GeneExampleData


	'GeneExampleData' gives the gene level simulated data with 5 ordered conditions, triplicates for each condition.
	The data set was simulated following the Negative Binomial distribution. The parameters of each gene (mean and overdispersion)
	were sampled from the empirical estimates from an empirical RNA-Seq data set from Thomson lab at Morgridge Institute for 
	Research.  


datasets

The EBSeqHMM package implements an auto-regressive hidden Markov model for statistical analysis in ordered RNA-seq experiments (e.g. time course or spatial course data). The EBSeqHMM package provides functions to identify genes and isoforms that have non-constant expression profile over the time points/positions, and cluster them into expression paths.

Ning Leng

EBSeqHMM

Bayesian analysis for identifying gene or isoform expression
changes in ordered RNA-seq experiments

GeneExampleData function

GeneExampleData is a matrix with 100 genes (rows) and 15 samples (columns).

Format

'GeneExampleData' gives the gene level simulated data with 5 ordered conditions, triplicates for each condition.
	The data set was simulated following the Negative Binomial distribution. The parameters of each gene (mean and overdispersion)
	were sampled from the empirical estimates from an empirical RNA-Seq data set from Thomson lab at Morgridge Institute for 
	Research.

GeneExampleData: Simulated gene level data set with 5 ordered conditions

Description

Arguments

Format

See Also

Examples