github.com - Nucleus is a library of Python and C++ code designed to make it easy to read, write and analyze data in common genomics file formats like SAM and VCF. In addition, Nucleus enables painless integration with the TensorFlow machine learning framework,...
github.com - Flanker, a Python package which performs alignment-free clustering of gene flanking sequences in a consistent format, allowing investigation of mobile genetic elements (MGEs) without prior knowledge of their structure. Flanker can be...
http://scikit-bio.org/ - scikit-bio is currently in beta. We are very actively developing it, and backward-incompatible interface changes can and will arise. To avoid these types of changes being a surprise to our users, our public APIs are decorated to make it clear...
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...
Biologists estimate that there are about 5 to 100 million species of organisms living on Earth today. Evidence from morphological, biochemical, and gene sequence data suggests that all organisms on Earth are genetically related, and the genealogical...
chagall.med.cornell.edu - Institute of computational biomedicine, Cornell University provide an NGS workshop tutorial at http://chagall.med.cornell.edu/NGScourse/
You can also add your favourite NGS educational material, or workshop tutorial by commenting on this...
genome.edu.au - RNA Seq
Basic Galaxy Tutorial
RNA-Seq tutorial based on Trapnell et al. (2012) Nature Protocols
In this tutorial we cover the concepts of RNA-Seq differential gene expression (DGE) analysis using a very small synthetic dataset from a well...
Part of the reason R has become so popular is the vast array of packages available at the cran and bioconductor repositories. In the last few years, the number of packages has grown exponentially!
This is a short post giving steps on how to...
www.r2d3.us - In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.
More at http://www.r2d3.us/visual-intro-to-machine-learning-part-1/