Question: Meta-Analysis after running limma on a normalized dataset
0
gravatar for Vani
4.3 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 • 1.2k views
ADD COMMENTlink modified 4.3 years ago by Aaron Lun25k • written 4.3 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). 

ADD REPLYlink written 2.8 years ago by Pekka Kohonen190
Answer: Meta-Analysis after running limma on a normalized dataset
2
gravatar for Aaron Lun
4.3 years ago by
Aaron Lun25k
Cambridge, United Kingdom
Aaron Lun25k 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.

ADD COMMENTlink written 4.3 years ago by Aaron Lun25k

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?

 

 

 

ADD REPLYlink written 4.3 years ago by Vani20

Look into the meta and the metafor packages for this. The metafor package has an extended website which might be more informative for a quick overview of what type of functionality it might provide you

ADD REPLYlink written 4.3 years ago by Steve Lianoglou12k
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 16.09
Traffic: 200 users visited in the last hour