[BioC] Analysis affymetrix of experiment....help please

suparna mitra smitra at liverpool.ac.uk
Fri Sep 7 13:14:56 CEST 2012 

Oh thanks.. I missed this point. But can you suggest me one more thing...
when I tried adjust = "BH" (Benjamini-Hochberg I suppose) I got the same
result as  adjust = "fdr". for topTable. Is it normal?
Further when I tried to do vennDiagram I was surprized to see 0 in all
circles. Thus I thought I must be doing something wrong. Sorry if my
question is silly.
Here is what I tried.

> topTable(fit2.invivo, coef = 1, adjust = "fdr")

           ID      logFC   AveExpr         t      P.Value adj.P.Val
B

8819  7943047 -0.3640702  4.177681 -5.395110 3.942713e-05 0.3282013
-2.023533

9675  7950951 -0.3640702  4.177681 -5.395110 3.942713e-05 0.3282013
-2.023533

18889 8043581 -0.3640702  4.177681 -5.395110 3.942713e-05 0.3282013
-2.023533

19899 8053785 -0.3640702  4.177681 -5.395110 3.942713e-05 0.3282013
-2.023533

3713  7896238  0.7731154  2.999029  4.796490 1.434510e-04 0.9552974
-2.323922

19926 8054075 -0.3816217  4.062936 -4.557543 2.424324e-04 0.9998796
-2.454618

18660 8041642 -1.0007299  4.220083 -4.290346 4.379518e-04 0.9998796
-2.607991

3759  7896284 -0.7555604  5.727302 -4.159251 5.861601e-04 0.9998796
-2.685960

6238  7917530  0.5596335 11.170012  4.117421 6.433789e-04 0.9998796
-2.711203

15545 8010622 -0.3324189  3.771856 -3.971869 8.899739e-04 0.9998796
-2.800385

> topTable(fit2.invivo, coef = 2, adjust = "fdr")

           ID      logFC   AveExpr         t      P.Value adj.P.Val
B

621   7893126 -0.5848178  4.412764 -4.577179 0.0002321630 0.9999684
-2.469821

6238  7917530 -0.5783362 11.170012 -4.255023 0.0004737013 0.9999684
-2.652426

26642 8120756 -1.0354557  5.439265 -4.238568 0.0004913467 0.9999684
-2.662042

1687  7894197 -0.9004303  2.631359 -4.169362 0.0005731153 0.9999684
-2.702782

2353  7894871  0.8441561  4.815714  4.161413 0.0005833454 0.9999684
-2.707492

3641  7896166 -0.6206262  7.735431 -4.144225 0.0006060986 0.9999684
-2.717698

2088  7894602  0.4713716  2.841855  4.115413 0.0006462632 0.9999684
-2.734873

5638  7911243 -0.7263053  5.676410 -4.053352 0.0007421075 0.9999684
-2.772143

7851  7933619  0.4194965  8.480778  4.040446 0.0007637691 0.9999684
-2.779941

20151 8056222 -0.8981049  7.892249 -4.031734 0.0007787485 0.9999684
-2.785214

> topTable(fit2.invivo, coef = 3, adjust = "fdr")

           ID      logFC  AveExpr         t      P.Value adj.P.Val
B

2590  7895109 -0.9415442 4.766552 -5.803704 1.670491e-05 0.5562234
-0.6982314

6210  7917182 -0.2981341 3.273225 -5.028595 8.656989e-05 0.6545102
-1.2472882

27812 8132245 -0.4595908 5.409405 -4.995303 9.304487e-05 0.6545102
-1.2727646

867   7893372  1.3251627 3.017891  4.981783 9.581361e-05 0.6545102
-1.2831553

26802 8122099 -0.4740894 4.548920 -4.828048 1.338927e-04 0.6545102
-1.4031177

808   7893313  1.0125247 7.938503  4.739949 1.623493e-04 0.6545102
-1.4733549

26093 8115516 -0.5100673 6.294000 -4.703760 1.757561e-04 0.6545102
-1.5025187

587   7893092 -0.9608515 6.013864 -4.631511 2.059886e-04 0.6545102
-1.5612836

22913 8084605 -0.3491973 6.211757 -4.519801 2.634837e-04 0.6545102
-1.6535466

3828  7896353  0.6239117 4.207636  4.504578 2.724902e-04 0.6545102
-1.6662493

>

>

> results <- decideTests(fit2.invivo)

> vennDiagram(results)
see the plot attached.
Thanks,
Mitra


On 7 September 2012 12:03, Sean Davis <sdavis2 at mail.nih.gov> wrote:

