network.default {RepertoiR}

Sequences distance network

Description

Computes pairwise string distances among repertoire's sequences and visualize similar pairs as connected nodes, each sized by its frequency.

Usage

## Default S3 method:
network(dataset, by = 1, nrow = 1000, method = "lv", ...)

Arguments

dataset

A matrix or a data frame includes row names which are used as the compared sequences. Data set's numeric values determine node-size.

by

Index of column to set its values as node-size. first column is default (1).

nrow

Number of nodes to display. Default is 1000 nodes.

method

stringdist method to perform for distance dissimilarity calculation: "osa", "lv", "dl", "hamming", "lcs", "qgram", "cosine", "jaccard", "jw", "soundex". Default is Levenshtein distance ("lv").

...

Any additional arguments needed by the specialized methods.

Value

No return value.

Examples

aa <- c(
  "G", "A", "V", "L", "I", "P", "F", "Y", "W", "S",
  "T", "N", "Q", "C", "M", "D", "E", "H", "K", "R"
)
data <- matrix(rexp(1 / 2, n = 1000), ncol = 4)
cons <- sample(aa, 10)
aavec <- c()

while (length(aavec) < nrow(data)) {
  aaseq <- cons
  index <- sample(length(aaseq), sample(length(aaseq) / 3, 1))
  aaseq[index] <- sample(aa, length(index), replace = TRUE)
  aaseq <- paste0(aaseq, collapse = "")
  aavec <- unique(append(aavec, aaseq))
}

rownames(data) <- aavec
colnames(data) <- LETTERS[1:ncol(data)]

network(data)