bioconda.github.io - Snakemake is a workflow engine that provides a readable Python-based workflow definition language and a powerful execution environment that scales from single-core workstations to compute clusters without modifying the workflow.
carpentries-incubator.github.io - A lesson introducing the Snakemake workflow system for bioinformatics analysis.
Prerequisites
This is an intermediate lesson and assumes learners have already done some bioinformatics:
Familiarity with the BASH command shell, including...
Integrated solutions * CLCbio Genomics Workbench - de novo and reference assembly of Sanger, Roche FLX, Illumina, Helicos, and SOLiD data. Commercial next-gen-seq software that extends the CLCbio Main Workbench software. Includes SNP detection,...
github.com - Heap, that enables robustly sensitive and accurate calling of SNPs, particularly with a low coverage NGS data, which must be aligned to the reference genome sequences in advance. To reduce false positive SNPs, Heap determines genotypes and calls...
github.com - RAINBOWR(Reliable Association INference By Optimizing Weights with R) is a package to perform several types of GWAS as follows.
Single-SNP GWAS with RGWAS.normal function
SNP-set (or gene set) GWAS with RGWAS.multisnp function (which tests...
github.com - DAVI consists of models for both global and local alignment and for variant calling. We have evaluated the performance of DAVI against existing state-of-the-art tool sets and found that its accuracy and performance is comparable to existing tools...
training.galaxyproject.org - The main challenge associated with non-diploid variant calling is the difficulty in distinguishing between the sequencing noise (abundant in all NGS platforms) and true low frequency variants. Some of the early attempts to do this well have been...
cosmos.hms.harvard.edu - COSMOS, our Python-based management system for implementing large-scale parallel workflows focusing on, but not restricted to, large-scale short-read "NGS" sequencing data is open-access published via Advance Access in Bioinformatics (Gafni et al....