BOL: Related items

MOSAIK: A Hash-Based Algorithm for Accurate Next-Generation Sequencing Short-Read Mapping

Neel — Fri, 20 May 2016 18:53:49 -0500

MOSAIK is a stable, sensitive and open-source program for mapping second and third-generation sequencing reads to a reference genome. Uniquely among current mapping tools, MOSAIK can align reads generated by all the major sequencing technologies, including Illumina, Applied Biosystems SOLiD, Roche 454, Ion Torrent and Pacific BioSciences SMRT. Indeed, MOSAIK was the only aligner to provide consistent mappings for all the generated data (sequencing technologies, low-coverage and exome) in the 1000 Genomes Project. To provide highly accurate alignments, MOSAIK employs a hash clustering strategy coupled with the Smith-Waterman algorithm. This method is well-suited to capture mismatches as well as short insertions and deletions. To support the growing interest in larger structural variant (SV) discovery, MOSAIK provides explicit support for handling known-sequence SVs, e.g. mobile element insertions (MEIs) as well as generating outputs tailored to aid in SV discovery.

Address of the bookmark: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0090581

GAEMR

Jit — Tue, 14 Jun 2016 06:18:37 -0500

The Genome Assembly Evaluation Metrics and Reporting (GAEMR) package is an assembly analysis framework composed a number of integrated modules. These modules can be executed as a single program to generate a complete analysis report, or executed individually to generate specific charts and tables. GAEMR standardizes input by converting a variety of read types to Binary Alignment Map (BAM) format, allowing a single input format to be entered into GAEMR’s analysis pipeline, hence enabling the generation of standard reports.

GAEMR’s analysis philosophy is centered on contiguity, correctness, and completeness -- how many pieces in an assembly composed of, how well those pieces accurately represent the genome sequenced, and how much of that genome is represented by those pieces. By performing over twenty different analyses based on these principles, GAEMR gives a clear picture of the condition of a genome assembly.

Address of the bookmark: https://www.broadinstitute.org/software/gaemr/

Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm)

Abhimanyu Singh — Thu, 29 Dec 2016 03:26:45 -0600

Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene finding program developed at Oak Ridge National Laboratory and the University of Tennessee. Key features of Prodigal include:

Speed: Prodigal is an extremely fast gene recognition tool (written in very vanilla C). It can analyze an entire microbial genome in 30 seconds or less.
Accuracy: Prodigal is a highly accurate gene finder. It correctly locates the 3' end of every gene in the experimentally verified Ecogene data set (except those containing introns). It possesses a very sophisticated ribosomal binding site scoring system that enables it to locate the translation initiation site with great accuracy (96% of the 5' ends in the Ecogene data set are located correctly).
Specificity: Prodigal's false positive rate compares favorably with other gene identification programs, and usually falls under 5%.
GC-Content Indifferent: Prodigal performs well even in high GC genomes, with over a 90% perfect match (5'+3') to the Pseudomonas aeruginosa curated annotations.
Metagenomic Version: Prodigal can run in metagenomic mode and analyze sequences even when the organism is unknown.
Ease of Use: Prodigal can be run in one step on a single genomic sequence or on a draft genome containing many sequences. It does not need to be supplied with any knowledge of the organism, as it learns all the properties it needs to on its own.
Open Source: Prodigal source code is freely available under the General Public License.

Download the latest version of Prodigal at the Prodigal github page.
or
Browse the wiki documenation.

Address of the bookmark: http://prodigal.ornl.gov/

HGT-Finder: A New Tool for Horizontal Gene Transfer Finding and Application to Aspergillus genomes

Jit — Wed, 17 Jan 2018 05:03:19 -0600

HGT-Finder:

(i) can be used for HGT detection in both prokaryotes and eukaryotes,

(ii) can report a statistical P value for each gene to indicate how likely it is to be horizontally transferred, and

(iii) is fully automated (requires minimal human intervention), as well as very easy to install and run.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4626719/

MGERT: Mobile Genetic Elements Retrieving Tool

Neel — Sat, 18 May 2019 08:58:01 -0500

MGERT is a computational pipeline for easy retrieving of MGE's coding sequences of a particular family from genome assemblies. MGERT utilizes several established bioinformatic tools combined into single pipeline which hides different technical quirks from an inexperienced user.

