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RUVseq

RUVSeq: Remove Unwanted Variation from RNA-Seq Data. This package implements the remove unwanted variation (RUV) methods of Risso et al. (2014) for the normalization of RNA-Seq read counts between samples.

Keywords for this software

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  • normalization
  • isoform analysis
  • FFPE
  • over-dispersion
  • DEGseq
  • symmetric Kullback-Leibler divergence
  • metagenomic data
  • pool adjacent violators algorithm
  • negative binomial processes
  • cluster analysis
  • Bayesian inference
  • ChIPseq
  • housekeeping gene
  • copy number change
  • classification
  • genome matching
  • batch effect
  • residual feed intake
  • replicate analysis
  • integrated nested Laplace approximation
  • control probes
  • quantitative trait loci
  • spike-in normalization
  • random coefficients regression
  • genotype calling
  • negative binomial test
  • RNAseq
  • Bayesian hierarchical modeling
  • Markov chain Monte Carlo
  • generalized linear model

  • URL: www.bioconductor.org/p...
  • InternetArchive
  • Authors: Davide Risso; Sandrine Dudoit
  • Dependencies: R

  • Add information on this software.


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References in zbMATH (referenced in 5 articles )

Showing results 1 to 5 of 5.
y Sorted by year (citations)

  1. Jia, Gaoxiang; Wang, Xinlei; Li, Qiwei; Lu, Wei; Tang, Ximing; Wistuba, Ignacio; Xie, Yang: RCRnorm: an integrated system of random-coefficient hierarchical regression models for normalizing nanostring nCounter data (2019)
  2. Dadaneh, Siamak Zamani; Qian, Xiaoning; Zhou, Mingyuan: BNP-seq: Bayesian nonparametric differential expression analysis of sequencing count data (2018)
  3. Mueller, Jonas; Jaakkola, Tommi; Gifford, David: Modeling persistent trends in distributions (2018)
  4. Nguyen, Yet; Nettleton, Dan; Liu, Haibo; Tuggle, Christopher K.: Detecting differentially expressed genes with RNA-seq data using backward selection to account for the effects of relevant covariates (2015)
  5. Datta, Somnath (ed.); Nettleton, Dan (ed.): Statistical analysis of next generation sequencing data (2014)

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