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. 2018 Apr 15;34(8):1416-1418.
doi: 10.1093/bioinformatics/btx795.

DaMiRseq-an R/Bioconductor package for data mining of RNA-Seq data: normalization, feature selection and classification

Mattia Chiesa  1 , Gualtiero I Colombo  1 , Luca Piacentini  1
Affiliations

DaMiRseq-an R/Bioconductor package for data mining of RNA-Seq data: normalization, feature selection and classification

Mattia Chiesa et al. Bioinformatics. .

Abstract

Summary: RNA-Seq is becoming the technique of choice for high-throughput transcriptome profiling, which, besides class comparison for differential expression, promises to be an effective and powerful tool for biomarker discovery. However, a systematic analysis of high-dimensional genomic data is a demanding task for such a purpose. DaMiRseq offers an organized, flexible and convenient framework to remove noise and bias, select the most informative features and perform accurate classification.

Availability and implementation: DaMiRseq is developed for the R environment (R ≥ 3.4) and is released under GPL (≥2) License. The package runs on Windows, Linux and Macintosh operating systems and is freely available to non-commercial users at the Bioconductor open-source, open-development software project repository (https://bioconductor.org/packages/DaMiRseq/). In compliance with Bioconductor standards, the authors ensure stable package maintenance through software and documentation updates.

Contact: luca.piacentini@ccfm.it.

Supplementary information: Supplementary data are available at Bioinformatics online.

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