[BioC] Loop design - biological, technical replication and contrasts

Maciej Jończyk mjonczyk at biol.uw.edu.pl
Tue Mar 2 19:35:21 CET 2010


I also think about lower p-value cutoff (0,01).

Below I pasted information about my experimental design (it is from my
previus message).

I have 2x2 factorial experiment conducted in a loop-design (two-colour
data).
There are two maize lines (dh7, dl3) and two temperature treatments
(cold=c and control=k).
Following hybridizations were conducted : dh_c vs dh_k; dh_k vs dl_k;
dl_k vs dl_c; dl_c vs dh_c
(forming a square on a diagram)
and two (diagonal on a diagram), namely: dl_k vs dh_c and dh_k vs dl_c.
I have four biological replications of this design, including dye-swap
(i.e. two hyb. cy3-cy5 and two cy5-cy3).
In each biological replication I have also three technical replications
of each RNA source
(i.e. in dh_c vs dh_k; dl_c vs dh_c and dl_k vs dh_c, sample dh_c is
from the same RNA pool).

I don't know how analyse it in limma. I want to get following contrasts:
dh_c vs dh_k; dh_k vs dl_k; dl_k vs dl_c; dl_c vs dh_c and include
effect of temperature,
maize line and interaction.

Avehna <avhena at gmail.com> nadawca :

