whataBamBam Member

Location: Italy

Join Date: May 2013 Posts: 27

Quote: Michael Love Originally Posted by

http://genomebiology.com/2010/11/10/r106



"Working without replicates

DESeq allows analysis of experiments with no biological replicates in one or even both of the conditions. While one may not want to draw strong conclusions from such an analysis, it may still be useful for exploration and hypothesis generation. If replicates are available only for one of the conditions, one might choose to assume that the variance-mean dependence estimated from the data for that condition holds as well for the unreplicated one. If neither condition has replicates, one can still perform an analysis based on the assumption that for most genes, there is no true differential expression, and that a valid mean-variance relationship can be estimated from treating the two samples as if they were replicates. A minority of differentially abundant genes will act as outliers; however, they will not have a severe impact on the gamma-family GLM fit, as the gamma distribution for low values of the shape parameter has a heavy right-hand tail. Some overestimation of the variance may be expected, which will make that approach conservative." The section of the original DESeq paper might shed some light:"Working without replicatesDESeq allows analysis of experiments with no biological replicates in one or even both of the conditions. While one may not want to draw strong conclusions from such an analysis, it may still be useful for exploration and hypothesis generation. If replicates are available only for one of the conditions, one might choose to assume that the variance-mean dependence estimated from the data for that condition holds as well for the unreplicated one. If neither condition has replicates, one can still perform an analysis based on the assumption that for most genes, there is no true differential expression, and that a valid mean-variance relationship can be estimated from treating the two samples as if they were replicates. A minority of differentially abundant genes will act as outliers; however, they will not have a severe impact on the gamma-family GLM fit, as the gamma distribution for low values of the shape parameter has a heavy right-hand tail. Some overestimation of the variance may be expected, which will make that approach conservative."



So basically you are saying that you have less statistical power because you have overestimated the variance. And if you see significant differences DESPITE this low statistical power then go for it.



To be fair it says in the vignette (or the paper I can't remember which) that there is simply low statistical power if you have no replicates. Great. Actually my original interpretation (before I posted this) was correct then. That the p values are perfectly valid (in fact conservative) and the problem of no replicates is actually low statistical power.So basically you are saying that you have less statistical power because you have overestimated the variance. And if you see significant differences DESPITE this low statistical power then go for it.To be fair it says in the vignette (or the paper I can't remember which) that there is simply low statistical power if you have no replicates.