[BioC] edgeR - technical and biological replication

[Kasper Daniel Hansen]

Hi Jacob

Technical replicates exists on many levels.  My guess from your
description is that the technical replicates you have is the same
library prep injected into different lanes of the same (or different
flowcells).  It has been well established that technical replication
at this level is close to poisson and that the lane and flowcell
effect is pretty minor (See for example Bullard et al (2010) BMC
Bioinformatics).  So you will not loose much by aggregating and you
will certainly gain a lot in reduced complexity.  It is hard enough to
suitably account for biological variation that I would start with
that.  And I would also recommend you to have a look at DESeq as well
(which currently only does two group comparisons).

Indeed, one can argue that the use of several lanes is not so much a
matter of replication, but rather a consequence of aiming for greater
sequencing depth.

Things might be different if you have separate library preps.

Kasper

On Mon, Apr 26, 2010 at 9:32 AM, Jakob Hedegaard
<Jakob.Hedegaard at agrsci.dk> wrote:
> Hi,
> I have a RNA-Seq dataset produced on a Illumina GA and wonder how to account for both technical and biological replication using edgeR.
> The dataset consist of 48 individual samples (time series with 4-6 biological replica per time point, 9 time points in total) which have been sequenced in three GA runs (3 technical replica) using 12-plex sequencing (4 lanes/run) - that is a total of 144 profiles representing 3 technical replica and 4-6 biological replica.
> Simply adding the counts from the 3 tech rep forming 48 profiles would be a start point, but it would be more powerful to include the tech rep in the analysis as well...
>
> Best regards,
> Jakob
>
>
> ###############################
> R version 2.11.0 (2010-04-22)
> x86_64-pc-mingw32
>
> locale:
> [1] LC_COLLATE=Danish_Denmark.1252  LC_CTYPE=Danish_Denmark.1252    LC_MONETARY=Danish_Denmark.1252 LC_NUMERIC=C
> [5] LC_TIME=Danish_Denmark.1252
>
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base
>
> other attached packages:
> [1] edgeR_1.6.0
>
> loaded via a namespace (and not attached):
> [1] limma_3.4.0  tools_2.11.0
>
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