来自异质性肿瘤样本的下一代测序数据的生物信息学数据分析

Bioinformatics Data Analysis of Next-Generation Sequencing Data from Heterogeneous Tumor Samples.

作者信息

Landman Sean R, Hwang Tae Hyun

机构信息

Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA.

Department of Quantitative Health Sciences, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OHIO, 44195, USA.

出版信息

Methods Mol Biol. 2017;1633:185-192. doi: 10.1007/978-1-4939-7142-8_12.

DOI:10.1007/978-1-4939-7142-8_12

PMID:28735488

Abstract

Tumor heterogeneity is a major challenge when it comes to treating cancer and also complicates research aimed at determining genetic sources for tumorigenesis. Leveraging high-throughput sequencing technology has been an effective approach for advancing our understanding of genetic diseases, and this type of data can also be used to better understand and make inferences about tumor heterogeneity. Here we describe the basics of genomics data analysis, as well as analysis pipelines for investigating tumor heterogeneity with next-generation sequencing data.

摘要

肿瘤异质性是癌症治疗面临的一项重大挑战，也使旨在确定肿瘤发生遗传根源的研究变得复杂。利用高通量测序技术一直是增进我们对遗传疾病理解的有效方法，这类数据还可用于更好地理解肿瘤异质性并进行推断。在此，我们描述基因组学数据分析的基础，以及利用下一代测序数据研究肿瘤异质性的分析流程。