milkweedgenome.org - Some of the useful bioinformatics scripts.
For example ... contig-stats.pl is a Perl script that will automatically describe features of a sequence assembly.
http://milkweedgenome.org/?q=scripts
readthedocs.org - Bipype is a very useful program, which prepare a lot of types of bioinformatics analyses. There are three input options: amplicons, WGS (whole genome sequences) and metatranscriptomic data. If amplicons are input data, then bipype does...
github.com - Turn (almost) any Python command line program into a full GUI application with one line
The easiest way to install Gooey is via pip
pip install Gooey
Alternatively, you can install Gooey by cloning the project to your local directory
git...
github.com - Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.
https://github.com/tanghaibao/jcvi
More at https://github.com/tanghaibao/jcvi/wiki
github.com - evolverSimControl (eSC) can be used to simulate multi-chromosome genome evolution on an arbitrary phylogeny (Newick format). In addition to simply running evolver, eSC also automatically creates statistical summaries of the simulation...
https://seq-lang.org -
Seq is a programming language for computational genomics and bioinformatics. With a Python-compatible syntax and a host of domain-specific features and optimizations, Seq makes writing high-performance genomics software as easy as writing...
github.com - MitoHiFi v3.2 is a python pipeline distributed under MIT License !
MitoHiFi was first developed to assemble the mitogenomes for a wide range of species in the Darwin Tree of Life Project...
deltarho.org - Trelliscope provides a way to flexibly visualize large, complex data in great detail from within the R statistical programming environment. Trelliscope is a component in the DeltaRho environment.
For those familiar with Trellis...
In an attempt to find a good Linux reference for bioinformatician and BOL readers, I was unsuccessful at finding a decent one on the Internet. So, we decided to make a cheat sheet for biological programmers.