> On Fri, Sep 7, 2012 at 6:57 AM, suparna mitra <smitra at liverpool.ac.uk
> >wrote:
>
> > Dear Sean,
> >   I have been reading Bioconductor and limma user guide and thus this is
> I
> > tried.
> > But just being a novice, wanted to make sure if I am right.
> > I know I have perform t-test when I created the contrast, but can you
> > please help me how can I perform unpaired t-test here. I am concerned as
> > the patients in groups are not same.
> >
>
>
> The t-test you performed was unpaired; unpaired is the "default".
>
> Sean
>
>
> > Thanks,
> > Mitra
> >
> > On 7 September 2012 11:41, Sean Davis <sdavis2 at mail.nih.gov> wrote:
> >
> > >
> > >
> > > On Fri, Sep 7, 2012 at 5:54 AM, suparna mitra <smitra at liverpool.ac.uk
> > >wrote:
> > >
> > >> Hello Group,
> > >> I am trying t analyze my affymetrix (HuGene-1_0-st-v1) data using BiC.
> > >> Previously i was using different softwares for this. And this is my
> > first
> > >> try with Bioconductor for big experiment. So thought to get some
> advice
> > in
> > >> the beginning.
> > >> I have Three groups of patient: (In-vivo)
> > >>  A-Acute reaction. Patient taking a drug X develops reaction.
> > >>  R-recovered (6 weeks after acute reaction-not longer taking drug X).
> > >>  T-Tolerant. Patient on X and tolerating treatment.
> > >>
> > >> Now in in-vitro study we used another constant Y
> > >>    RXY recovered and challenged with X+Y
> > >>    RY recovered challenged with only Y. RXY vs RY are to exclude
> effects
> > >> by
> > >> Y.
> > >>   TXY tolerant and challenged with X+Y,
> > >>   TY tolerant challenged with only Y. TXY vs TY are to exclude effects
> > by
> > >> Y.
> > >>
> > >> No I want to check the cross relation and effects A vs R, RvsT and
> Avs T
> > >> and  differentially expressed genes for each comparison. And the same
> in
> > >> invitro. There are not same patients in different groups, thus I
> think I
> > >> want to apply unpaired-t test.
> > >>
> > >> This is what I tried:
> > >> > sessionInfo()
> > >> R version 2.15.1 (2012-06-22)
> > >> Platform: i386-apple-darwin9.8.0/i386 (32-bit)
> > >>
> > >> locale:
> > >> [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
> > >>
> > >> attached base packages:
> > >> [1] stats     graphics  grDevices utils     datasets  methods   base
> > >>
> > >> other attached packages:
> > >>  [1] statmod_1.4.15              limma_3.12.1
> > >>  annotate_1.34.1             hugene10stprobeset.db_8.0.1
> > >> org.Hs.eg.db_2.7.1
> > >>
> > >>  [6] BiocInstaller_1.4.7         affycoretools_1.28.0
> >  KEGG.db_2.7.1
> > >>               GO.db_2.7.1                 AnnotationDbi_1.18.1
> > >> [11] affy_1.34.0                 Biobase_2.16.0
> > >>  BiocGenerics_0.2.0          pd.hugene.1.0.st.v1_3.6.0
> RSQLite_0.11.1
> > >>
> > >> [16] DBI_0.2-5                   oligo_1.20.4
> > >>  oligoClasses_1.18.0
> > >>
> > >>
> > >>  rmaOligoinvivo = oligo::rma(InVivodat1)
> > >> Background correcting
> > >> Normalizing
> > >> Calculating Expression
> > >>
> > >> > rmaOligoinvitro = oligo::rma(InVitrodat1)
> > >> Background correcting
> > >> Normalizing
> > >> Calculating Expression
> > >>
> > >> > maplot(rmaOligoinvivo)
> > >> > maplot(rmaOligoinvitro)
> > >> > InVivoTargets
> > >>  FileName Treatment
> > >> 1   MC1       A
> > >> 2   MC2       A
> > >> 3   MC3       A
> > >> 4   MC4       A
> > >> 5   MC5       A
> > >> 6   MC6       A
> > >> 7   MC7       R
> > >> 8   MC8        R
> > >> 9   MC9        R
> > >> 10 MC10        R
> > >> 11 MC11        R
> > >> 12 MC12        R
> > >> 13 MC13       T
> > >> 14 MC14        T
> > >> 15 MC15        T
> > >> 16 MC16        T
> > >> 17 MC17        T
> > >> 18 MC18        T
> > >> >
> > >>
> > >>
> >
> InVitroTargets=readTargets("~/Desktop/Recent/Liverpool-work-related/Micro_RawData/InVitroTargets.txt")
> > >> > InVitroTargets
