STORMSeq: an open-source, user-friendly pipeline for processing personal genomics data in the cloud.

The increasing public availability of personal complete genome sequencing data has ushered in an era of democratized genomics. However, read mapping and variant calling software is constantly improving and individuals with personal genomic data may prefer to customize and update their variant calls....

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Main Authors: Konrad J Karczewski, Guy Haskin Fernald, Alicia R Martin, Michael Snyder, Nicholas P Tatonetti, Joel T Dudley
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3893165?pdf=render
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spelling doaj-7e27acc060974172a89fb7d0876933dd2020-11-25T01:26:49ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0191e8486010.1371/journal.pone.0084860STORMSeq: an open-source, user-friendly pipeline for processing personal genomics data in the cloud.Konrad J KarczewskiGuy Haskin FernaldAlicia R MartinMichael SnyderNicholas P TatonettiJoel T DudleyThe increasing public availability of personal complete genome sequencing data has ushered in an era of democratized genomics. However, read mapping and variant calling software is constantly improving and individuals with personal genomic data may prefer to customize and update their variant calls. Here, we describe STORMSeq (Scalable Tools for Open-Source Read Mapping), a graphical interface cloud computing solution that does not require a parallel computing environment or extensive technical experience. This customizable and modular system performs read mapping, read cleaning, and variant calling and annotation. At present, STORMSeq costs approximately $2 and 5-10 hours to process a full exome sequence and $30 and 3-8 days to process a whole genome sequence. We provide this open-access and open-source resource as a user-friendly interface in Amazon EC2.http://europepmc.org/articles/PMC3893165?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Konrad J Karczewski
Guy Haskin Fernald
Alicia R Martin
Michael Snyder
Nicholas P Tatonetti
Joel T Dudley
spellingShingle Konrad J Karczewski
Guy Haskin Fernald
Alicia R Martin
Michael Snyder
Nicholas P Tatonetti
Joel T Dudley
STORMSeq: an open-source, user-friendly pipeline for processing personal genomics data in the cloud.
PLoS ONE
author_facet Konrad J Karczewski
Guy Haskin Fernald
Alicia R Martin
Michael Snyder
Nicholas P Tatonetti
Joel T Dudley
author_sort Konrad J Karczewski
title STORMSeq: an open-source, user-friendly pipeline for processing personal genomics data in the cloud.
title_short STORMSeq: an open-source, user-friendly pipeline for processing personal genomics data in the cloud.
title_full STORMSeq: an open-source, user-friendly pipeline for processing personal genomics data in the cloud.
title_fullStr STORMSeq: an open-source, user-friendly pipeline for processing personal genomics data in the cloud.
title_full_unstemmed STORMSeq: an open-source, user-friendly pipeline for processing personal genomics data in the cloud.
title_sort stormseq: an open-source, user-friendly pipeline for processing personal genomics data in the cloud.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2014-01-01
description The increasing public availability of personal complete genome sequencing data has ushered in an era of democratized genomics. However, read mapping and variant calling software is constantly improving and individuals with personal genomic data may prefer to customize and update their variant calls. Here, we describe STORMSeq (Scalable Tools for Open-Source Read Mapping), a graphical interface cloud computing solution that does not require a parallel computing environment or extensive technical experience. This customizable and modular system performs read mapping, read cleaning, and variant calling and annotation. At present, STORMSeq costs approximately $2 and 5-10 hours to process a full exome sequence and $30 and 3-8 days to process a whole genome sequence. We provide this open-access and open-source resource as a user-friendly interface in Amazon EC2.
url http://europepmc.org/articles/PMC3893165?pdf=render
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