Q: Can I use the packages to combine other types of genomic studies except for microarray gene expression studies (e.g. methylation studies or GWAS)? What about next-generation sequencing data?

A: In majority of papers, we aim for combining multiple microarray gene expression studies when we develop the methods. To apply to other types of genomic studies, the major statistical concepts are the same but some extra extension and coding may be necessary. For example, Bhattacharjee et al. (2012) and Han and Eskin (2012) extended our adaptively weighted approach to GWAS meta-analysis with frequentist and Bayesian flavors of random and fixed effects models separately. We have applied our methods in methylation and eQTL meta-analysis. For NGS data, preprocessing of data will be needed and utilize our packages. For example, one can generate RPKM values in RNA-seq data and use them as input in all packages (i.e. simply treat RPKM values like normalized intensities from microarray). Or alternatively, “CuffDiff” or other differential analysis packages for RNA-seq can be used to generate p-values and use the p-values as input in the MetaDE package.

Q: How do I cite the software?

A: : In general, please cite our software paper below. This paper introduced the MetaQC, MetaDE and MetaPath packages. If you use a specific package or method, please refer to the “Methods” section to cite individual paper(s).

Xingbin Wang, Dongwan Kang, Kui Shen, Chi Song, Shuya Lu, Lunching Chang, Serena G. Liao, Zhiguang Huo, Naftali Kaminski, Etienne Sibille, Yan Lin, Jia Li* and George C. Tseng*. (2012) A Suite of R Packages for Quality Control, Differentially Expressed Gene and Enriched Pathway Detection in Microarray Meta-analysis. Bioinformatics. 28:2534-2536.