=== Another milestone for biology ports Links: + link:https://github.com/auerlab/biolibc-tools[Biolibc-tools] URL: link:https://github.com/auerlab/biolibc-tools[https://github.com/auerlab/biolibc-tools] + link:https://github.com/auerlab/fasda[Fast And Simple Differential Analysis] URL: link:https://github.com/auerlab/fasda[https://github.com/auerlab/fasda] Contact: Jason Bacon The biology category in ports continues to grow and mature, and reached another milestone in 2022q4 with the introduction of the rna-seq metaport. The fields of genomics, and more generally, bioinformatics, are often referred to as the "wild west" of computational science. Analyses are typically mired by a lack of clear documentation, and difficulties deploying and using software. Many scientific software developers do not understand the potential of package managers to simplify their lives and the lives of their users. As a result, much scientific software is deployed using ad hoc "caveman" installations involving overly complicated and unreliable build systems that either bundle dependencies or attempt to work with random installations thereof. Work has been ongoing to make FreeBSD ports a model of how easy scientific software deployment should be. It now contains a solid core of many of the most commonly used open source applications in biological research. This quarter saw the completion of a tool chain for one of the most important types of analysis, known as RNA-Seq. RNA-Seq measures the abundance of RNA, and hence gene activity, in tissue samples. All of the tools needed to perform a typical RNA-Seq analysis can now be installed on FreeBSD using: `pkg install rna-seq` This includes many mature existing tools as well as new tools developed on FreeBSD, such as FASDA and biolibc-tools, easy-to-use replacements for some of the more troublesome tools traditionally used in an RNA-Seq pipeline. Software deployments for RNA-Seq that traditionally have taken weeks or longer can now be performed on FreeBSD in a few minutes with a single command. Scientists can spend their time doing science rather than struggling with IT issues.