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. 2019:1956:321-336.
doi: 10.1007/978-1-4939-9151-8_15.

Evaluation of Whole Genome Sequencing Data

Affiliations

Evaluation of Whole Genome Sequencing Data

Daniel Hübschmann et al. Methods Mol Biol. 2019.

Abstract

Whole genome sequencing (WGS) can provide comprehensive insights into the genetic makeup of lymphomas. Here we describe a selection of methods for the analysis of WGS data, including alignment, identification of different classes of genomic variants, the identification of driver mutations, and the identification of mutational signatures. We further outline design considerations for WGS studies and provide a variety of quality control measures to detect common quality problems in the data.

Keywords: Mutational signatures; Next-generation sequencing; Quality control; Variant calling.

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