plotDistanceVisNetwork_EC: Plotting a Distance Network (error correction)

In genBaRcode: Analysis and Visualization Tools for Genetic Barcode Data

Plotting a Distance Network (error correction)

Description

plotDistanceVisNetwork will create a graph-like visualisation (ripple plot) of the corresponding barcode sequences and their similarity based on the ggplot2 and the ggnetwork packages. The nodes represent the barcode sequences and their respective size reflects the corresponding read counts. Edges between nodes indicate a distance between two barcodes of maximal minDist. If ori_BCs is provided the effects of the error correction function will be color-coded only for those sequences.

Usage

plotDistanceVisNetwork_EC(
  BC_dat,
  BC_dat_EC,
  minDist = 1,
  loga = TRUE,
  equal_node_sizes = TRUE,
  BC_threshold = NULL,
  ori_BCs = NULL,
  complete = FALSE,
  col_type = "rainbow",
  m = "hamming"
)

Arguments

BC_dat	a BCdat object.
BC_dat_EC	the corresponding error corrected BCdat object (EC_analysis has to be TRUE)
minDist	an integer value representing the maximal distance value for which the graph will contain edges.
loga	a logical value indicating the use or non-use of logarithmic read count values.
equal_node_sizes	a logical value. If TRUE, every node will have the sames size.
BC_threshold	an integer value representing the number of barcodes for which the color-coding should be applied (starting with the barcodes with the most read counts).
ori_BCs	a vector of character strings containing the barcode sequences (without the fixed positions of the barcode construct).
complete	a logical value. If TRUE, every node will have at least one edge.
col_type	a character sting, choosing one of the available color palettes.
m	a character string, Method for distance calculation, default value is Hamming distance. Possible values are "osa", "lv", "dl", "hamming", "lcs", "qgram", "cosine", "jaccard", "jw", "soundex" (see stringdist function of the stringdist-package for more information).

Value

a visNetwork object.

genBaRcode documentation built on March 31, 2023, 11:02 p.m.