PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data

Personal-genomics endeavors, such as the 1000 Genomes project, are generating maps of genomic structural variants by analyzing ends of massively sequenced genome fragments. To process these we developed Paired-End Mapper (PEMer; ). This comprises an analysis pipeline, compatible with several next-ge...

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Autores principales: Korbel, Jan O, Abyzov, Alexej, Mu, Xinmeng Jasmine, Carriero, Nicholas, Cayting, Philip, Zhang, Zhengdong, Snyder, Michael, Gerstein, Mark B
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2688268/
https://www.ncbi.nlm.nih.gov/pubmed/19236709
http://dx.doi.org/10.1186/gb-2009-10-2-r23
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author Korbel, Jan O
Abyzov, Alexej
Mu, Xinmeng Jasmine
Carriero, Nicholas
Cayting, Philip
Zhang, Zhengdong
Snyder, Michael
Gerstein, Mark B
author_facet Korbel, Jan O
Abyzov, Alexej
Mu, Xinmeng Jasmine
Carriero, Nicholas
Cayting, Philip
Zhang, Zhengdong
Snyder, Michael
Gerstein, Mark B
author_sort Korbel, Jan O
collection PubMed
description Personal-genomics endeavors, such as the 1000 Genomes project, are generating maps of genomic structural variants by analyzing ends of massively sequenced genome fragments. To process these we developed Paired-End Mapper (PEMer; ). This comprises an analysis pipeline, compatible with several next-generation sequencing platforms; simulation-based error models, yielding confidence-values for each structural variant; and a back-end database. The simulations demonstrated high structural variant reconstruction efficiency for PEMer's coverage-adjusted multi-cutoff scoring-strategy and showed its relative insensitivity to base-calling errors.
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spelling pubmed-26882682009-05-29 PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data Korbel, Jan O Abyzov, Alexej Mu, Xinmeng Jasmine Carriero, Nicholas Cayting, Philip Zhang, Zhengdong Snyder, Michael Gerstein, Mark B Genome Biol Software Personal-genomics endeavors, such as the 1000 Genomes project, are generating maps of genomic structural variants by analyzing ends of massively sequenced genome fragments. To process these we developed Paired-End Mapper (PEMer; ). This comprises an analysis pipeline, compatible with several next-generation sequencing platforms; simulation-based error models, yielding confidence-values for each structural variant; and a back-end database. The simulations demonstrated high structural variant reconstruction efficiency for PEMer's coverage-adjusted multi-cutoff scoring-strategy and showed its relative insensitivity to base-calling errors. BioMed Central 2009 2009-02-23 /pmc/articles/PMC2688268/ /pubmed/19236709 http://dx.doi.org/10.1186/gb-2009-10-2-r23 Text en Copyright © 2009 Korbel et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Korbel, Jan O
Abyzov, Alexej
Mu, Xinmeng Jasmine
Carriero, Nicholas
Cayting, Philip
Zhang, Zhengdong
Snyder, Michael
Gerstein, Mark B
PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data
title PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data
title_full PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data
title_fullStr PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data
title_full_unstemmed PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data
title_short PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data
title_sort pemer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2688268/
https://www.ncbi.nlm.nih.gov/pubmed/19236709
http://dx.doi.org/10.1186/gb-2009-10-2-r23
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