hotspot_df

A dataframe containing mutation probabilities for every possible 5mer pattern

datasets

Simulate full B-cell and T-cell receptor repertoires using an in silico
recombination process that includes a wide variety of tunable parameters to introduce noise and biases.
Additional post-simulation modification functions allow the user to implant motifs or codon biases as
well as remodeling sequence similarity architecture. The output repertoires contain records of all
relevant repertoire dimensions and can be analyzed using provided repertoire analysis functions.
Preprint is available at bioRxiv (Weber et al., 2019 <doi:10.1101/759795>).

C<c3><a9>dric R. Weber

immuneSIM

Tunable Simulation of B- And T-Cell Receptor Repertoires

Victor Greiff

hotspot_df function

A data frame with 1024 rows and variables:<dl class="dl-horizontal">
 <dt>pattern</dt><dd>amino acid</dd>
 <dt>toA</dt><dd>probability of mutation to adenine</dd>
 <dt>toC</dt><dd>probability of mutation to cytosine</dd>
 <dt>toG</dt><dd>probability of mutation to guanine</dd>
 <dt>toT</dt><dd>probability of mutation to thymine</dd>
 <dt>Source</dt><dd>source of probability</dd>
</dl>

Format

Hotspot dataframe for SHM — hotspot_df

A data frame with 1024 rows and variables:<dl class='dl-horizontal'>
 <dt>pattern</dt><dd>amino acid</dd>
 <dt>toA</dt><dd>probability of mutation to adenine</dd>
 <dt>toC</dt><dd>probability of mutation to cytosine</dd>
 <dt>toG</dt><dd>probability of mutation to guanine</dd>
 <dt>toT</dt><dd>probability of mutation to thymine</dd>
 <dt>Source</dt><dd>source of probability</dd>
</dl>

hotspot_df: Hotspot dataframe for SHM

Description

Usage

Arguments

Format