Dataset Information

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

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). 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.

SUBMITTER: Korbel JO

PROVIDER: S-EPMC2688268 | biostudies-literature | 2009 Feb

REPOSITORIES: biostudies-literature

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

Korbel Jan O JO Abyzov Alexej A Mu Xinmeng Jasmine XJ Carriero Nicholas N Cayting Philip P Zhang Zhengdong Z Snyder Michael M Gerstein Mark B MB

Genome biology 20090223 2

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). 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 demonstrat ...[more]

PMID: 19236709

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Dataset Information

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

Publications

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

Similar Datasets

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