coverage_clustering: Cluster coverage data

In RomainFeron/radsex-vis: Visualization of results from the RADSex pipeline

Description

Cluster individuals and sequences in a coverage table.

Usage

coverage_clustering(data, min.coverage = 0, max.coverage = 150,
  distance.method = "euclidean", clustering.method = "ward.D")

Arguments

data	A table of coverage obtained with the load_coverage_table function.
min.coverage	Minimum coverage value to consider a sequence present in an individual: coverage lower than this value will be set to 0 (default 0).
max.coverage	Maximum coverage allowed in an individual: coverage higher than this value will be set to this value (default 100).
distance.method	Method to use to compute the distance matrix. Possible values: "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski". See dist for details (default euclidean).
clustering.method	Method to use in the clustering. Possible values: "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or "centroid" (= UPGMC). See hclust for details (default ward.D).

Value

A list with the following elements:

data	A data frame of coverage with individuals and sequences ordered based on the clustering results
individuals	Individuals clustering results
sequences	Sequences clustering results
distribution	Distribution of coverage values

Examples

clustering_data <- coverage_clustering(data,
                                       min.coverage = 0, max.coverage = 100,
                                       distance.method = "binary", clustering.method = "complete")

RomainFeron/radsex-vis documentation built on May 23, 2019, 2:48 p.m.