Creighton Chad J
Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas.
Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Curr Protoc Mol Biol. 2018 Jan 16;121:19.14.1-19.14.13. doi: 10.1002/cpmb.49.
The vast amounts of genomic data now deposited in public repositories represent rich resources for cancer researchers. Large-scale genomics initiatives such as The Cancer Genome Atlas have made available data from multiple molecular profiling platforms (e.g., somatic mutation, RNA and protein expression, and DNA methylation) for the same set of over 10,000 human tumors. There has been much collective effort toward providing user-friendly software tools for biologists lacking computational skills to ask questions of large-scale genomic datasets. At the same time, there remains a clear need for skilled bioinformatics analysts to answer the types of questions that cannot easily be addressed using the public user-friendly software tools. This overview introduces the reader to the many resources available for working with cancer genomic databases. © 2018 by John Wiley & Sons, Inc.
目前存于公共数据库中的海量基因组数据,对癌症研究人员而言是丰富的资源。诸如癌症基因组图谱之类的大规模基因组计划,已提供了来自多个分子分析平台(例如体细胞突变、RNA和蛋白质表达以及DNA甲基化)的数据,这些数据来自同一组超过10000个人类肿瘤。为缺乏计算技能的生物学家提供用户友好型软件工具,以便他们对大规模基因组数据集提出问题,各方已付出诸多共同努力。与此同时,显然仍需要熟练的生物信息学分析师来回答那些使用公共用户友好型软件工具难以解决的问题类型。本综述向读者介绍了处理癌症基因组数据库时可用的众多资源。© 2018约翰威立国际出版公司