rnaseq

<p>RNA-seq data simulated following the standard procedures
(provided by Dr. Wei Sun, weisun@email.unc.edu).</p>

dataset

Provides functions that (1) fit multivariate discrete distributions, (2) generate random numbers from multivariate discrete distributions, and (3) run regression and penalized regression on the multivariate categorical response data.  Implemented models include: multinomial logit model, Dirichlet multinomial model, generalized Dirichlet multinomial model, and negative multinomial model. Making the best of the minorization-maximization (MM) algorithm and Newton-Raphson method, we derive and implement stable and efficient algorithms to find the maximum likelihood estimates. On a multi-core machine, multi-threading is supported.

Juhyun Kim

MGLM

Multivariate Response Generalized Linear Models

rnaseq function

<p>A data frame containing 10 columns and 100 rows. 
		The first 6 columns are the expression counts of 6 exons of a 
		gene; the last four columns are the covariates:
		age, gender, treatment, and total number of reads.</p>

rnaseq: RNA-seq count data

Description

Usage

Arguments

Format