ComputeSummaryStatistics

Summary statistics are computed for all samples (or cells).

Nucleotide conversion sequencing experiments have been
developed to add a temporal dimension to RNA-seq and single-cell RNA-seq. Such
experiments require specialized tools for primary processing such as GRAND-SLAM,
(see 'Jürges et al' <doi:10.1093/bioinformatics/bty256>) and specialized tools for
downstream analyses. 'grandR' provides a comprehensive toolbox for quality control,
kinetic modeling, differential gene expression analysis and visualization of such data.

Florian Erhard

grandR

Comprehensive Analysis of Nucleotide Conversion Sequencing Data

Teresa Rummel

Lygeri Sakellaridi

Kevin Berg

ComputeSummaryStatistics function

<dl><dt>data</dt>
<dd>a grandR object</dd>
<dt>pairs</dt>
<dd>a no4sU pairs list as generated by Findno4sUPairs</dd>
<dt>coldata</dt>
<dd>if TRUE, add the coldata table</dd>
<dt>do.bootstrap</dt>
<dd>if TRUE, also report standard errors of the 4sU dropout estimated via bootstrapping</dd>
<dt>seed</dt>
<dd>the seed for the random number generator for bootstrapping</dd></dl>

Arguments

Compute summary statistics — ComputeSummaryStatistics

<dl>

<dt>data</dt>
<dd>a grandR object</dd>


<dt>pairs</dt>
<dd>a no4sU pairs list as generated by Findno4sUPairs</dd>


<dt>coldata</dt>
<dd>if TRUE, add the coldata table</dd>


<dt>do.bootstrap</dt>
<dd>if TRUE, also report standard errors of the 4sU dropout estimated via bootstrapping</dd>


<dt>seed</dt>
<dd>the seed for the random number generator for bootstrapping</dd>

</dl>

ComputeSummaryStatistics: Compute summary statistics

Description

Usage

Value

Arguments