DeepSNVMiner specifications

Information


Unique identifier OMICS_12087
Name DeepSNVMiner
Software type Pipeline/Workflow
Interface Command line interface
Restrictions to use Academic or non-commercial use
Input data DeepSNVMiner requires three input files; paired-end FASTQ read files and a BED file containing the specific locations of targeted genomic region(s). An initial configuration step is also required to determine the location of three required external resources; Burrows-Wheeler Aligner (BWA), SAMtools, and a reference genome FASTA file with BWA index files.
Output data The final report contains a listing of all variants detected, based on either the user-configured expected variant frequency or default parameters.
Operating system Unix/Linux, Mac OS
Programming languages Perl
Computer skills Advanced
Stability Stable
Maintained Yes

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Documentation


Maintainer


  • person_outline Matthew A. Field <>

Publication for DeepSNVMiner

DeepSNVMiner in publication

PMCID: 5852328
PMID: 29552334
DOI: 10.1016/j.csbj.2018.01.003

[…] rate (after consensus), resulting in remarkably higher specificity compared to raw-reads-based variant calling.fig. 1, currently, three umi-based variant callers are available in public domain: deepsnvminer, mageri, and smcounter , , . deepsnvminer first generates an initial list of variants using samtools calmd and then selects the high-confidence variants with strong umi support. mageri […]


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DeepSNVMiner institution(s)
Department of Immunology, John Curtin School of Medical Research, Australian National University, Canberra, Australia; National Computational Infrastructure, Canberra, Australia; School of Medicine and Pharmacology, University of Western Australia, Harry Perkins Institute, Perth, Australia; Haematology Translational Research Unit, Haematology Unit, ACT Pathology, Canberra, Australia; ANU Medical School, Australian National University, Canberra, Australia; Immunology Division, Garvan Institute of Medical Research, Sydney, Australia; St Vincent’s Clinical School, University of New South Wales, Darlinghurst, Australia
DeepSNVMiner funding source(s)
National Institutes of Health Grant U19 AI100627; NHMRC Australian Fellowship 585490; Bioplatoforms Australia

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