Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications

Bioinformatics - Tập 32 Số 8 - Trang 1220-1222 - 2016
Heyan Sun1, Ole Schulz-Trieglaff2, Richard J. Shaw2, Bret Barnes1, Felix Schlesinger1, Morten Källberg2, Anthony J. Cox2, Semyon Kruglyak1, Christopher T. Saunders1
11Illumina, Inc, 5200 Illumina Way, San Diego, CA 92122, USA and
22Illumina Cambridge Ltd, Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK

Tóm tắt

Summary: We describe Manta, a method to discover structural variants and indels from next generation sequencing data. Manta is optimized for rapid germline and somatic analysis, calling structural variants, medium-sized indels and large insertions on standard compute hardware in less than a tenth of the time that comparable methods require to identify only subsets of these variant types: for example NA12878 at 50× genomic coverage is analyzed in less than 20 min. Manta can discover and score variants based on supporting paired and split-read evidence, with scoring models optimized for germline analysis of diploid individuals and somatic analysis of tumor-normal sample pairs. Call quality is similar to or better than comparable methods, as determined by pedigree consistency of germline calls and comparison of somatic calls to COSMIC database variants. Manta consistently assembles a higher fraction of its calls to base-pair resolution, allowing for improved downstream annotation and analysis of clinical significance. We provide Manta as a community resource to facilitate practical and routine structural variant analysis in clinical and research sequencing scenarios. Availability and implementation: Manta is released under the open-source GPLv3 license. Source code, documentation and Linux binaries are available from https://github.com/Illumina/manta. Contact: [email protected] Supplementary information:  Supplementary data are available at Bioinformatics online.

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Tài liệu tham khảo

Forbes, 2015, COSMIC: exploring the world’s knowledge of somatic mutations in human cancer, Nucleic Acids Res, 43, D805, 10.1093/nar/gku1075

Layer, 2014, LUMPY: a probabilistic framework for structural variant discovery, Genome Biol, 15, R84, 10.1186/gb-2014-15-6-r84

Rausch, 2012, DELLY: structural variant discovery by integrated paired-end and split-read analysis, Bioinformatics, 28, i333, 10.1093/bioinformatics/bts378

Sindi, 2012, An integrative probabilistic model for identification of structural variation in sequencing data, Genome Biol, 13, R22, 10.1186/gb-2012-13-3-r22

Ye, 2009, Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads, Bioinformatics, 25, 2865, 10.1093/bioinformatics/btp394

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Thông tin xuất bản

Bioinformatics

Tập 32 Số 8

1220-1222

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