one_spot_df

A dataframe containing a mutation probabilities to base per 5mer
(inherited from AbSim package)

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

one_spot_df function

A dataframe with 32 entries:<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

One Spot — one_spot_df

A dataframe with 32 entries:<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>

one_spot_df: One Spot

Description

Usage

Arguments

Format