BOL: Related items

pipesnake: bioinformatics best-practice analysis pipeline for phylogenomic reconstruction

LEGE — Wed, 21 Feb 2024 06:19:41 -0600

ausarg/pipesnake is a bioinformatics best-practice analysis pipeline for phylogenomic reconstruction starting from short-read 'second-generation' sequencing data.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.

Address of the bookmark: https://github.com/AusARG/pipesnake

NanoPack: visualizing and processing long-read sequencing data

Jit — Tue, 25 Dec 2018 21:20:50 -0600

The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.

Address of the bookmark: https://github.com/wdecoster/nanopack

Parliament2: Runs a combination of tools to generate structural variant calls on whole-genome sequencing data

Jit — Thu, 28 May 2020 21:57:03 -0500

Parliament2 identifies structural variants in a given sample relative to a reference genome. These structural variants cover large deletion events that are called as Deletions of a region, Insertions of a sequence into a region, Duplications of a region, Inversions of a region, or Translocations between two regions in the genome.

Parliament2 runs a combination of tools to generate structural variant calls on whole-genome sequencing data. It can run the following callers: Breakdancer, Breakseq2, CNVnator, Delly2, Manta, and Lumpy. Because of synergies in how the programs use computational resources, these are all run in parallel. Parliament2 will produce the outputs of each of the tools for subsequent investigation.

Address of the bookmark: https://github.com/dnanexus/parliament2

Ktrim: an extra-fast and accurate adapter- and quality-trimmer for sequencing data

Jit — Thu, 11 Feb 2021 21:39:05 -0600

Ktrim is written in C++ for GNU Linux/Unix platforms. After uncompressing the source package, you can find an executable file ktrim under bin/ directory compiled using g++ v4.8.5 and linked with libz v1.2.7 for Linux x86_64 system. If you could not run it (which is usually caused by low version of libc++ or libz library) or you want to build a version optimized for your system, you can re-compile the programs:

user@linux$ make clean && make

Address of the bookmark: https://github.com/hellosunking/Ktrim

lordFAST: sensitive and Fast Alignment Search Tool for LOng noisy Read sequencing Data

BioJoker — Tue, 27 Nov 2018 04:43:57 -0600

lordFAST is a sensitive tool for mapping long reads with high error rates. lordFAST is specially designed for aligning reads from PacBio sequencing technology but provides the user the ability to change alignment parameters depending on the reads and application.

lordFAST, a novel long-read mapper that is specifically designed to align reads generated by PacBio and potentially other SMS technologies to a reference. lordFAST not only has higher sensitivity than the available alternatives, it is also among the fastest and has a very low memory footprint.

Address of the bookmark: https://github.com/vpc-ccg/lordfast

Is reference genome necessary for gene expression study in transcriptome sequencing or for variant discovery in genome sequencing?

Rahul Agarwal — Wed, 17 Jul 2013 15:25:09 -0500

Like in case of plant genomes where nature of genome is too complex and huge in size to accomplish complete de novo assembly by current sequencing technology. What would be alternate solution? Can we live in reference free world?

FastProNGS: fast preprocessing of next-generation sequencing reads

Rahul Nayak — Sat, 26 Dec 2020 08:35:21 -0600

FastProNGS to integrate the quality control process with automatic adapter removal. Parallel processing was implemented to speed up the process by allocating multiple threads. Compared with similar up-to-date preprocessing tools, FastProNGS is by far the fastest.

Address of the bookmark: https://github.com/Megagenomics/FastProNGS

TEannot

Jit — Thu, 18 Aug 2016 10:02:03 -0500

We advise to run first the TEdenovo pipeline but it is not compulsory. We suppose you begin by running the TEannot pipeline on the example provided in the directory "db/" rather than directly on your own genomic sequences. Thus, from now on, the project name is "DmelChr4".

Address of the bookmark: https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto

NAViGaTOR: Network Analysis, Visualization and Graphing Toronto

Rahul Nayak — Tue, 03 Jul 2018 05:05:55 -0500

NAViGaTOR – Network Analysis, Visualization, & Graphing TORonto is a software system for scaleable visualizing and analyzing networks. The current version, NAViGaTOR 3, increases modularity, improves scaleability, extends input/output options, brings new network views and analysis algorithms. http://142.150.188.236/navigatorwp/

Address of the bookmark: http://142.150.188.236/navigatorwp/

SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis

BioStar — Mon, 17 Aug 2020 05:21:09 -0500

SHAMAN is a shiny application for differential analysis of metagenomic data (16S, 18S, 23S, 28S, ITS and WGS) including bioinformatics treatment of raw reads for targeted metagenomics, statistical analysis and results visualization with a large variety of plots (barplot, boxplot, heatmap, …).
The bioinformatics treatment is based on Vsearch [Rognes 2016] which showed to be both accurate and fast [Wescott 2015].The statistical analysis is based on DESeq2 R package [Anders and Huber 2010] which robustly identifies the differential abundant features as suggested in [McMurdie and Holmes 2014] and [Jonsson2016]. SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2 [Love 2014].
SHAMAN is compatible with standard formats for metagenomic analysis (.csv, .tsv, .biom) and figures can be downloaded in several formats. A presentation about SHAMAN is available here and a poster here.

More at https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4

Address of the bookmark: https://github.com/aghozlane/shaman