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NanoStringNormCNV: pre-processing of NanoString CNV data
Dorota H Sendorek1, Emilie Lalonde1,2, Cindy Q Yao1
1Informatics and Biocomputing Program, Ontario Institute for Cancer Research.
Bioinformatics (Oxford, England)
|November 8, 2017
Summary
A new R package, NanoStringNormCNV, addresses the need for analyzing copy number variation from NanoString data. It offers pre-processing, normalization, and variant calling for improved genomic analysis.
Area of Science:
- Genomics
- Bioinformatics
Background:
- The NanoString system is widely used for RNA and DNA abundance measurement.
- Analysis tools for copy number variation (CNV) from NanoString data are limited.
Purpose of the Study:
- To develop and introduce NanoStringNormCNV, an R package for pre-processing and CNV calling from NanoString data.
- To provide a comprehensive solution for analyzing CNV in genomic datasets.
Main Methods:
- Implementation of algorithms for pre-processing, quality control, and normalization.
- Development of copy number variant detection methods.
- Integration of reporting and data visualization tools.
Main Results:
- NanoStringNormCNV enables robust pre-processing and CNV detection.
- The package was successfully applied to a dataset of prostate tumors and matched normal samples.
- Demonstrated utility in analyzing copy number variations across 96 genes.
Conclusions:
- NanoStringNormCNV fills a critical gap in the analysis of NanoString genomic data.
- The package facilitates exploratory data analysis and variant calling for researchers.
- Provides a valuable resource for genomic studies involving NanoString technology.
