Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/nbinomDeviance.R
Fit the same log-link negative binomial or Poisson generalized linear model (GLM) to each row of a matrix of counts.
1 | nbinomDeviance(y, mean, dispersion=0, weights=NULL)
|
y |
numeric matrix containing the negative binomial counts, with rows for genes and columns for libraries. A vector will be treated as a matrix with one row. |
mean |
numeric matrix of expected values, of same dimension as |
dispersion |
numeric vector or matrix of negative binomial dispersions, as for |
weights |
numeric vector or matrix of non-negative weights, as for |
Computes the total residual deviance for each row of y
, i.e., weighted row sums of the unit deviances.
Care is taken to ensure accurate computation in limiting cases when the dispersion is near zero or mean*dispersion
is very large.
nbinomDeviance
returns a numeric vector of length equal to the number of rows of y
.
Gordon Smyth, Yunshun Chen, Aaron Lun. C++ code by Aaron Lun.
Jorgensen, B. (2013). Generalized linear models. Encyclopedia of Environmetrics 3, Wiley. http://onlinelibrary.wiley.com/doi/10.1002/9780470057339.vag010.pub2/abstract.
McCarthy, DJ, Chen, Y, Smyth, GK (2012). Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Research 40, 4288-4297. https://doi.org/10.1093/nar/gks042
1 2 3 | y <- matrix(1:6,3,2)
mu <- matrix(3,3,2)
nbinomDeviance(y,mu,dispersion=0.2)
|
Loading required package: limma
[1] 1.4363222 0.8929643 1.3117841
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