NanoStringNormCNV: pre-processing of NanoString CNV data | Zendy

Dorota H.S. Sendorek | Zendy; Emilie Lalonde | Zendy; Cindy Q. Yao | Zendy; Veronica Y. Sabelnykova | Zendy; Robert G. Bristow | Zendy; Paul C. Boutros | Zendy

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NanoStringNormCNV: pre-processing of NanoString CNV data

Author(s) -

Dorota H.S. Sendorek,

Emilie Lalonde,

Cindy Q. Yao,

Veronica Y. Sabelnykova,

Robert G. Bristow,

Paul C. Boutros

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx707

Subject(s) - computer science , normalization (sociology) , visualization , software , copy number variation , data mining , data processing , software package , r package , database , computational science , operating system , biology , gene , biochemistry , genome , sociology , anthropology

The NanoString System is a well-established technology for measuring RNA and DNA abundance. Although it can estimate copy number variation, relatively few tools support analysis of these data. To address this gap, we created NanoStringNormCNV, an R package for pre-processing and copy number variant calling from NanoString data. This package implements algorithms for pre-processing, quality-control, normalization and copy number variation detection. A series of reporting and data visualization methods support exploratory analyses. To demonstrate its utility, we apply it to a new dataset of 96 genes profiled on 41 prostate tumour and 24 matched normal samples.

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