seqCluster {immunarch}

Function for assigning clusters based on sequences similarity

Description

Graph clustering based on distances between sequences

Usage

seqCluster(.data, .dist, .perc_similarity, .nt_similarity, .fixed_threshold)

Arguments

.data

The data which was used to caluculate .dist object. Can be data.frame, data.table, or a list of these objects.

Every object must have columns in the immunarch compatible format immunarch_data_format

.dist

List of distance objects produced with seqDist function.

.perc_similarity

Numeric value between 0 and 1 specifying the maximum acceptable weight of an edge in a graph. This threshold depends on the length of sequences.

.nt_similarity

Numeric between 0-sequence length specifying the threshold of allowing a 1 in n nucleotides mismatch in sequencies.

.fixed_threshold

Numeric specifying the threshold on the maximum weight of an edge in a graph.

Value

Immdata data format object. Same as .data, but with extra 'Cluster' column with clusters assigned.

Examples

data(immdata)
# In this example, we will use only 2 samples with 500 clonotypes in each for time saving
input_data <- lapply(immdata$data[1:2], head, 500)
dist_result <- seqDist(input_data)
cluster_result <- seqCluster(input_data, dist_result, .fixed_threshold = 1)