[BioC] down-expression and high-expression in single cell + amplification

[papori [guest]]

Hi all,
First of all, I am new to this field so i am sorry if i am not clear..
 
I will try to explain what is my aim, and what i did before DESeq.

I am trying to do Differential expression analysis using DESeq for De-Novo invertebrate .
 
We had an experiment of 3 conditions with 3 biological replicate for each.(total of 9 samples)
We used hiseq2000 50bp single end reads.
We had a different library size for each.(that was single cell experiment so we had amplification step.. what yield variance in the library sizes..)

We reconstructed the transcriptome using Trinity.
Estimating counts with RSEM.

And then i used DESeq..

i have weird behavior of the data, and i dont know if it is because something wrong that i did..

i am always getting down-expression from condition 1 to condition 2 and high-expression from condition 2 to condition 3.(for all the transcripts, no out-layers..)

The number of counts that got for each condition to reference transcriptome was:
32M, 27M, 40M respectively..
What made me to think that because cond 2 has lowest count it has a behavior of down-expression from 1 to 2 and high-expression from 2 to 3..

if my conclusion is right, i am in a big mass..(Normalization??)

my DESeq script is:
Conditions = c("C1", "C2", "C3", "C1", "C2", "C3","C1", "C2", "C3")
Counts<-round(MultiGeneMat,0)
cds <- newCountDataSet(Counts,Conditions)
cds <- estimateSizeFactors(cds)
cds <- estimateDispersions(cds,method="per-condition",sharingMode="maximum",fitType="local")

res_1vs2 <- nbinomTest(cds,condA="C1",condB="C2")
sigDESeq_1vs2 <- res_1vs2[res_1vs2$padj <= 0.1, ]
sigDESeq_1vs2 <- na.omit(sigDESeq_1vs2)

res_2vs3 <- nbinomTest(cds,condA="C2",condB="C3")
sigDESeq_2vs3 <- res_2vs3[res_2vs3$padj <= 0.1, ]
sigDESeq_2vs3 <- na.omit(sigDESeq_2vs3)

res_1vs3 <- nbinomTest(cds,condA="1",condB="C3")
sigDESeq_1vs3 <- res_1vs3[res_1vs3$padj <= 0.1, ]
sigDESeq_1vs3 <- na.omit(sigDESeq_1vs3)



Is there anything wrong here? or anywhere else??
If i wasnt clear enough so tell me in what and i will try to explain..
Any help will be appreciate here!
Thanks,
Pap













 -- output of sessionInfo(): 

R version 2.14.0 (2011-10-31)
Platform: x86_64-unknown-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8    LC_PAPER=C                 LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] edgeR_2.4.6    limma_3.10.3   DESeq_1.6.1    locfit_1.5-8   Biobase_2.14.0

loaded via a namespace (and not attached):
 [1] annotate_1.32.3       AnnotationDbi_1.16.19 DBI_0.2-5             genefilter_1.36.0     geneplotter_1.32.1   
 [6] grid_2.14.0           IRanges_1.12.6        lattice_0.20-6        RColorBrewer_1.0-5    RSQLite_0.11.1       
[11] splines_2.14.0        survival_2.36-14      tools_2.14.0          xtable_1.7-0         
> 


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