read_dist: Read distance matrices

In clustur: Clustering

Read distance matrices

Description

Read in distances from a file that is formatted with three columns for the row, column, and distance of a sparse, square matrix or in a phylip-formatted distance matrix.

Usage

read_dist(distance_file, count_table, cutoff, is_similarity_matrix = FALSE)

Arguments

distance_file	Either a phylip or column distance file, or a sparse matrix. The function will detect the format for you.
count_table	A table of names and the given abundance per group. Can be in mothur's sparse or full format. The function will detect the format for you.
cutoff	The value you wish to use as a cutoff when clustering.
is_similarity_matrix	are you using a similarity matrix (default) or distance matrix?

Value

A distance 'externalptr' object that contains all your distance information. Can be accessed using 'get_distance_df()'

Examples

 i_values <- as.integer(1:100)
 j_values <- as.integer(sample(1:100, 100, TRUE))
 x_values <- as.numeric(runif(100, 0, 1))
 s_matrix <- create_sparse_matrix(i_values, j_values, x_values)

 sparse_count <- data.frame(
                 Representative_Sequence = 1:100,
                 total = rep(1, times = 100))

 column_path <- example_path("amazon_column.dist")
 phylip_path <- example_path("amazon_phylip.dist")
 count_table <- read_count(example_path("amazon.full.count_table"))

 data_column <- read_dist(column_path, count_table, 0.03)
 data_phylip <- read_dist(phylip_path, count_table, 0.03)
 data_sparse <- read_dist(s_matrix, sparse_count, 0.03)

clustur documentation built on April 15, 2025, 1:33 a.m.