> > Hi Maciej:I have the same problem, I did the same procedure but
> > still I'm getting large numbers for differentially expressed
> > genes. I could reduce this number by defining p.value = 0.01 in
> > decideTests. But I'm not completely sure whether changing the
> > "method" for decideTests and/or pvalue should give better results.
> > I'm looking forward to someone else answer.Best
> > Regards,Avhena2010/3/2 Maciej Jończyk <mjonczyk at biol.uw.edu.pl> Hi
> > again,  I apologise for replying to my own post, but it helps keep
> > track if someone will be interested.  I analysed my data with single
> > channel analysis in limma, according to Chapter 9. of limma
> > usersguide.  I changed my targets file (to make it more condensed)
> > and removed suffix which identified biological replication. So my
> > targets looks like:  >nt_trg     SlideNumber              
> >     FileName Cy3 Cy5 1           93
> >  c_093_DH_K_vs_DH_CHex.gpr  hk  hc 2          104
> >  c_104_DH_CH_vs_DH_Kex.gpr  hc  hk 3          116  
> >  c_116_DHK_vs_DHCHex.gpr  hk  hc 4           16  
> > c_016_DH_C_vs_DH_Kex.gpr  hc  hk 5           94  
> > c_094_DH_K_vs_DL_Kex.gpr  hk  lk 6          105  
> > c_105_DL_K_vs_DH_Kex.gpr  lk  hk 7          117    
> > c_117_DHK_vs_DLKex.gpr  hk  lk 8          139  
> > c_139_DL_K_vs_DH_Kex.gpr  lk  hk 9           92
> >  c_092_DL_CH_vs_DL_Kex.gpr  lc  lk 10         106
> >  c_106_DL_K_vs_DL_CHex.gpr  lk  lc 11         118  
> >  c_118_DLCH_vs_DLKex.gpr  lc  lk 12          23  
> > c_023_DL_K_vs_DL_Cex.gpr  lk  lc 13          95
> > c_095_DL_CH_vs_DH_CHex.gpr  lc  hc 14         107
> > c_107_DH_CH_vs_DL_CHex.gpr  hc  lc 15         119  
> > c_119_DLCH_vs_DHCHex.gpr  lc  hc 16         136  
> > c_136_DH_C_vs_DL_Cex.gpr  hc  lc 17         101
> >  c_101_DL_K_vs_DH_CHex.gpr  lk  hc 18         103
> >  c_103_DH_CH_vs_DL_Kex.gpr  hc  lk 19         121  
> >  c_121_DLK_vs_DHCHex.gpr  lk  hc 20          15  
> > c_015_DH_C_vs_DL_Kex.gpr  hc  lk 21         100
> >  c_100_DH_K_vs_DL_CHex.gpr  hk  lc 22         102
> >  c_102_DL_CH_vs_DH_Kex.gpr  lc  hk 23         120  
> >  c_120_DHK_vs_DLCHex.gpr  hk  lc 24         140  
> > c_140_DL_C_vs_DH_Kex.gpr  lc  hk   I transform it to apropriate
> > form: >tgr_sc=targetsA2C(nt_trg) >tgr_sc       channel.col
> > SlideNumber                   FileName Target 1.1      
> >      1          93  c_093_DH_K_vs_DH_CHex.gpr     hk 1.2
> >            2          93  c_093_DH_K_vs_DH_CHex.gpr  
> >   hc 2.1            1         104
> >  c_104_DH_CH_vs_DH_Kex.gpr     hc 2.2            2      
> >   104  c_104_DH_CH_vs_DH_Kex.gpr     hk 3.1            1
> >         116    c_116_DHK_vs_DHCHex.gpr     hk 3.2      
> >      2         116    c_116_DHK_vs_DHCHex.gpr     hc 4.1
> >            1          16   c_016_DH_C_vs_DH_Kex.gpr  
> >   hc 4.2            2          16  
> > c_016_DH_C_vs_DH_Kex.gpr     hk 5.1            1        
> >  94   c_094_DH_K_vs_DL_Kex.gpr     hk 5.2            2  
> >        94   c_094_DH_K_vs_DL_Kex.gpr     lk 6.1        
> >    1         105   c_105_DL_K_vs_DH_Kex.gpr     lk 6.2  
> >          2         105   c_105_DL_K_vs_DH_Kex.gpr     hk
> > 7.1            1         117     c_117_DHK_vs_DLKex.gpr
> >     hk 7.2            2         117    
> > c_117_DHK_vs_DLKex.gpr     lk 8.1            1        
> > 139   c_139_DL_K_vs_DH_Kex.gpr     lk 8.2            2  
> >       139   c_139_DL_K_vs_DH_Kex.gpr     hk 9.1          
> >  1          92  c_092_DL_CH_vs_DL_Kex.gpr     lc 9.2    
> >        2          92  c_092_DL_CH_vs_DL_Kex.gpr     lk
> > 10.1           1         106  c_106_DL_K_vs_DL_CHex.gpr  
> >   lk 10.2           2         106
> >  c_106_DL_K_vs_DL_CHex.gpr     lc 11.1           1      
> >   118    c_118_DLCH_vs_DLKex.gpr     lc 11.2           2
> >         118    c_118_DLCH_vs_DLKex.gpr     lk 12.1      
> >     1          23   c_023_DL_K_vs_DL_Cex.gpr     lk 12.2
> >           2          23   c_023_DL_K_vs_DL_Cex.gpr    
> > lc 13.1           1          95 c_095_DL_CH_vs_DH_CHex.gpr
> >     lc 13.2           2          95
> > c_095_DL_CH_vs_DH_CHex.gpr     hc 14.1           1      
> >   107 c_107_DH_CH_vs_DL_CHex.gpr     hc 14.2           2  
> >       107 c_107_DH_CH_vs_DL_CHex.gpr     lc 15.1          
> > 1         119   c_119_DLCH_vs_DHCHex.gpr     lc 15.2      
> >     2         119   c_119_DLCH_vs_DHCHex.gpr     hc 16.1  
> >         1         136   c_136_DH_C_vs_DL_Cex.gpr     hc
> > 16.2           2         136   c_136_DH_C_vs_DL_Cex.gpr  
> >   lc 17.1           1         101
> >  c_101_DL_K_vs_DH_CHex.gpr     lk 17.2           2      
> >   101  c_101_DL_K_vs_DH_CHex.gpr     hc 18.1           1  
