BOL

github.com - Second generation sequencing technologies paved the way to an exceptional increase in the number of sequenced genomes, both prokaryotic and eukaryotic. However, short reads are difficult to assemble and often lead to highly fragmented assemblies....

apps.bioconnector.virginia.edu - Coverage / Read Count Calculator Calculate how much sequencing you need to hit a target depth of coverage (or vice versa). Instructions: set the read length/configuration and genome size, then select what you want to calculate. Written by Stephen...

github.com - NextSV, a meta SV caller and a computational pipeline to perform SV calling from low coverage long-read sequencing data. NextSV integrates three aligners and three SV callers and generates two integrated call sets (sensitive/stringent) for different...

code.google.com - d2Tools are the toolbox for counting the frequency of K-tuple from sequencing datasets and then calculating the pairwise dissimilarity matrix between samples with the d2-style(d2/d2*/d2S representing d2/d2Star/d2shepp, respectively)...

github.com - Required python modules biopython intervaltree numpy scipy tqdm PyYAML

github.com - Run a pipeline processing fast5s to a consensus in a single command. Recommended fixed "standard" and "fast" pipelines. Interchange basecaller, assembler, and consensus components of the pipelines simply by changing the target filepath. Seemless...

github.com - MitoZ is a Python3-based toolkit which aims to automatically filter pair-end raw data (fastq files), assemble genome, search for mitogenome sequences from the genome assembly result, annotate mitogenome (genbank file as result), and mitogenome...

github.com - an integrated bioinformatics pipeline for the detection of TE insertions in whole-genome shotgun data, called McClintock (https://github.com/bergmanlab/mcclintock), which automatically runs and standardizes output for multiple TE detection methods....

GATB Library. The Genome Analysis Toolbox with de-Bruijn graph. A large part of tools developed by the GenScale team are based on this library.These methods enable the analysis of data sets of any size on multi-core desktop...

github.com - Motivation: Identification of biological specimens is a major requirement for a range of applications. Reference-free methods analyse unprocessed sequencing data without relying on prior knowledge, but these do not scale to arbitrarily large genomes...