Agglomerative Clustering Tree Builder

Generate phylogenetic trees using hierarchical agglomerative clustering from sequence data

Clustering Options

Hamming Distance
Jukes-Cantor
Kimura 2-parameter

Distance Matrix

What is Agglomerative Clustering?

Agglomerative clustering is a hierarchical clustering method used in phylogenetic analysis. It builds trees by iteratively merging the closest clusters based on distance metrics, creating a dendrogram that shows evolutionary relationships between sequences.

How to Use This Tree Builder

Build phylogenetic trees in three steps:

  1. Paste multiple sequences in FASTA format
  2. Select linkage method and distance metric
  3. View Newick tree and distance matrix

When to Use

This tool is useful when you need to:

  • Build phylogenetic trees from sequence data
  • Analyze evolutionary relationships
  • Compare different clustering methods

Example Input

Sample sequences in FASTA format:

>Species_A ATCGATCGATCG >Species_B ATCGATCAATCG >Species_C ATCAATCGATCG

Try with your own sequences or use the Example button.

Example Output

Newick tree format:

((Species_A:0.042,Species_B:0.042):0.083,Species_C:0.125);

Can be visualized in tree viewing software.

FAQ

Q: What is UPGMA?
A: Unweighted Pair Group Method with Arithmetic Mean - the most common linkage method for phylogenetics.

Q: Which distance metric should I use?
A: Hamming for simple differences, Jukes-Cantor or Kimura for evolutionary models.