Strelka2: fast and accurate calling of germline and somatic variants

By Sangtae Kim, Konrad Scheffler, A. Halpern, M. Bekritsky, Eunho Noh, Morten Källberg, Xiaoyu Chen, Yeonbin Kim, Doruk Beyter, P. Krusche and 1 more. Nature Methods, 2018

1,345 citations recorded by the source corpus.

We describe Strelka2 (https://github.com/Illumina/strelka), an open-source small-variant-calling method for research and clinical germline and somatic sequencing applications. Strelka2 introduces a novel mixture-model-based estimation of insertion/deletion error parameters from each sample, an efficient tiered haplotype-modeling strategy, and a normal sample contamination model to improve liquid tumor analysis. For both germline and somatic calling, Strelka2 substantially outperformed the current leading tools in terms of both variant-calling accuracy and computing cost. Strelka2 incorporates improvements for fast and accurate calling of somatic and germline single-nucleotide variants and indels.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0dd631fcb7c6d61549e5e3c3ddbb996f0db397f1

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In Cancer Research

1. Guo-li Ming
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1. Hongjun Song
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Citations in the corpus

• A Patient-Derived Glioblastoma Organoid Model and Biobank Recapitulates Inter- and Intra-tumoral Heterogeneity. (2019, methodology): “Then, Strelka2 was run in exome mode using identified candidate indels also across the primary GRCh38 contigs to identify somatic variants (Kim et al., 2018).”