt.pool mu2.U
>79 mu2.U3 079.gpr wt.pool mu2.U
>68 mu2.U4 068.gpr wt.pool mu2.U
>72 mu3.U1 072.gpr wt.pool mu3.U
>73 mu3.U2 073.gpr wt.pool mu3.U
>69 mu3.U3 069.gpr wt.pool mu3.U
>88 mu3.U4 088.gpr wt.pool mu3.U
>
> > targetsA=readTargets("targetsA.txt")
> >
>RGA=read.maimages(targetsA,source="genepix",wt.fun=wtflags(weight=0,
>cutoff=-50))
>Read 043.gpr
>Read 046.gpr
>Read 048.gpr
>Read 077.gpr
> > spottypes=readSpotTypes("SpotTypes.txt")
> > RG$genes$Status=controlStatus(spottypes,RGA)
>Matching patterns for: ID Name
>Found 31200 cDNA
>Found 48 no_change
>Setting attributes: values Color
> > RGAb=backgroundCorrect(RGA, method="normexp", offset=50)
>Green channel
>Corrected array 1
>Corrected array 2
>Corrected array 3
>Corrected array 4
>Red channel
>Corrected array 1
>Corrected array 2
>Corrected array 3
>Corrected array 4
> > MAA=normalizeWithinArrays(RGAb)
> > fitA=lmFit(MAA)
>Warning message:
>In lmFit(MAA) :
> Some coefficients not estimable: coefficient interpretation may vary.
> > fitA=eBayes(fitA)
> > write.table(topTable(fitA,
>+
>number=100,adjust.method="BH",p.value=0.05,lfc=1,sort.by="P",resort.by="logFC"),"topTableA.txt")
> > write.fit(fitA, digits=6,F.adjust="BH",file="resultsA.txt")
>
>---------------------------------
> > targetsB=readTargets("targetsB.txt")
> >
>RGB=read.maimages(targetsB,source="genepix",wt.fun=wtflags(weight=0,
>cutoff=-50))
>Read 043.gpr
>Read 046.gpr
>Read 048.gpr
>ReRead 074.gpr
>Read 079.gpr
>Read 068.gpr
>Read 072.gpr
>Read 073.gpr
>Read 069.gpr
>Read 088.gpr
> > spottypes=readSpotTypes("SpotTypes.txt")
> > RG$genes$Status=controlStatus(spottypes,RGB)
>Matching patterns for: ID Name
>Found 31200 cDNA
>Found 48 no_change
>Setting attributes: values Color
> > RGBb=backgroundCorrect(RGB, method="normexp", offset=50)
>Green channel
>Corrected array 1
>Corrected array 2
>Corrected array 3
>Corrected array 4
>Corrected array 5
>Corrected array 6
>Corrected array 7
>Corrected array 8
>Corrected array 9
>Corrected array 10
>Corrected array 11
>Corrected array 12
>Corrected array 13
>Corrected array 14
>Corrected array 15
>Corrected array 16
>Corrected array 17
>Corrected array 18
>Corrected array 19
>Corrected array 20
>Red channel
>Corrected array 1
>Corrected array 2
>Corrected array 3
>Corrected array 4
>Corrected array 5
>Corrected array 6
>Corrected array 7
>Corrected array 8
>Corrected array 9
>Corrected array 10
>Corrected array 11
>Corrected array 12
>Corrected array 13
>Corrected array 14
>Corrected array 15
>Corrected array 16
>Corrected array 17
>Corrected array 18
>Corrected array 19
>Corrected array 20
> > MAB=normalizeWithinArrays(RGBb)
> > designB=modelMatrix(targetsB,ref="wt.pool")
>Found unique target names:
> mu1.U mu2.U mu3.U wt.CdCl2 wt.NaCl wt.pool
> > designB
> mu1.U mu2.U mu3.U wt.CdCl2 wt.NaCl
> [1,] 0 0 0 0 1
> [2,] 0 0 0 0 1
> [3,] 0 0 0 0 1
> [4,] 0 0 0 0 1
> [5,] 0 0 0 1 0
> [6,] 0 0 0 1 0
> [7,] 0 0 0 1 0
> [8,] 0 0 0 1 0
> [9,] 1 0 0 0 0
>[10,] 1 0 0 0 0
>[11,] 1 0 0 0 0
>[12,] 1 0 0 0 0
>[13,] 0 1 0 0 0
>[14,] 0 1 0 0 0
>[15,] 0 1 0 0 0
>[16,] 0 1 0 0 0
>[17,] 0 0 1 0 0
>[18,] 0 0 1 0 0
>[19,] 0 0 1 0 0
>[20,] 0 0 1 0 0
> > fitB=lmFit(MAB,designB)
>Warning message:
>In lmFit(MAB, designB) :
> Some coefficients not estimable: coefficient interpretation may vary.
> > contrast.matrix=makeContrasts(wt.NaCl,levels=designB)
> > contrast.matrix
> Contrasts
>Levels wt.NaCl
> mu1.U 0
> mu2.U 0
> mu3.U 0
> wt.CdCl2 0
> wt.NaCl 1
> > fitB=contrasts.fit(fitB,contrast.matrix)
> > fitB=eBayes(fitB)
> > write.table(topTable(fitB,
>+
>number=100,adjust.method="BH",p.value=0.05,lfc=1,sort.by="P",resort.by="logFC"),"topTableB.txt")
> > write.fit(fitB, digits=6,F.adjust="BH",file="resultsB.txt")
>
>
>
>Dr Agnieszka ̄mieñko
>
>Centrum Doskonalosci CENAT
>Instytut Chemii Bioorganicznej Polskiej Akademii Nauk
>Noskowskiego 12/14
>61-704 Poznañ
>tel. (61) 8528503 wew. 249
>fax: (61) 8520532
>
>Agnieszka Zmienko, Ph.D.
>
>CENAT
>Institute of Bioorganic Chemistry
>Polish Academy of Sciences
>Noskowskiego 12/14
>61-704 Poznan, Poland
>phone (0048) 61-8528503 ext. 249
>fax: (0048) 61-8520532
>
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>**********************************************************
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Dr Agnieszka ¯mieñko
Centrum Doskonalosci CENAT
Instytut Chemii Bioorganicznej Polskiej Akademii Nauk
Noskowskiego 12/14
61-704 Poznañ
tel. (61) 8528503 wew. 249
fax: (61) 8520532
Agnieszka Zmienko, Ph.D.
CENAT
Institute of Bioorganic Chemistry
Polish Academy of Sciences
Noskowskiego 12/14
61-704 Poznan, Poland
phone (0048) 61-8528503 ext. 249
fax: (0048) 61-8520532
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