[BioC] Positive correlation between dye-swap technical replicates

[James W. MacDonald]

Hi Michal,

Michał Góralski wrote:
> Dear All,
> 
> I have some doubts concerning linear model used in my data analysis. I 
> was searching for the answer on the mail list but I didn't find the 
> similar case.
> I analyse tobacco roots treated with 2 types of stress: NaCl and CdCl2. 
> I have pooled common reference and I have 3 biological replicates of 
> treated plants. I also did dye swaps as technical replicate.
> This is my targets file:
> SlideNumber    Name    FileName    Cy3    Cy5
> 13244317    21    13244317.gpr    Control    NaCl
> 13244318    22    13244318.gpr    Control    NaCl
> 13244315    23    13244315.gpr    Control    NaCl
> 13244319    31    13244319.gpr    Control    CdCl2
> 13244337    32    13244337.gpr    Control    CdCl2
> 13244316    33    13244316.gpr    Control    CdCl2
> 13244330    21    13244330.gpr    NaCl    Control
> 13244329    22    13244329.gpr    NaCl    Control
> 13244331    23    13244331.gpr    NaCl    Control
> 13244333    31    13244333.gpr    CdCl2    Control
> 13244335    32    13244335.gpr    CdCl2    Control
> 13244336    33    13244336.gpr    CdCl2    Control
> 
> I did background subtraction with method "normexp" and normalization 
> "pronttip loess", without normalization between arrays.
> 
> Now I have the vector indicating biological and technical replicates.
> 
>  >biolrep=c(1,2,3,4,5,6,1,2,3,4,5,6)
> 
> and create model matrix:
> 
>  >design=modelMatrix(targets, ref="Control")
>  > design
>      CdCl2 NaCl
> [1,]     0    1
> [2,]     0    1
> [3,]     0    1
> [4,]     1    0
> [5,]     1    0
> [6,]     1    0
> [7,]     0   -1
> [8,]     0   -1
> [9,]     0   -1
> [10,]    -1    0
> [11,]    -1    0
> [12,]    -1    0
> 
> I'm interested in such contrasts:
> 
>  >cmatrix=makeContrasts(NaCl, CdCl2, NaCl-CdCl2,levels=design)
>  > cmatrix
>       Contrasts
> Levels  NaCl CdCl2 NaCl - CdCl2
>  CdCl2    0     1           -1
>  NaCl     1     0            1
> 
> Object for duplicate correlation with dye-swaps:
> 
>  >corfit=duplicateCorrelation(MA, design=design, ndups=1, block=biolrep)
> 
> and the first problem is:
>  > corfit$consensus
> [1] 0.3926545
> 
> In limma manual it is written that correlation should be negative for 
> dye swaps- why is it positive?- is it a question of wrong model matrix 
> or is it something wrong with my samples?

As you note below, this is probably due to a dye-bias. Making some MA 
plots should help clarify the problem.

> 
> but
> 
> When I do simple hierarchical clustering of log-ratios:
>  >dist.matrix=dist(t(MA$M))
>  >hc=hclust(dist.matrix)
>  >par(mfrow=c(1,1)
>  >plot(hc)
> 
> The plot divides my arrays in two groups that exactly reflects dye 
> swaps. So maybe the model is correct?
> 
> I was thinking also about checking dye effect so I tried with such model:
> 
>  > design2=cbind(Dye=1, design)
>  > design2
>      Dye CdCl2 NaCl
> [1,]   1     0    1
> [2,]   1     0    1
> [3,]   1     0    1
> [4,]   1     1    0
> [5,]   1     1    0
> [6,]   1     1    0
> [7,]   1     0   -1
> [8,]   1     0   -1
> [9,]   1     0   -1
> [10,]   1    -1    0
> [11,]   1    -1    0
> [12,]   1    -1    0
> 
> I'm not sure if  I can use such model.
> if  I  use it:
> 
>  > corfit=duplicateCorrelation(MA, design=design2, ndups=1, block=blockrep)
>  > corfit$consensus
> [1] -0.04530506
> 
> The second problem is that each probe on my array is duplicated so in 
> the final top table I have each gene doubled- I read it is not possible 
> in Limma to analyse both technical duplicates and gene replicas on the 
> array. Could you give me any hint how to solve this problem?

Well, that isn't much correlation between the dye-swaps after 
controlling for the dye-bias, so you might check the correlation between 
the technical replicates. It might be more reasonable to ignore the fact 
that the dye-swaps are technical replicates and account for the 
intra-slide duplicate correlations instead.

The other possibility is to average the within-slide duplicates and 
account for the fact that you have technical replication at the dye-swap 
level. But you will have to look at your data to make that call.


Best,

Jim


> 
> I will be glad for any help in this cases
> 
> Best regards,
> 
> Michal Goralski, PhD student,
> Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, 
> Poland.
> 
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-- 
James W. MacDonald, M.S.
Biostatistician
Douglas Lab
University of Michigan
Department of Human Genetics
5912 Buhl
1241 E. Catherine St.
Ann Arbor MI 48109-5618
734-615-7826
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