TDI: Compute the Transcriptome Divergence Index (TDI)

In HajkD/myTAI: Evolutionary Transcriptomics

Compute the Transcriptome Divergence Index (TDI)

Description

This function computes the sequence distance based transcriptome divergence index (TDI) introduced by Quint et al., 2012.

Usage

TDI(DivergenceExpressionSet)

Arguments

DivergenceExpressionSet

a standard PhyloExpressionSet or DivergenceExpressionSet object.

Details

The TDI measure represents the weighted arithmetic mean (expression levels as weights for the divergence-stratum value) over all gene divergence categories denoted as divergence-strata.

TDI_s = \sum (e_is * ds_i) / \sum e_is

where TDI_s denotes the TDI value in developmental stage s, e_is denotes the gene expression level of gene i in stage s, and ds_i denotes the corresponding divergence-stratum of gene i, i = 1,...,N and N = total number of genes.

Internally the function is written in C++ to speed up TDI computations.

Value

a numeric vector containing the TDI values for all given developmental stages.

Author(s)

Hajk-Georg Drost

References

Quint M et al. (2012). A transcriptomic hourglass in plant embryogenesis. Nature (490): 98-101.

Drost HG et al. (2015) Mol Biol Evol. 32 (5): 1221-1231 doi:10.1093/molbev/msv012

See Also

TAI, PlotPattern, FlatLineTest, ReductiveHourglassTest

Examples

# reading a standard DivergenceExpressionSet
data(DivergenceExpressionSetExample)

# computing the TDI profile of a given DivergenceExpressionSet object
TDIs <- TDI(DivergenceExpressionSetExample)

HajkD/myTAI documentation built on April 6, 2024, 7:47 p.m.