timeSeq.sort: Sort NDPE Genes by Kullback Leibler Distance Ratios or...

In timeSeq: Detecting Differentially Expressed Genes in Time Course RNA-Seq Data

Description

Sort all genes in the dataset by their Kullback Leibler distance ratios or p-values.

Usage

timeSeq.sort(genenames,npde,pde,table,count,pvalue)

Arguments

genenames	a vector of gene names.
npde	a vector of Kullback Leibler distance ratios or p-values for NPDE genes.
pde	a vector of Kullback Leibler distance ratios or p-values for PDE genes.
table	gene expression values.
count	the number of exons or replicates for each gene.
pvalue	logical:indicating if p-values are returned.

Value

A list with components

npde.list	dataframe of NPDE genes sorted by KLRs or p-values.
pde.list	dataframe of PDE genes sorted by KLRs or p-values.
table1	gene expression values for each gene, corresponding to npde.list.
table2	gene expression values for each gene, corresponding to pde.list.

Author(s)

Fan Gao and Xiaoxiao Sun

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

timeSeq documentation built on May 2, 2019, 3:07 a.m.