BOL: Related items

Picard

Neel — Fri, 29 Apr 2016 08:21:54 -0500

Picard is a set of command line tools for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF. These file formats are defined in the Hts-specs repository. See especially the SAM specification and the VCF specification.

Note that the information on this page is targeted at end-users. For developers, the source code, building instructions and implementation/development resources are available on GitHub.

The Picard toolkit is open-source under the MIT license and free for all uses.

Enjoy!

Address of the bookmark: http://broadinstitute.github.io/picard/

Andi

Jit — Fri, 13 May 2016 05:16:35 -0500

This is the andi program for estimating the evolutionary distance between closely related genomes. These distances can be used to rapidly infer phylogenies for big sets of genomes. Because andi does not compute full alignments, it is so efficient that it scales even up to thousands of bacterial genomes.

This readme covers all necessary instructions for the impatient to get andi up and running. For extensive instructions please consult the manual.

More at https://github.com/evolbioinf/andi/

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full

Bpipe - a tool for running and managing bioinformatics pipelines

Radha Agarkar — Sat, 21 May 2016 22:42:16 -0500

Bpipe provides a platform for running big bioinformatics jobs that consist of a series of processing stages - known as 'pipelines'.

January 20th, 2016 - New! Bpipe 0.9.9 released!
Download latest, all
Documentation
Mailing List (Google Group)

Bpipe has been published in Bioinformatics! If you use Bpipe, please cite:

Sadedin S, Pope B & Oshlack A, Bpipe: A Tool for Running and Managing Bioinformatics Pipelines, Bioinformatics

Address of the bookmark: http://docs.bpipe.org/

CovCal: Coverage / Read Count Calculator

Jit — Wed, 15 Jun 2016 18:08:13 -0500

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 Turner, based on the Lander-Waterman formula, inspired by a similar calculator written by James Hadfield. Coverage is calculated as C=LN/G and reads as N=CG/L where C = Coverage (X),L = Read length (bp), G = Haploid genome size (bp), and N = Number of reads. Source code on GitHub.

Address of the bookmark: http://apps.bioconnector.virginia.edu/covcalc/

HivePlot

Jit — Thu, 16 Feb 2017 11:39:34 -0600

The hive plot is a rational visualization method for drawing networks. Nodes are mapped to and positioned on radially distributed linear axes — this mapping is based on network structural properties. Edges are drawn as curved links. Simple and interpretable.

The purpose of the hive plot is to establish a new baseline for visualization of large networks — a method that is both general and tunable and useful as a starting point in visually exploring network structure.

More at http://www.hiveplot.com/

Address of the bookmark: http://www.hiveplot.com/

SVfinder: Tool for detecting genomic rearrangement form DNA-seq data

Robert M Willioms — Thu, 14 Dec 2017 15:51:40 -0600

SVfinder provides genome-wide detection of structural variants from next generation paired-end sequencing reads.

Address of the bookmark: https://github.com/cauyrd/SVfinder

CViT: Chromosome Viewing Tool

Rahul Nayak — Wed, 02 Jan 2019 04:10:09 -0600

CViT - Chromosome Viewing Tool. A collection of Perl scripts that enable quick visualizations of features on linkage groups, psuedochromosomes or cytogenetic maps. Intended for whole-genome views of data but can be used to create images of single chromosomes/linkage groups, contigs, or BACs, or even proteins -- any feature that has a location on a backbone. Handles most standard genetic/genomic coordinate systems. Reads GFF3 data and produces a PNG or SVG image.

https://www.hindawi.com/journals/ijpg/2011/373875/

Address of the bookmark: https://sourceforge.net/projects/cvit/

R Package for PCA Analysis

LEGE — Sun, 24 Mar 2024 20:06:24 -0500

An R package for performing principal component analysis (PCA) of genomics data. The package performs PCA, generates the publication-ready plots, and identifies population-specific outlier individuals. The package can be accessed on GitHub: https://github.com/Devashish13/PopulationStructure

Address of the bookmark: https://rpubs.com/Devashish13/PCAGenomics

From DNA Chaos to a Clear Microbial Story

BioStar — Fri, 21 Aug 2026 11:22:54 -0500

Imagine opening a metagenomic dataset and finding millions of DNA fragments, each carrying a tiny piece of information about the microbial world inside a sample. The challenge is not generating the data — it is turning that data into a meaningful story.

This is where MeTAline comes in.

MeTAline is a reproducible workflow designed to simplify shotgun metagenomic analysis. It brings together important steps such as quality control, host-DNA removal, taxonomic profiling and functional analysis, using tools including Kraken2, MetaPhlAn4 and HUMAnN.

What makes it especially useful is its ability to handle large datasets while keeping analyses organized and reproducible. Built with Snakemake and supporting containerized environments, MeTAline can also be used on high-performance computing systems.

In simple terms, MeTAline helps researchers move from millions of confusing DNA fragments to a clearer picture of who is there, what they might be doing, and what the data could mean.

Sometimes, the biggest challenge in science isn't collecting more data — it's finding the story hidden inside it.

Read more at https://academic.oup.com/nargab/article/7/4/lqaf158/8340158?login=false

DAVI: Deep learning-based tool for alignment and single nucleotide variant identification

Jit — Tue, 16 Mar 2021 05:41:33 -0500

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 used for bench-marking. We further demonstrate that while existing tools are based on data generated from a specific sequencing technology, the models proposed in DAVI are generic and can be used across different NGS technologies as well as across different species

https://iopscience.iop.org/article/10.1088/2632-2153/ab7e19/pdf

Address of the bookmark: https://github.com/gguptaiitd/NEAT