[BioC] EdgeR: replicated pools, yes or not?

Ryan rct at thompsonclan.org
Wed Apr 23 19:06:24 CEST 2014

Don't pool. You are throwing away information. If you're going to do 24 
animals, you may as well use 24 barcodes. To see that a separate 
barcode for each animal provides strictly more information than 
pooling, note that once you have used separate barcodes, you could add 
the counts together to do in silico pooling and get the same result as 
if you had done pooling in vitro. In other words, you can get from 
separate barcodes to pooling by throwing away information.

For a literature reference, try "Efficient experimental design and 
analysis strategies for the detection of differential expression using 
RNA-Sequencing." http://www.ncbi.nlm.nih.gov/pubmed/22985019

That publication doesn't directly address the issue of pooling multiple 
biological samples in the same barcode, but it does make clear that 
more biological replication results in a drastic improvement in 
results. You could simulate your described pooling scheme yourself: 
simply simulate 24 libraries in 2 groups with some number of true 
differentially expressed genes between them. Then pool them 3 at a time 
(by adding their counts together) to get the pooled dataset of 8 pooled 
libraries in 2 groups. Then perform the analysis on both datasets using 
your preferred tool and compute the ROC curve. I think you will find 
that pooling significantly diminishes your power to detect differential 

-Ryan Thompson

On Wed Apr 23 09:42:15 2014, "Manuel J Gómez [guest]"   wrote:
> Hello,
> I would like to ask for your opinion on whether using replicated pools in the context of RNASeq experiments makes sense, or not.
> Lets say that we are interested in detecting genes that are differentially expressed in two genetic backgrounds (a certain KO mutant strain and the corresponding WT), in mouse liver.
> We could perform an RNASeq experiment using liver tissue from four KO and four WT with the same sex, age, and diet.
> We would have eight samples: four biological replicates for each of the two conditions to be compared.
> However, we decide to pool liver tissue from three animals, to prepare each of the eight samples (we would use, therefore 24 animals: 12 KO animals pooled to produce four KO samples, and 12 WT animals pooled to produce four WT samples).
> We would do it following the argument that pooling samples to build biological replicates reduces variation between replicates and increases the statistical power of the analysis, resulting in a more sensitive detection of genes that are differentially expressed between conditions.
> However, EdgeR relies, precisely, on measuring biological variability to establish the statistical significance of differences in gene expression across conditions. Therefore, pooling samples to buid biological replicates is not correct and we are, in fact, losing statistical power. We are unable of determining whether the observed differences in gene expression are significative or not.
> There are some publications dealing with this issue in the context of microarrays (for example, Kendziorski et al, 2005, "On the utility of pooling biological samples in microarray experiments", PNAS, 102:4252) but I have not found anything similar in the context of RNASeq and, more specifically, of the analysis of RNASeq data with EdgeR.
> Any comment will be more than welcome, as well as any relevant references.
> Thanks a lot in advance.
>   -- output of sessionInfo():
> NA
> --
> Sent via the guest posting facility at bioconductor.org.
> _______________________________________________
> 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

More information about the Bioconductor mailing list