systemPipeR: NGS workflow and report generation environment

In this 2016 paper published in BMC Bioinformatics, Backman and Girke discuss the R/Bioconductor package systemPipeR. Recognizing that the analysis of next-generation sequencing (NGS) data remains a significant challange, the authors turned to the R programming language and the Bioconductor environment to make workflows that were "time-efficient and reproducible." After giving some background and then discussing the development and implementation, they conclude that systemPipeR helps researchers "reduce the complexity and time required to translate NGS data into interpretable research results, while a built-in reporting feature improves reproducibility."

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