Large-scale profiling of microRNAs for The Cancer Genome Atlas | Zendy

Andy Chu | Zendy; Gordon Robertson | Zendy; Denise Brooks | Zendy; Andrew J. Mungall | Zendy; İnanç Birol | Zendy; Robin Coope | Zendy; Yussanne Ma | Zendy; Steven J.M. Jones | Zendy; Marco A. Marra | Zendy

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Large-scale profiling of microRNAs for The Cancer Genome Atlas

Author(s) -

Andy Chu,

Gordon Robertson,

Denise Brooks,

Andrew J. Mungall,

İnanç Birol,

Robin Coope,

Yussanne Ma,

Steven J.M. Jones,

Marco A. Marra

Publication year - 2015

Publication title -

nucleic acids research

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 9.008

H-Index - 537

eISSN - 1362-4954

pISSN - 0305-1048

DOI - 10.1093/nar/gkv808

Subject(s) - biology , computational biology , genome , atlas (anatomy) , microrna , profiling (computer programming) , gene expression profiling , genetics , gene , gene expression , anatomy , computer science , operating system

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.

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