explore_features: Plots repertoire features for binding versus non binding...

In rodamian/Bindpred: package for antibody specificity and affinity prediction

Description

Plots repertoire features for binding versus non binding cells. This can be done both at the clonotype level or at the single cell level.

Usage

explore_features(features, per.sample = T, combined = T)

Arguments

features	List of dataframes containing the extracted features. This is the output of load_data function.
per.sample	Logical indicating if the plots produced are separated by sample or aggregated.
combined	Logical indicating if the plots produced are combined in a single publication ready plot.

Value

This function plots the mean mutation for each cell (divided in Heavy chain and Light chain mutations), gene usage, CDR3 length, and the ratio between coding versus non-coding mutations.

Examples

## Not run: 
check_explore_features <- explore_features(features = output.load_data, per.sample = T, combined = T)

## End(Not run)

rodamian/Bindpred documentation built on July 29, 2021, 7:29 p.m.