> > >>    FileName Treatment Batch  CD4
> > >> 1  MC19       RY     1 High
> > >> 2  MC20        TY     1  Low
> > >> 3  MC21        RY     2 High
> > >> 4  MC22        TY     2 High
> > >> 5  MC23        TY     2  Low
> > >> 6  MC24        RY     2 High
> > >> 7  MC25        TXY     1  Low
> > >> 8  MC26       RXY     1 High
> > >> 9  MC27       RXY    2  Low
> > >> 10 MC28        TXY    2 High
> > >> 11 MC29        RXY     2 High
> > >> 12 MC30      TXY    2 High
> > >>
> > >> f.invivo <- factor(InVivoTargets$Treatment, levels = c("A", "R", "T"))
> > >>
> > >> design.invivo <- model.matrix(~0 + f.invivo)
> > >>
> > >> >
> > >>
> > >> > colnames(design.invivo) <- c("A", "R", "T")
> > >>
> > >> > fit.invivo <- lmFit(rmaOligoinvivo, design.invivo)
> > >>
> > >> > contrast.matrix.invivo <- makeContrasts(R-A, T-R, T-A,levels =
> > >> design.invivo)
> > >>
> > >> > fit2.invivo <- contrasts.fit(fit.invivo, contrast.matrix.invivo)
> > >>
> > >> > fit2.invivo <-eBayes(fit2.invivo)
> > >>
> > >> > topTable(fit2.invivo, coef = 1, adjust = "fdr")
> > >>
> > >>            ID      logFC   AveExpr         t      P.Value adj.P.Val
> > >> B
> > >>
> > >> 8819  7943047 -0.3640702  4.177681 -5.395110 3.942713e-05 0.3282013
> > >> -2.023533
> > >>
> > >> 9675  7950951 -0.3640702  4.177681 -5.395110 3.942713e-05 0.3282013
> > >> -2.023533
> > >>
> > >> 18889 8043581 -0.3640702  4.177681 -5.395110 3.942713e-05 0.3282013
> > >> -2.023533
> > >>
> > >> 19899 8053785 -0.3640702  4.177681 -5.395110 3.942713e-05 0.3282013
> > >> -2.023533
> > >>
> > >> 3713  7896238  0.7731154  2.999029  4.796490 1.434510e-04 0.9552974
> > >> -2.323922
> > >>
> > >> 19926 8054075 -0.3816217  4.062936 -4.557543 2.424324e-04 0.9998796
> > >> -2.454618
> > >>
> > >> 18660 8041642 -1.0007299  4.220083 -4.290346 4.379518e-04 0.9998796
> > >> -2.607991
> > >>
> > >> 3759  7896284 -0.7555604  5.727302 -4.159251 5.861601e-04 0.9998796
> > >> -2.685960
> > >>
> > >> 6238  7917530  0.5596335 11.170012  4.117421 6.433789e-04 0.9998796
> > >> -2.711203
> > >>
> > >> 15545 8010622 -0.3324189  3.771856 -3.971869 8.899739e-04 0.9998796
> > >> -2.800385
> > >> I am progressing in a right way? Further I want to perform unpaired t
> > test
> > >> for comparing AvsT and so on. Any help will be really great.
> > >>
> > >
> > > Hi, Mitra.  I think that looks about right.  You have already performed
> > > the unpaired t-test of AvsT (well, actually TvsA, but the p-values will
> > be
> > > the same) as coefficient 3.
> > >
> > > Sean
> > >
> > >
> >
> >
> >
> > --
> > Dr. Suparna Mitra
> > Wolfson Centre for Personalised Medicine
> > Department of Molecular and Clinical Pharmacology
> > Institute of Translational Medicine University of Liverpool
> > Block A: Waterhouse Buildings,  L69 3GL Liverpool
> >
> > Tel.  +44 (0)151 795 5394, Internal ext: 55394
> > M: +44 (0) 7511387895
> > Email id: smitra at liverpool.ac.uk
> > Alternative Email id: suparna.mitra.sm at gmail.com
> >
> >         [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > Bioconductor mailing list
> > Bioconductor at r-project.org
> > https://stat.ethz.ch/mailman/listinfo/bioconductor
> > Search the archives:
> > http://news.gmane.org/gmane.science.biology.informatics.conductor
> >
>
>         [[alternative HTML version deleted]]
>
> _______________________________________________
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>



-- 
Dr. Suparna Mitra
Wolfson Centre for Personalised Medicine
Department of Molecular and Clinical Pharmacology
Institute of Translational Medicine University of Liverpool
Block A: Waterhouse Buildings,  L69 3GL Liverpool

Tel.  +44 (0)151 795 5394, Internal ext: 55394
M: +44 (0) 7511387895
Email id: smitra at liverpool.ac.uk
Alternative Email id: suparna.mitra.sm at gmail.com
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