Description Details Author(s) References See Also
An R package for implementing goodness-of-fit tests for negative binomial (NB) distributions and NB dispersion models, with applications in RNA-Seq data analysis.
This package can be used to test the goodness-of-fit of NB2, NBP or Poisson regression models. It can also be used to test the goodness-of-fit for a variety of negative binomial dispersion models in popular R/Bioconductor packages, including
NBP dispersion model in the NBPSeq
package (NBP
)
NBQ dispersion model in the NBPSeq
package (NBQ
)
NB common dispersion model in the edgeR
package (Common
)
NB genewise dispersion model in the edgeR
package (Genewise
)
NB trended (non-parametric) dispersion model in the edgeR
package
(Trended
)
NB tagwise-common dispersion model in the edgeR
package
(Tagwise-Common
)
NB tagwise-trended dispersion model in the edgeR
package
(Tagwise-Trend
)
Gu Mi <neo.migu@gmail.com>, Yanming Di, Daniel Schafer
Maintainer: Gu Mi <https://github.com/gu-mi>
Mi, G, Di, Y, & Schafer, DW (2015). Goodness-of-Fit Tests and Model Diagnostics for Negative Binomial Regression of RNA Sequencing Data. PLOS ONE, 10 (3).
Di Y, Schafer DW, Cumbie JS, and Chang JH (2011): "The NBP Negative Binomial Model for Assessing Differential Gene Expression from RNA-Seq", Statistical Applications in Genetics and Molecular Biology, 10 (1).
McCarthy DJ, Chen Y and Smyth GK (2012). Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Research 40, 4288-4297.
Cox, DR, and Reid, N (1987). Parameter orthogonality and approximate conditional inference. Journal of the Royal Statistical Society Series B 49, 1-39.
See https://github.com/gu-mi/NBGOF/wiki/ for more details.
See nb.gof.v
and nb.gof.m
for examples on simulated
datasets. See earthquake
and arab
for real data examples.
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