gen_code

A dataframe containing a mapping from each of 64 codons
to amino acids.

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

gen_code function

A data frame with 64 rows and variables:<dl class="dl-horizontal">
 <dt>aa</dt><dd>amino acid</dd>
 <dt>codon</dt><dd>nucleotide codon</dd>
</dl>

Format

Translation dictionary amino acid &lt;-&gt; nucleotide codon — gen_code

A data frame with 64 rows and variables:<dl class='dl-horizontal'>
 <dt>aa</dt><dd>amino acid</dd>
 <dt>codon</dt><dd>nucleotide codon</dd>
</dl>

gen_code: Translation dictionary amino acid <-> nucleotide codon

Description

Usage

Arguments

Format