necom Documentation

Cluster entries using DBSCAN.

Input:

• A pairwise distance TSV file (name1\tname2\tdistance). Lower distances indicate higher similarity.

Output:

• --format cluster (default): each line contains points of one cluster.
• --format pair: each line contains a (representative, member) pair.

Notes:

• The input must contain distances, not similarities.
• --eps <V>: neighborhood radius (default: 0.05).
• --min-points <N>: minimum number of points (including the point itself) to form a dense region (default: 4).
• --min-pct <P>: alternative to --min-points; specify the minimum as a fraction of the total number of samples (range (0, 1]). The effective value is ceil(P * n_samples). Mutually exclusive with --min-points.
• --same <V>: default score of identical element pairs (default: 0.0).
• --missing <V>: default score of missing pairs (default: 1.0).
• The representative point is selected by --rep:
  • medoid (default): point with minimum sum of distances to other cluster members.
  • first: alphabetically first member.
• In cluster format, the representative is placed first; in pair format, it is the first column.
• Noise points (points not assigned to any density cluster) are emitted as single-member clusters. In pair format this appears as Name <tab> Name.
• The neighborhood count used by --min-points includes the point itself when --same is 0.0 (default), because self-distance is then 0 and is always <= eps. Setting --same to a value greater than eps excludes the point from its own neighborhood.
• To scan eps values and compare internal metrics, use necom clust scan-dbscan.

Examples:

1. Run DBSCAN with defaults necom clust dbscan pairs.tsv

2. Set epsilon and min-points (min-points default: 4; here set to 5) necom clust dbscan pairs.tsv --eps 0.05 --min-points 5

3. Use –min-pct instead of –min-points necom clust dbscan pairs.tsv --min-pct 0.1

4. Output as pairs necom clust dbscan pairs.tsv --format pair