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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2014-01-01
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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 |
work_keys_str_mv |
AT konradjkarczewski stormseqanopensourceuserfriendlypipelineforprocessingpersonalgenomicsdatainthecloud AT guyhaskinfernald stormseqanopensourceuserfriendlypipelineforprocessingpersonalgenomicsdatainthecloud AT aliciarmartin stormseqanopensourceuserfriendlypipelineforprocessingpersonalgenomicsdatainthecloud AT michaelsnyder stormseqanopensourceuserfriendlypipelineforprocessingpersonalgenomicsdatainthecloud AT nicholasptatonetti stormseqanopensourceuserfriendlypipelineforprocessingpersonalgenomicsdatainthecloud AT joeltdudley stormseqanopensourceuserfriendlypipelineforprocessingpersonalgenomicsdatainthecloud |
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