getNormTheta

object

<p>A numeric vector. The effective library size
normalization factors (e.g., from edgeR or DESeq2).</p>

norm.factors

<p>The <code>getNormTheta</code> function calculates the differential proportionality
 between each feature and a set of normalization factors. When the
 normalization factors correctly remove the compositional bias, the
 resultant thetas indicate differential expression (DE). However, unlike
 other DE tests, the p-value for differential proportionality is
 not linked to the normalization factors. Here, normalization factors
 only affect the interpretation, not the statistics.</p>

The bioinformatic evaluation of gene co-expression often begins with
correlation-based analyses. However, correlation lacks validity when
applied to relative data, including count data generated by next-generation
sequencing. 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

Ryan Moore

getNormTheta function

Get Per-Feature Theta — getNormTheta

Get Per-Feature Theta

getNormTheta: Get Per-Feature Theta

Description

Usage

Arguments

Value

Details