Description Usage Arguments Value See Also
Internal Function to Fit a GammaPoisson GLM
1 2 3 4 5 6 7 8 9 10 11  glm_gp_impl(
Y,
model_matrix,
offset = 0,
size_factors = c("normed_sum", "deconvolution", "poscounts"),
overdispersion = TRUE,
overdispersion_shrinkage = TRUE,
do_cox_reid_adjustment = TRUE,
subsample = FALSE,
verbose = FALSE
)

Y 
any matrixlike object (e.g. 
model_matrix 
a numeric matrix that specifies the experimental
design. It can be produced using 
offset 
Constant offset in the model in addition to 
size_factors 
in large scale experiments, each sample is typically of different size
(for example different sequencing depths). A size factor is an internal mechanism of GLMs to
correct for this effect. 
overdispersion 
the simplest count model is the Poisson model. However, the Poisson model
assumes that variance = mean. For many applications this is too rigid and the GammaPoisson
allows a more flexible meanvariance relation (variance = mean + mean^2 * overdispersion).
Note that 
overdispersion_shrinkage 
the overdispersion can be difficult to estimate with few replicates. To
improve the overdispersion estimates, we can share information across genes and shrink each individual
overdispersion estimate towards a global overdispersion estimate. Empirical studies show however that
the overdispersion varies based on the mean expression level (lower expression level => higher
dispersion). If 
do_cox_reid_adjustment 
the classical maximum likelihood estimator of the 
subsample 
the estimation of the overdispersion is the slowest step when fitting
a GammaPoisson GLM. For datasets with many samples, the estimation can be considerably sped up
without loosing much precision by fitting the overdispersion only on a random subset of the samples.
Default: 
verbose 
a boolean that indicates if information about the individual steps are printed
while fitting the GLM. Default: 
a list with four elements
Beta
the coefficient matrix
overdispersion
the vector with the estimated overdispersions
Mu
a matrix with the corresponding means for each gene
and sample
size_factors
a vector with the size factor for each
sample
glm_gp()
and overdispersion_mle()
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.