distances: Internal functions for estimating pair-wise expression...

In jingwyang/TreeExp: the R package for analyzing expression evolution based on RNA-seq data

Description

Several published methods to estimate pair-wise expression distances

Usage

dist.jsd(expMat = NULL)

dist.pea(expMat = NULL)

dist.spe(expMat = NULL)

dist.euc(expMat = NULL)

dist.cos(expMat = NULL)

dist.tani(expMat = NULL)

dist.jac(expMat = NULL)

dist.ced(expMat = NULL)

dist.sou(expMat = NULL)

Arguments

expMat

an exprssion level matrix

Value

returns expression distance matrix

References

Chen H, He X. 2016. The Convergent Cancer Evolution toward a Single Cellular Destination. Mol Biol Evol 33:4-12

Gu X, Su Z. 2007. Tissue-driven hypothesis of genomic evolution and sequence-expression correlations. Proc Natl Acad Sci USA 104:2779-2784.

Pereira V, Waxman D, Eyre-Walker A. 2009. A problem with the correlation coefficient as a measure of gene expression divergence. Genetics 183:1597-1600.

Sudmant PH, Alexis MS, Burge CB. 2015. Meta-analysis of RNA-seq expression data across species, tissues and studies. Genome Biol 16:287.

Examples

data('tetraExp')
expression_table <- exptabTE(tetraExp, taxa = "all",
subtaxa = "Brain")
dismat <- dist.pea(expression_table)

jingwyang/TreeExp documentation built on June 11, 2019, 6:17 p.m.