timeSeq (version 1.0.4)

timeSeq.heatmap: Heatmap of the Most Significant NDPE Genes

Description

Heatmap for the most significant NDPE genes.

Usage

timeSeq.heatmap(timeSeq.obj,n)

Arguments

timeSeq.obj

an object returned by timeSeq function

n

the number of the most significant NPDE genes. It must be a positive integer.

References

Sun, Xiaoxiao, David Dalpiaz, Di Wu, Jun S. Liu, Wenxuan Zhong, and Ping Ma. "Statistical inference for time course RNA-Seq data using a negative binomial mixed-effect model." BMC Bioinformatics, 17(1):324, 2016.

Chong Gu. Model diagnostics for smoothing spline ANOVA models. Canadian Journal of Statistics, 32(4):347-358, 2004.

Chong Gu. Smoothing spline ANOVA models. Springer, second edition, 2013.

Chong Gu and Ping Ma. Optimal smoothing in nonparametric mixed-effect models. Annals of Statistics, pages 1357-1379, 2005a.

Wood (2001) mgcv:GAMs and Generalized Ridge Regression for R. R News 1(2):20-25

Examples

# NOT RUN {
data(simulate.dt)
attach(simulate.dt)
model.fit <- timeSeq(data.count,group.label,gene.names,exon.level=FALSE,pvalue=TRUE)
timeSeq.heatmap(model.fit,n=10)
# }