BOL

github.com - Convenient conversions between genome assemblie. The liftover package makes it easy to remap genomic coordinates to a different genome assembly. More at...

catchenlab.life.illinois.edu - Stacks is a software pipeline for building loci from short-read sequences, such as those generated on the Illumina platform. Stacks was developed to work with restriction enzyme-based data, such as RAD-seq, for the purpose of building genetic maps...

scikit-learn.org - Machine Learning in Python Simple and efficient tools for data mining and data analysis Accessible to everybody, and reusable in various contexts Built on NumPy, SciPy, and matplotlib Open source, commercially usable - BSD license More...

github.com - CSBB is a command line based bioinformatics suite to analyze biological data acquired through varied avenues of biological experiments. CSBB is implemented in Perl, while it also leverages the use of R and python in background for specific modules....

engr.case.edu - In this report we provide an overview of known techniques for discovery of patterns of biological sequences (DNA and proteins). We also provide biological motivation, and methods of biological verification of such patterns. Finally we list publicly...

github.com - maftools - An R package to summarize, analyze and visualize MAF files. Introduction. With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widley accepted and used to store variants detected. The Cancer Genome Atlas Project...

Structural variation caller tools using long reads

The IBL laboratory focuses on the multi-disciplinary analyses of the global responses of model microorganisms, cyanobacteria (mainly Synechocystis PCC6803) and yeasts (mainly Saccharomyces cerevisae) to environmental stresses triggered by oxidative...

samtools.sourceforge.net - In current genome era, our day to day work is to handle the huge geneome sequences, expression data, several other datasets. This link provide a comprehensive list of commonly used sofware/tools.

Basics of computational proteomics