calculateFDR

A <code>data.frame</code>. The result of a
<code>calculateTheta</code> call.

theta

A <code>data.frame</code>. The result of a
<code>permuteTheta</code> call.

ptheta

For <code>updateCutoffs</code>, a numeric vector.
this argument provides the FDR cutoffs to test for theta.
For graph functions, a numeric scalar. This argument
indicates the maximum theta to include in the figure.
For graph functions, a large integer will instead
retrieve the top N pairs as ranked by theta.

cutoff

This function uses the result of a <code>permuteTheta</code> call
 to calculate false discovery rate (FDR) cutoffs.

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.

calculateFDR: Calculate FDR Cutoffs

Description

Usage

Arguments