Hi,
I am trying to run a meta-analysis on multiple datasets. After the normalization was completed I applied, limma's lmfit,ebayes, and toptable on the datasets. I would like to use the data produced by toptable to do a meta-analysis on the datasets.
This is the header of my top tables:
[1] "ENTREZID" "SYMBOL" "GENENAME" "logFC" "CI.L" "CI.R"
[7] "AveExpr" "t" "P.Value" "adj.P.Val" "B"
After performing a meta-analysis I would also like to do a forest plot on the result.
What would be the best way to do this?
Thanks
I am not sure if it makes sense to do traditional meta-analysis on gene expression data. What I have found is that using packages such as RankProd works pretty well. You would take the directional t-statistics from limma, make a table out of them and then do one-sample RankProd analysis (or Ranksum if you like). Maybe you can do the forest plot afterwards on the few remaining genes. RankProd can deal with missing values (or you could do imputation also).