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.
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)