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

doi:10.1186/gb-2009-10-2-r23

Genome Biology

Volume 10
Issue 2

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Korbel JO
Abyzov A
Mu XJ
Carriero N
Cayting P
Zhang Z
Snyder M
Gerstein MB

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Korbel JO
Abyzov A
Mu XJ
Carriero N
Cayting P
Zhang Z
Snyder M
Gerstein MB
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PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data

Jan O Korbel¹^,2^,3 , Alexej Abyzov³ , Xinmeng Jasmine Mu⁴ , Nicholas Carriero⁵ , Philip Cayting³ , Zhengdong Zhang³ , Michael Snyder³^,4 and Mark B Gerstein³^,4^,5^,6

¹Gene Expression Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstr., Heidelberg, 69117, Germany

²EMBL Outstation Hinxton, EMBL-European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK

³Molecular Biophysics and Biochemistry Department, Yale University, Whitney Ave, New Haven, CT 06520, USA

⁴Department of Molecular, Cellular, and Developmental Biology, Yale University, Whitney Ave, New Haven, CT 06520, USA

⁵Department of Computer Science, Yale University, Prospect Street, New Haven, CT 06511, USA

⁶Program in Computational Biology and Bioinformatics, Yale University, Whitney Ave, New Haven, CT 06520, USA

author email corresponding author email

Genome Biology 2009, 10:R23doi:10.1186/gb-2009-10-2-r23


Published:	23 February 2009

Subject areas: Bioinformatics, Genome studies

Abstract

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; http://sv.gersteinlab.org/pemer webcite). 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.