metaSNV v2.0.1 – Metagenomic SNV Calling Pipeline

metaSNV v2.0.1

:: DESCRIPTION

MetaSNV is a pipeline for calling metagenomic single nucleotide variants (SNVs). It was designed to scale well with the exponentially increasing amount of available metagenomic datasets and is capable of handling large multi-species references.

::DEVELOPER

metaSNV team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / MacOsX
Python

:: DOWNLOAD

metaSNV

:: MORE INFORMATION

Citation:

Van Rossum T, Costea PI, Paoli L, Alves R, Thielemann R, Sunagawa S, Bork P.
metaSNV v2: detection of SNVs and subspecies in prokaryotic metagenomes.
Bioinformatics. 2021 Nov 17:btab789. doi: 10.1093/bioinformatics/btab789. Epub ahead of print. PMID: 34791031.

FermiKit 0.13 / fermi-lite 0.1- De novo Assembly based Variant Calling pipeline for Illumina Short Reads

FermiKit 0.13 / fermi-lite 0.1

:: DESCRIPTION

FermiKit is a de novo assembly based variant calling pipeline for deep Illumina resequencing data.

fermi-lite is a standalone C library as well as a command-line tool for assembling Illumina short reads in regions from 100bp to 10 million bp in size. Fermi-lite is largely a miniature of FermiKit.

::DEVELOPER

Heng Li

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

FermiKit , fermi-lite

:: MORE INFORMATION

Citation

FermiKit: assembly-based variant calling for Illumina resequencing data.
Li H.
Bioinformatics. 2015 Nov 15;31(22):3694-6. doi: 10.1093/bioinformatics/btv440.

CHIAMO 0.2.1 – Genotype Calling Algorithm for Multi-cohort Study

CHIAMO 0.2.1

:: DESCRIPTION

CHIAMO is a program for calling genotypes from the Affymetrix 500K Mapping chip. The program allows for multiple cohorts which have potentially different intensity characteristics that can lead to elevated false-positive rates in genome-wide studies. The underlying model has a hierarchical structure that allows for correlation between the parameters of each cohort.

::DEVELOPER

Chris Spencer, Jonathan Marchini, Peter Donnelly, YY Teo

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/MacOsX

:: DOWNLOAD

CHIAMO

:: MORE INFORMATION

Citation

J. Marchini, B. Howie, S. Myers, G. McVean and P. Donnelly (2007)
A new multipoint method for genome-wide association studies via imputation of genotypes.
Nature Genetics 39 : 906-913

AlphaPeel 0.1.0 – Calling, Phasing, and Imputing Genotype and Sequence data in Pedigree Populations

AlphaPeel 0.1.0

:: DESCRIPTION

AlphaPeel is a software package for calling, phasing, and imputing genotype and sequence data in pedigree populations. This program implements single locus peeling, multi locus peeling, and hybrid peeling.

::DEVELOPER

AlphaGenes

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/MacOsX

:: DOWNLOAD

AlphaPeel

:: MORE INFORMATION

Citation

Whalen A, Ros-Freixedes R, Wilson DL, Gorjanc G, Hickey JM.
Hybrid peeling for fast and accurate calling, phasing, and imputation with sequence data of any coverage in pedigrees.
Genet Sel Evol. 2018 Dec 18;50(1):67. doi: 10.1186/s12711-018-0438-2. PMID: 30563452; PMCID: PMC6299538.

NanoCaller 0.3.3 – Variant Calling tool for long-read Sequencing data

NanoCaller 0.3.3

:: DESCRIPTION

NanoCaller is a computational method that integrates long reads in deep convolutional neural network for the detection of SNPs/indels from long-read sequencing data. NanoCaller uses long-range haplotype structure to generate predictions for each SNP candidate variant site by considering pileup information of other candidate sites sharing reads. Subsequently, it performs read phasing, and carries out local realignment of each set of phased reads and the set of all reads for each indel candidate variant site to generate indel calling, and then creates consensus sequences for indel sequence prediction.

::DEVELOPER

Wang Genomics Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
Pyton

:: DOWNLOAD

NanoCaller

:: MORE INFORMATION

Citation

Ahsan, Umair and Liu, Qian and Wang, Kai.
NanoCaller for accurate detection of SNPs and small indels from long-read sequencing by deep neural networks.
bioRxiv 2019.12.29.890418; doi: https://doi.org/10.1101/2019.12.29.890418

deepSNV 1.32.0 – Calling Subclonal SNVs from paired Deep Sequencing Experiments

deepSNV 1.32.0

:: DESCRIPTION

deepSNV is an R package for calling subclonal single-nucleotide variants from paired deep sequencing experiments.This package provides provides a quantitative variant caller for detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing experiments. It assumes a comparative setup with a control experiment of the same loci and a beta-binomial model to discriminate sequencing errors and subclonal SNVs.

::DEVELOPER

the Computational Biology Group (CBG)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows / Linux / MacOS
R package
VGAM
Bioconductor

:: DOWNLOAD

deepSNV

:: MORE INFORMATION

Citation

Nat Commun. 2012 May 1;3:811. doi: 10.1038/ncomms1814.
Reliable detection of subclonal single-nucleotide variants in tumour cell populations.
Gerstung M1, Beisel C, Rechsteiner M, Wild P, Schraml P, Moch H, Beerenwinkel N.