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Pash 3.0: A versatile software package for read mapping and integrative analysis of genomic and epigenomic variation using massively parallel DNA sequencing.

ABSTRACT: Massively parallel sequencing readouts of epigenomic assays are enabling integrative genome-wide analyses of genomic and epigenomic variation. Pash 3.0 performs sequence comparison and read mapping and can be employed as a module within diverse configurable analysis pipelines, including ChIP-Seq and methylome mapping by whole-genome bisulfite sequencing.Pash 3.0 generally matches the accuracy and speed of niche programs for fast mapping of short reads, and exceeds their performance on longer reads generated by a new generation of massively parallel sequencing technologies. By exploiting longer read lengths, Pash 3.0 maps reads onto the large fraction of genomic DNA that contains repetitive elements and polymorphic sites, including indel polymorphisms.We demonstrate the versatility of Pash 3.0 by analyzing the interaction between CpG methylation, CpG SNPs, and imprinting based on publicly available whole-genome shotgun bisulfite sequencing data. Pash 3.0 makes use of gapped k-mer alignment, a non-seed based comparison method, which is implemented using multi-positional hash tables. This allows Pash 3.0 to run on diverse hardware platforms, including individual computers with standard RAM capacity, multi-core hardware architectures and large clusters.

SUBMITTER: Coarfa C

PROVIDER: S-EPMC3001746 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature

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Pash 3.0: A versatile software package for read mapping and integrative analysis of genomic and epigenomic variation using massively parallel DNA sequencing.

Coarfa Cristian C Yu Fuli F Miller Christopher A CA Chen Zuozhou Z Harris R Alan RA Milosavljevic Aleksandar A

BMC bioinformatics 20101123

<h4>Background</h4>Massively parallel sequencing readouts of epigenomic assays are enabling integrative genome-wide analyses of genomic and epigenomic variation. Pash 3.0 performs sequence comparison and read mapping and can be employed as a module within diverse configurable analysis pipelines, including ChIP-Seq and methylome mapping by whole-genome bisulfite sequencing.<h4>Results</h4>Pash 3.0 generally matches the accuracy and speed of niche programs for fast mapping of short reads, and exce ...[more]

PMID: 21092284

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Project description:BACKGROUND:We recently described Hi-Plex, a highly multiplexed PCR-based target-enrichment system for massively parallel sequencing (MPS), which allows the uniform definition of library size so that subsequent paired-end sequencing can achieve complete overlap of read pairs. Variant calling from Hi-Plex-derived datasets can thus rely on the identification of variants appearing in both reads of read-pairs, permitting stringent filtering of sequencing chemistry-induced errors. These principles underly ROVER software (derived from Read Overlap PCR-MPS variant caller), which we have recently used to report the screening for genetic mutations in the breast cancer predisposition gene PALB2. Here, we describe the algorithms underlying ROVER and its usage. RESULTS:ROVER enables users to quickly and accurately identify genetic variants from PCR-targeted, overlapping paired-end MPS datasets. The open-source availability of the software and threshold tailorability enables broad access for a range of PCR-MPS users. METHODS:ROVER is implemented in Python and runs on all popular POSIX-like operating systems (Linux, OS X). The software accepts a tab-delimited text file listing the coordinates of the target-specific primers used for targeted enrichment based on a specified genome-build. It also accepts aligned sequence files resulting from mapping to the same genome-build. ROVER identifies the amplicon a given read-pair represents and removes the primer sequences by using the mapping co-ordinates and primer co-ordinates. It considers overlapping read-pairs with respect to primer-intervening sequence. Only when a variant is observed in both reads of a read-pair does the signal contribute to a tally of read-pairs containing or not containing the variant. A user-defined threshold informs the minimum number of, and proportion of, read-pairs a variant must be observed in for a 'call' to be made. ROVER also reports the depth of coverage across amplicons to facilitate the identification of any regions that may require further screening. CONCLUSIONS:ROVER can facilitate rapid and accurate genetic variant calling for a broad range of PCR-MPS users.

Dataset Information

Pash 3.0: A versatile software package for read mapping and integrative analysis of genomic and epigenomic variation using massively parallel DNA sequencing.

Publications

Pash 3.0: A versatile software package for read mapping and integrative analysis of genomic and epigenomic variation using massively parallel DNA sequencing.

Similar Datasets

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