split_to_kmers: Analysis immune repertoire kmer statistics: sequence...

In immunomind/immunarch: Bioinformatics Analysis of T-Cell and B-Cell Immune Repertoires

Analysis immune repertoire kmer statistics: sequence profiles, etc.

Description

Analysis immune repertoire kmer statistics: sequence profiles, etc.

Usage

split_to_kmers(.data, .k)

kmer_profile(.data, .method = c("freq", "prob", "wei", "self"), .remove.stop = TRUE)

Arguments

.data	Character vector or the output from getKmers.
.k	Integer. Size of k-mers.
.method	Character vector of length one. If "freq" then returns a position frequency matrix (PFM) - a matrix with occurences of each amino acid in each position. If "prob" then returns a position probability matrix (PPM) - a matrix with probabilities of occurences of each amino acid in each position. This is a traditional representation of sequence motifs. If "wei" then returns a position weight matrix (PWM) - a matrix with log likelihoods of PPM elements. If "self" then returns a matrix with self-information of elements in PWM. For more information see https://en.wikipedia.org/wiki/Position_weight_matrix.
.remove.stop	Logical. If TRUE (by default) remove stop codons.

Value

split_to_kmers - Data frame with two columns (k-mers and their counts).

kmer_profile - a matrix with per-position amino acid statistics.

Examples

data(immdata)
kmers <- getKmers(immdata$data[[1]], 5)
kmer_profile(kmers) %>% vis()

immunomind/immunarch documentation built on March 20, 2024, 12:01 p.m.