BOL

github.com - This repository contains the scripts and pipeline that reproduces the results of the HCMV benchmarking study. In this study we evaluated genome assemblers and variant callers on 10 in vitro generated, mixed strain HCMV sequence samples, each...

The goal of our research is to better understand the biology of microbial organisms of significant ecological, veterinary and medical importance. To achieve this goal, our team combines the power of next generation DNA sequencing and...

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...

github.com - LAMSA (Long Approximate Matches-based Split Aligner) is a novel split alignment approach with faster speed and good ability of handling SV events. It is well-suited to align long reads (over thousands of base-pairs). LAMSA takes takes the...

github.com - rHAT is a seed-and-extension-based noisy long read alignment tool. It is suitable for aligning 3rd generation sequencing reads which are in large read length with relatively high error rate, especially Pacbio's Single Molecule Read-time (SMRT)...

github.com - URMAP, a new read mapping algorithm. URMAP is an order of magnitude faster than BWA with comparable accuracy on several validation tests. On a Genome in a Bottle (GIAB) variant calling test with 30× coverage 2×150 reads, URMAP achieves...