| TDI {myTAI} | R Documentation |
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)