[BioC] Please comment the way I'm thinking about the way to find differentially expressed genes

[Kaj Chokeshaiusaha [guest]]

Dear R helpers,

I'm a starter in gene expression analysis, and I must apologize everyone in the first place if I'm posting something irritated. My attemp is just to figure out an alternative way to find out differentailly expressed genes in low replicated datasets.

In case that, I have very few number of replicated datasets per group (2-3 replicates per group). I'm wondering whether I can generate several datasets from my original datasets I have (using methods like Bootstrap) and then perform the test to find out the lists of differentially expressed genes from my created datasets. After that I count the repeated genes from all lists and pick the top ones as differentially expressed genes.

Please comment the idea, I don't want to slip too far in the wrong approach.

With Respects,
Kaj


 -- output of sessionInfo(): 

R version 3.1.0 (2014-04-10)
Platform: x86_64-pc-linux-gnu (64-bit)

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

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

other attached packages:
[1] CMA_1.22.0          Biobase_2.24.0      BiocGenerics_0.10.0
[4] e1071_1.6-3        

loaded via a namespace (and not attached):
[1] class_7.3-10 tools_3.1.0

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