Question: Meta-Analysis after running limma on a normalized dataset
0
3.7 years ago by
Vani20
United States
Vani20 wrote:

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

limma toptable meta-analysis • 1.1k views
modified 3.7 years ago by Aaron Lun23k • written 3.7 years ago by Vani20

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).

Answer: Meta-Analysis after running limma on a normalized dataset
2
3.7 years ago by
Aaron Lun23k
Cambridge, United Kingdom
Aaron Lun23k wrote:

I don't think that there are any functions in limma for constructing forest plots. You'll have to use some other packages; a quick Google search brings up forestplot and rmeta. With the former, it seems like you can make a forest plot for each gene, by supplying the log-FC with the upper and lower bound for the confidence interval. Make sure you've matched up the genes properly between data sets, though.

Hi,

Before I create a forest plot I want to run a fixed and random effect meta-analysis process across all the 4 datasets. I couldn't find a way to do this on rmeta? Do you have any advice in this regard?