Address of the bookmark: https://github.com/andrewgull/MGERT

Panacus : A Counting Tool for Pangenome Graphs

Neel — Fri, 14 Jun 2024 14:42:28 -0500

panacus is a tool for calculating statistics for GFA files. It supports GFA files with P and W lines, but requires that the graph is blunt, i.e., nodes do not overlap and consequently, each link (L) points from the end of one segment (S) to the start of another.

panacus supports the following calculations:

coverage histogram
pangenome growth statistics
path-/group-resolved coverage table

Address of the bookmark: https://github.com/marschall-lab/panacus

FQC Dashboard: Integrates FastQC results into a web-based, interactive, and extensible FASTQ quality control tool

Shruti Paniwala — Tue, 10 Nov 2020 01:30:22 -0600

FQC is software that facilitates quality control of FASTQ files by carrying out a QC protocol using FastQC, parsing results, and aggregating quality metrics into an interactive dashboard designed to richly summarize individual sequencing runs. The dashboard groups samples in dropdowns for navigation among the data sets, utilizes human-readable configuration files to manipulate the pages and tabs, and is extensible with CSV data.

Address of the bookmark: https://github.com/pnnl/fqc

Perlbrew: admin-free perl installation management tool.

Jit — Wed, 12 Jul 2017 03:53:08 -0500

perlbrew is an admin-free perl installation management tool. The latest version is 0.79, read the release note: Release 0.79.

Copy & Paste this line into your terminal:

\curl -L https://install.perlbrew.pl | bash

Or, if your system does not have curl but something else:

# Linux
\wget -O - https://install.perlbrew.pl | bash

# FreeBSD
\fetch -o- https://install.perlbrew.pl | sh

If you prefer to install with cpan, there are two steps:

sudo cpan App::perlbrew
perlbrew init

If it is installed with cpan, the perlbrew executable should be installed as /usr/bin/perlbrew or /usr/local/bin/perlbrew. For all users who want to use perlbrew, a prior perlbrew init needs to be executed.

The default perlbrew root directory is ~/perl5/perlbrew, which can be changed by setting PERLBREW_ROOTenvironment variable before the installation and initialization. For more advanced installation process, please read the perlbrew document.

Address of the bookmark: https://perlbrew.pl/

PLAST: A fast, accurate and NGS scalable bank-to-bank sequence similarity search tool

Jit — Fri, 01 Dec 2017 04:10:54 -0600

PLAST is a fast, accurate and NGS scalable bank-to-bank sequence similarity search tool providing significant accelerations of seeds-based heuristic comparison methods, such as the Blast suite of algorithms.

Relying on unique software architecture, PLAST takes full advantage of recent multi-core personal computers without requiring any additional hardware devices.

PLAST stands for Parallel Local Sequence Alignment Search Tool and is was published in BMC Bioinformatics.

PLAST is a general purpose sequence comparison tool providing the following benefits:

PLAST is a high-performance sequence comparison tool designed to compare two sets of sequences (query vs. reference),
Reduces the processing time of sequences comparisons while providing highest quality results,
Contains a fully integrated data filtering engine capable of selecting relevant hits with user-defined criteria (E-Value, identity, coverage, alignment length, etc.),
Does not require any additional hardware, since it is a software solution. It is easy to install, cost-effective, takes full advantage of multi-core processors and uses a small RAM footprint,
Ready to be used on desktop computer, cluster, cloud as well as within distributed system running Hadoop.

https://plast.inria.fr/

Address of the bookmark: https://plast.inria.fr/

Multi-CAR: a tool of contig scaffolding using multiple references

Rahul Nayak — Tue, 06 Mar 2018 16:39:41 -0600

we design a simple heuristic method to further revise our single reference-based scaffolding tool CAR into a new one called Multi-CAR such that it can utilize multiple complete genomes of related organisms as references to more accurately order and orient the contigs of a draft genome. In practical usage, our Multi-CAR does not require prior knowledge concerning phylogenetic relationships among the draft and reference genomes and libraries of paired-end reads. To validate Multi-CAR, we have tested it on a real dataset composed of several prokaryotic genomes and also compared its accuracy performance with other multiple reference-based scaffolding tools Ragout and MeDuSa.

Address of the bookmark: http://genome.cs.nthu.edu.tw/Multi-CAR/