Hübschmann Daniel, Schlesner Matthias
Division of Theoretical Bioinformatics (B080), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Department of Pediatric Immunology, Hematology and Oncology, University Hospital, Heidelberg, Germany.
Methods Mol Biol. 2019;1956:321-336. doi: 10.1007/978-1-4939-9151-8_15.
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.
全基因组测序（WGS）能够全面洞察淋巴瘤的基因构成。在此，我们描述了一系列分析WGS数据的方法，包括比对、不同类型基因组变异的识别、驱动突变的识别以及突变特征的识别。我们还进一步概述了WGS研究的设计考量，并提供了多种质量控制措施，以检测数据中常见的质量问题。
