caneToad.groups

<p>Group labels for twenty toads sampled from one
 of two regions in Australia. Data set reduced to
 exclude any transcripts without at least 10 counts
 in at least 10 samples.</p>

datasets

The bioinformatic evaluation of gene co-expression often begins with
correlation-based analyses. However, this approach lacks statistical validity
when applied to relative data. This includes, for example, biological count data
generated by high-throughput RNA-sequencing, chromatin immunoprecipitation (ChIP),
ChIP-sequencing, Methyl-Capture sequencing, and other techniques. This package
implements several metrics for proportionality, including
phi [Lovell et al (2015) <DOI:10.1371/journal.pcbi.1004075>] and
rho [Erb and Notredame (2016) <DOI:10.1007/s12064-015-0220-8>]. This package also
implements several metrics for differential proportionality. Unlike correlation,
these measures give the same result for both relative and absolute data.

Thomas Quinn

propr

Calculating Proportionality Between Vectors of Compositional
Data

David Lovell

Ionas Erb

Anders Bilgrau

Greg Gloor

caneToad.groups function

<p>An object of class <code>character</code> of length 20.</p>

Format

Example Cane Toad Group Data — caneToad.groups

Example Cane Toad Group Data

caneToad.groups: Example Cane Toad Group Data

Description

Usage

Arguments

Format