github.com - Sibelia: A comparative genomics tool: It assists biologists in analysing the genomic variations that correlate with pathogens, or the genomic changes that help microorganisms adapt in different environments. Sibelia will also be helpful for the...
github.com - The algorithm presented herein, Mining Algorithm for GenetIc Controllers (MAGIC), uses ENCODE ChIP-seq data to look for statistical enrichment of TFs and cofactors in gene bodies and flanking regions in gene lists without...
https://js.cgview.ca/ - CGView.js is a Circular Genome Viewing tool for visualizing and interacting with small genomes. This software is an adaptation of the Java program CGView.
CGView.js is the genome viewer of Proksee, an expert system for genome...
downloads.jbei.org - MaxBin is software for binning assembled metagenomic sequences based on an Expectation-Maximization algorithm. Users can understand the underlying bins (genomes) of the microbes in their metagenomes by simply providing assembled metagenomic...
licheng/gccfilter - gccfilter is a perl filter to colorize and simplify (or expand) gcc diagnostic messages. gccfilter is particularly aimed at g++ (i.e. dealinging with C++) messages which can contain lot of template-related errors or warnings...
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 - 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...
github.com - Long Read Correction and other Correction tools
This package is a loose collection of scripts. To run the correctionroutine see the section below. Descriptions of the other scriptsare at the bottom of this file.
Contact: gurtowsk@cshl.edu
In...
www.exelixis-lab.org - PEAR is an ultrafast, memory-efficient and highly accurate pair-end read merger. It is fully parallelized and can run with as low as just a few kilobytes of memory.
PEAR evaluates all possible paired-end read overlaps and without requiring the...