On the optimal trimming of high-throughput mRNA sequence data

The widespread and rapid adoption of high-throughput sequencing technologies has afforded researchers the opportunity to gain a deep understanding of genome level processes that underlie evolutionary change, and perhaps more importantly, the links between genotype and phenotype. In particular, researchers interested in functional biology and adaptation have used these technologies to sequence mRNA transcriptomes of specific tissues, which in turn are often compared to other tissues, or other individuals with different phenotypes. While these techniques are extremely powerful, careful attention to data quality is required. In particular, because high-throughput sequencing is more error-prone than traditional Sanger sequencing, quality trimming of sequence reads should be an important step in all data processing pipelines. While several software packages for quality trimming exist, no general guidelines for the specifics of trimming have been developed. Here, using empirically derived seq...