RNA-Seq analysis includes genome alignment or mapping, generation of gene and transcript counts, and quality assessment of data. Initial expression analysis includes evaluation of read fates to assess how many reads mapped within annotated gene or transcript regions, followed by generation of a list of differentially expressed genes between experimental groups of interested.

Standard analyses includes data preprocessing and differential gene expression analysis with statistical tests to evaluate significance, all using common open-source tools such as those within the Bioconductor suite of R libraries. Additional data mining, including gene clustering, heat map generation, WGCNA, GO and KEGG testing, and generation of publication-quality figures are available on a consultation basis.