normalMM

This function perform an empirical Bayes modeling on log fold ratios
and return the posterior log fold ratios.

Provides analytical methods for analyzing CRISPR screen data
at different levels of gene expression. Multi-component normal mixture models
and EM algorithms are used for modeling.

Lianbo Yu

CEDA

CRISPR Screen and Gene Expression Differential Analysis

Yue Zhao

Lang Li

normalMM function

<dl><dt>data</dt>
<dd>A numeric matrix containing limma results and log2 gene 
expression levels that has a column nameed 'lfc' and a column 
named 'exp.level.log2'</dd>
<dt>theta0</dt>
<dd>Standard deviation of log2 fold changes under permutations</dd>
<dt>n.b</dt>
<dd>Number of bins, default is 5 bins</dd>
<dt>d</dt>
<dd>Number of times for fitting mixture model using different 
starting values, default is 10</dd></dl>

Arguments

Performing empirical Bayes modeling on limma results — normalMM

<dl>

<dt>data</dt>
<dd>A numeric matrix containing limma results and log2 gene 
expression levels that has a column nameed 'lfc' and a column 
named 'exp.level.log2'</dd>


<dt>theta0</dt>
<dd>Standard deviation of log2 fold changes under permutations</dd>


<dt>n.b</dt>
<dd>Number of bins, default is 5 bins</dd>


<dt>d</dt>
<dd>Number of times for fitting mixture model using different 
starting values, default is 10</dd>

</dl>

normalMM: Performing empirical Bayes modeling on limma results

Description

Usage

Value

Arguments