compute_normalization_factors

internal

Provides a comprehensive framework for time series omics analysis,
integrating changepoint detection, smooth and shape-constrained trends,
and uncertainty quantification. It supports gene- and transcript-level inferences,
p-value aggregation for improved power, and both case-only and case-control designs.
It includes an interactive 'shiny' interface. The methods are described in Yates et al. (2024) <doi:10.1101/2024.12.22.630003>.

Luke Yates

cpam

Changepoint Additive Models for Time Series Omics Data

Michael Charleston

Jazmine Humphreys

Steven Smith

compute_normalization_factors function

<dl><dt>count_matrix_filtered</dt>
<dd>Filtered count matrix</dd>
<dt>normalize</dt>
<dd>Whether to perform normalization</dd></dl>

Arguments

Compute normalization factors — compute_normalization_factors

<dl>

<dt>count_matrix_filtered</dt>
<dd>Filtered count matrix</dd>


<dt>normalize</dt>
<dd>Whether to perform normalization</dd>

</dl>

Compute normalization factors

compute_normalization_factors: Compute normalization factors

Description

Usage

Value

Arguments