TDI: Compute the Transcriptome Divergence Index (TDI)

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

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

Usage

1
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 = ∑ (e_is * ds_i) / ∑ 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). Evidence for Active Maintenance of Phylotranscriptomic Hourglass Patterns in Animal and Plant Embryogenesis. Mol Biol Evol. 32 (5): 1221-1231 doi:10.1093/molbev/msv012.

See Also

TAI, PlotPattern, FlatLineTest, ReductiveHourglassTest

Examples

1
2
3
4
5
# reading a standard DivergenceExpressionSet
data(DivergenceExpressionSetExample)

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


Search within the myTAI package
Search all R packages, documentation and source code

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.