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.
CITATION STYLE
Chiesa, M., Colombo, G. I., & Piacentini, L. (2018). DaMiRseq -An R/Bioconductor package for data mining of RNA-Seq data: Normalization, feature selection and classification. Bioinformatics, 34(8), 1416–1418. https://doi.org/10.1093/bioinformatics/btx795
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