Figure 1.

The Myrna pipeline. (a) Reads are aligned to the genome using a parallel version of Bowtie. (b) Reads are aggregated into counts for each genomic feature - for example, for each gene in the annotation files. (c) For each sample a normalization constant is calculated based on a summary of the count distribution. (d) Statistical models are used to calculate differential expression in the R programming language parallelized across multiple processors. (e) Significance summaries such as P-values and gene-specific counts are calculated and returned. (f) Myrna also returns publication ready coverage plots for differentially expressed genes.