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Introduce Manta, an efficient computational algorithm designed for the rapid discovery of structural variants and indels from germline and cancer whole-genome sequencing.

December 8, 2015BioinformaticsOpen Access

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

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Introduce Manta, an efficient computational algorithm designed for the rapid discovery of structural variants and indels from germline and cancer whole-genome sequencing.
Engineered a bioinformatics tool combining paired-read analysis and local assembly to detect genomic rearrangements.
Optimized computational runtime and memory usage for both germline genomes and paired tumor-normal sequencing datasets.
Enables scalable and rapid identification of structural variants and small insertions or deletions across diverse sequencing pipelines.
Improves variant-calling workflows for high-throughput germline genetics and clinical cancer genomics.

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Computational biology study presents an algorithm for identifying structural variants and indels across germline and cancer genomes, facilitating clinical sequencing applications.

Abstract

Supplementary data are available at Bioinformatics online.

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Chen et al. (2015) studied this question.

synapsesocial.com/papers/69d8da67ade63f05b9bedb50 https://doi.org/10.1093/bioinformatics/btv710

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Implication

Computational biology study presents an algorithm for identifying structural variants and indels across germline and cancer genomes, facilitating clinical sequencing applications.

Abstract

Supplementary data are available at Bioinformatics online.

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

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

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