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Papers: 10.1186/s12859-017-1498-y

https://doi.org/10.1186/s12859-017-1498-y

Evaluation of logistic regression models and effect of covariates for case–control study in RNA-Seq analysis

Cited by: 15
Author(s): Seung Hoan Choi, Adam Labadorf, Richard H. Myers, Kathryn L. Lunetta, Josée Dupuis, Anita L. DeStefano
Published: over 8 years ago

Software Mentions 10

bioconductor: baySeq
Empirical Bayesian analysis of patterns of differential expression in count data
Papers that mentioned: 139
Very Likely Science (100)
bioconductor: DESeq2
Differential gene expression analysis based on the negative binomial distribution
Papers that mentioned: 9,583
Very Likely Science (100)
bioconductor: EBSeq
An R package for gene and isoform differential expression analysis of RNA-seq data
Papers that mentioned: 261
Very Likely Science (100)
bioconductor: edgeR
Empirical Analysis of Digital Gene Expression Data in R
Papers that mentioned: 6,568
Very Likely Science (100)
bioconductor: limma
Linear Models for Microarray Data
Papers that mentioned: 7,776
Very Likely Science (78)
bioconductor: NOISeq
Exploratory analysis and differential expression for RNA-seq data
Papers that mentioned: 321
Very Likely Science (100)
bioconductor: TCC
TCC: Differential expression analysis for tag count data with robust normalization strategies
Papers that mentioned: 67
Very Likely Science (100)
cran: NBPSeq
Negative Binomial Models for RNA-Sequencing Data
Papers that mentioned: 32
Very Likely Science (93)
cran: PoissonSeq
Papers that mentioned: 30
Unlikely Science (0)
pypi: voom
A python message bus that you can put 4 million volts through.
Papers that mentioned: 136
Likely Science (40)