seqgen_diff

A numeric design matrix. The rows index the samples
and the columns index the variables.

designmat

A numeric matrix of coefficients. The rows index the
genes and the columns index the variables.

coefmat

A vector of negative binomial dispersion parameters.
Element i is the dispersion for gene i.

dispvec

A numeric design matrix for the surrogate variables.
The rows index the samples and the columns index the surrogate
variables.

design_sv

A numeric matrix of coefficients for the surrogate
variables. The rows index the genes and the columns index the
variables.

coef_sv

Generate a matrix of RNA-seq counts from a theoretical negative-binomial
model.

Generates/modifies RNA-seq data for use in simulations. We provide
a suite of functions that will add a known amount of signal to a real
RNA-seq dataset. The advantage of using this approach over simulating under
a theoretical distribution is that common/annoying aspects of the data
are more preserved, giving a more realistic evaluation of your method.
The main functions are select_counts(), thin_diff(), thin_lib(),
thin_gene(), thin_2group(), thin_all(), and effective_cor(). See
Gerard (2019) <doi:10.1101/758524> for details on the
implemented methods.

seqgen_diff: Theoretical sequence simulation for differential expression analysis.

Description

Usage

Arguments

Value

Details

References