> >       103  c_103_DH_CH_vs_DL_Kex.gpr     hc 18.2        
> >   2         103  c_103_DH_CH_vs_DL_Kex.gpr     lk 19.1    
> >       1         121    c_121_DLK_vs_DHCHex.gpr     lk
> > 19.2           2         121    c_121_DLK_vs_DHCHex.gpr
> >     hc 20.1           1          15  
> > c_015_DH_C_vs_DL_Kex.gpr     hc 20.2           2        
> >  15   c_015_DH_C_vs_DL_Kex.gpr     lk 21.1           1  
> >       100  c_100_DH_K_vs_DL_CHex.gpr     hk 21.2        
> >   2         100  c_100_DH_K_vs_DL_CHex.gpr     lc 22.1    
> >       1         102  c_102_DL_CH_vs_DH_Kex.gpr     lc 22.2
> >           2         102  c_102_DL_CH_vs_DH_Kex.gpr    
> > hk 23.1           1         120  
> >  c_120_DHK_vs_DLCHex.gpr     hk 23.2           2        
> > 120    c_120_DHK_vs_DLCHex.gpr     lc 24.1           1  
> >       140   c_140_DL_C_vs_DH_Kex.gpr     lc 24.2        
> >   2         140   c_140_DL_C_vs_DH_Kex.gpr     hk  Next, I
> > made design matrix  >u=unique(tgr_sc$Target)
> > >f=factor(tgr_sc$Target,levels=u) >design=model.matrix(~0+f)
> > >colnames(design)=u >design     hk hc lk lc 1   1  0  0  0 2  
> > 0  1  0  0 3   0  1  0  0 4   1  0  0  0 5   1  0  0
> >  0 6   0  1  0  0 7   0  1  0  0 8   1  0  0  0 9   1
> >  0  0  0 10  0  0  1  0 11  0  0  1  0 12  1  0  0  0
> > 13  1  0  0  0 14  0  0  1  0 15  0  0  1  0 16  1  0
> >  0  0 17  0  0  0  1 18  0  0  1  0 19  0  0  1  0 20
> >  0  0  0  1 21  0  0  0  1 22  0  0  1  0 23  0  0  1
> >  0 24  0  0  0  1 25  0  0  0  1 26  0  1  0  0 27  0
> >  1  0  0 28  0  0  0  1 29  0  0  0  1 30  0  1  0  0
> > 31  0  1  0  0 32  0  0  0  1 33  0  0  1  0 34  0  1
> >  0  0 35  0  1  0  0 36  0  0  1  0 37  0  0  1  0 38
> >  0  1  0  0 39  0  1  0  0 40  0  0  1  0 41  1  0  0
> >  0 42  0  0  0  1 43  0  0  0  1 44  1  0  0  0 45  1
> >  0  0  0 46  0  0  0  1 47  0  0  0  1 48  1  0  0  0
> > attr(,"assign") [1] 1 1 1 1 attr(,"contrasts") attr(,"contrasts")$f
> > [1] "contr.treatment"  *Is it correct form my design? I see, that it
> > simply identifies what RNA was hybridized on each array.
> > >corfit=intraspotCorrelation(nt_img_lA,design) corfit$consensus [1]
> > 0.7341876
> > >fit=lmscFit(nt_img_lAq,design,correlation=corfit$consensus)  I want
> > to get contrasts "hc - hk", "lc - lk", "hc - lc", "hk - lk" and also
> > test effect of line and temperature. To do that I write this
> > command:
> >
>contr.matrix=makeContrasts(hc-hk,lc-lk,hc-lc,hk-lk,linia=(hc+hk-lc-lk)/2,temp=(hc+lc-hk-lk)/2,inter=(hc-lc)-(hk-lk),levels=design)
> >  * I'm not 100% sure that it's correct.
> > >contr.fit=contrasts.fit(fit,contr.matrix)
> > >contr.fit=eBayes(contr.fit)
> >
>wynik=decideTests(contr.fit,method="global",adjust.method="BH",p.value=0.05)
> > >summary(wynik)    hc - hk lc - lk hc - lc hk - lk linia  temp
> > inter -1    5865    5039    3014    2685  3931  7382
> >  1113 0    30922   33433   37177   38480 35896 28364 40776 1
> >     6594    4909    3190    2216  3554  7635  1492  From
> > that it seem that there is a lot of differentially expressed genes.
> > I feel that it isn't optimal design, here technical and
> > biological replications are treated in the same manner, aren't
> > they?  I've read about "duplicateCorrelation" command, is it
> > possible to combine it with single channel analysis? Or I should
> > rewrite target file (add number of replication) and rewrite
> > contrasts (e.g. hc-hk change to
> > "((hc1+hc2+hc3+hc4)-(hk1+hk2+hk3+hk4))/4 )?  And if I want to
> > include a dye effect, I should only add column with 1's to my
> > design, right?  Thank you for reading of my post. I'd be very
> > grateful for help. I've tried to analyse this data for a along
> > time and I think limma is the best choice.  Yours sincerely,  Maciej
> > Jończyk  Maciej Jończyk Department of Plant Molecular
> > Ecophysiology Institute of Plant Experimental Biology Faculty of
> > Biology, University of Warsaw 02-096 Warszawa, Miecznikowa 1
> > ___________________________________ NOCC,
> > http://nocc.sourceforge.net     -- This email was Anti Virus checked
> > by Astaro Security Gateway. http://www.astaro.com
> > _______________________________________________ Bioconductor mailing
> > list Bioconductor at stat.math.ethz.ch
> > https://stat.ethz.ch/mailman/listinfo/bioconductor Search the
> > archives:
> > http://news.gmane.org/gmane.science.biology.informatics.conductor


Maciej Jończyk
Department of Plant Molecular Ecophysiology
Institute of Plant Experimental Biology
Faculty of Biology, University of Warsaw
02-096 Warszawa, Miecznikowa 1



___________________________________
NOCC, http://nocc.sourceforge.net





More information about the Bioconductor mailing list