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PopPUNK (cluster) (version 1.1.6)

FASTA datasets (assemblies):

Choose a model to use:

See documentation or description below for advice, if default does not work.

Number of mixture components:

Run model refinement after model fit:

Make visualisations for microreact (recommended):

Perplexity parameter for accessory plot t-SNE:

Make visualisations for cytoscape:

Select representative references:

External cluster labels to add (e.g. MLST/serotype):

Epidemiological information CSV formatted for microreact:

Minimum k-mer length:

Maximum k-mer length:

Step size between k-mer lengths:

Sketch size:

Maximum accessory distance to permit:

Ignore assembly length outliers:

What it does

PopPUNK will calculate core and accessory distance between input assemblies using variable length k-mers. A model will be fitted to all of these distances to determine genetic clusters for all inpits.

Description

The most important thing to check is that in the output plot the component (blob) closest to the origin has been correctly identified - this should be checked in the cluster/model plot output. If it has not, you may wish to try another model. Some broad advice:

DBSCAN is a good default, but may lead to unclassified points (black). If there are a large number of these consider another model.

GMM will work well with well-separated components and an appropriate choice of K (consider increasing it based on the number of components that can be seen).

The refine mode should be added in recombining species, which can be seen from the output plots if the coloured components are overlapping, or if there is a blur of points rather than discrete blobs of points..