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癌症基因组图谱的大规模微小RNA分析

Large-scale profiling of microRNAs for The Cancer Genome Atlas.

作者信息

Chu Andy, Robertson Gordon, Brooks Denise, Mungall Andrew J, Birol Inanc, Coope Robin, Ma Yussanne, Jones Steven, Marra Marco A

机构信息

Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada.

Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada Department of Medical Genetics, University of British Columbia, Vancouver, V6H 3N1, Canada.

出版信息

Nucleic Acids Res. 2016 Jan 8;44(1):e3. doi: 10.1093/nar/gkv808. Epub 2015 Aug 13.

Abstract

The comprehensive multiplatform genomics data generated by The Cancer Genome Atlas (TCGA) Research Network is an enabling resource for cancer research. It includes an unprecedented amount of microRNA sequence data: ~11 000 libraries across 33 cancer types. Combined with initiatives like the National Cancer Institute Genomics Cloud Pilots, such data resources will make intensive analysis of large-scale cancer genomics data widely accessible. To support such initiatives, and to enable comparison of TCGA microRNA data to data from other projects, we describe the process that we developed and used to generate the microRNA sequence data, from library construction through to submission of data to repositories. In the context of this process, we describe the computational pipeline that we used to characterize microRNA expression across large patient cohorts.

摘要

癌症基因组图谱(TCGA)研究网络生成的综合多平台基因组学数据是癌症研究的有力资源。它包含了数量空前的微小RNA序列数据:涵盖33种癌症类型的约11000个文库。结合美国国立癌症研究所基因组学云试点项目等计划,此类数据资源将使大规模癌症基因组学数据的深入分析广泛可得。为支持此类计划,并使TCGA微小RNA数据能够与其他项目的数据进行比较,我们描述了我们开发并用于生成微小RNA序列数据的过程,从文库构建到将数据提交至数据库。在此过程中,我们描述了用于在大量患者队列中表征微小RNA表达的计算流程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f3b/4705681/e1055c01512d/gkv808fig1.jpg

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