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QuasiSeq

QuasiSeq: Analyzing RNA Sequence Count Tables Using Quasi-likelihood. Identify differentially expressed genes in RNA-seq count data using quasi-Poisson or quasi-negative binomial models with QL, QLShrink and QLSpline methods (Lund, Nettleton, McCarthy, and Smyth, 2012).

Keywords for this software

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  • quasi-likelihood
  • generalized linear model
  • RNA-seq data
  • differential expression
  • gene expression
  • moderate deviation
  • random effects
  • RNA sequencing
  • ROC/AUC
  • RNA-seq
  • hierarchical model
  • method comparison
  • type-I error
  • mixture model
  • microarray
  • residual feed intake
  • detection boundary
  • mixture models
  • multiple testing procedure
  • empirical Bayes
  • differential expression analysis
  • RNA-seq data analysis
  • heterosis
  • multifactor experiments
  • false discovery proportion
  • generalized linear mixed models
  • generalized linear models
  • false discovery rate

  • URL: cran.r-project.org/web...
  • Code
  • InternetArchive
  • Manual: cran.r-project.org/web...
  • Authors: Steve Lund; Long Qu
  • Dependencies: R

  • Add information on this software.


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References in zbMATH (referenced in 7 articles , 1 standard article )

Showing results 1 to 7 of 7.
y Sorted by year (citations)

  1. Qiu, Yumou; Chen, Song Xi; Nettleton, Dan: Detecting rare and faint signals via thresholding maximum likelihood estimators (2018)
  2. Lun, Aaron T. L.; Smyth, Gordon K.: No counts, no variance: allowing for loss of degrees of freedom when assessing biological variability from RNA-seq data (2017)
  3. Bonafede, Elisabetta; Picard, Franck; Robin, Stéphane; Viroli, Cinzia: Modeling overdispersion heterogeneity in differential expression analysis using mixtures (2016)
  4. Cui, Shiqi; Ji, Tieming; Li, Jilong; Cheng, Jianlin; Qiu, Jing: What if we ignore the random effects when analyzing RNA-seq data in a multifactor experiment (2016)
  5. 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)
  6. Ji, Tieming; Liu, Peng; Nettleton, Dan: Estimation and testing of gene expression heterosis (2014)
  7. Lund, Steven P.; Nettleton, Dan; McCarthy, Davis J.; Smyth, Gordon K.: Detecting differential expression in RNA-sequence data using quasi-likelihood with shrunken dispersion estimates (2012)

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