Meta-analysis in R with multiple SNPs

Question

I'm conducting a meta-analysis on two genome wide association studies (GWAS), each consisting of 150 SNPs, for which I computed summary statistics for association. I'm using the R package meta and the function metagen. It seems to me that this function is able to combine studies but on single measurement effect (I have 150), one for each study.

For example, I may have 3 SNPs on each study

STUDY    SNP    OR    SE
GWAS_A  rs694739    0.6691  0.07588
GWAS_A  rs9858968   0.1091  0.01588
GWAS_A  rs1529267   0.9291  0.02588
GWAS_B  rs694739    0.6128  0.37344
GWAS_B  rs9858968   0.0332  0.27344
GWAS_B  rs1529267   0.3481  0.81284

so I would like an output in a table format (e.g., as in PLINK), with 3 rows and the corresponding pooling statistics. I know I could manage it with for loops or by grouping with the by function on the summary output of metagen, but I wonder whether there is another R package/function to easily accomplish this.

Answer 1

The MetABEL part of GenABEL does this. For 150 SNPs, you might find coding the loop yourself quicker than ensuring it's doing exactly what you want. (Neither should take very long)

Answer 2

A quicker option would be to use the built-in meta-analysis option from PLINK.

It is quite straightforward, and no additional coding is needed. You could then use the meta package from R to make forest plots of significant results. My experience with the meta package is that it isn't very practical when doing more than a few meta-analyses.