Subcommand: squash

Perform Squash Clustering for a set of samples.

Usage: gappa analyze squash [options]

Options

Input
--jplace-path	Required. TEXT ... List of jplace files or directories to process. For directories, only files with the extension .jplace are processed.
Settings
--exponent	FLOAT=1 Exponent for KR integration.
--point-mass	Treat every pquery as a point mass concentrated on the highest-weight placement.
--ignore-multiplicities	Set the multiplicity of each pquery to 1.
Output
--out-dir	TEXT=. Directory to write files to
--tree-file-prefix	TEXT=tree_ File prefix for tree files
Color
--color-list	TEXT=BuPuBk List of colors to use for the palette. Can either be the name of a color list, a file containing one color per line, or an actual list of colors.
--reverse-color-list	If set, the --color-list is reversed.
--log-scaling	If set, the sequential color list is logarithmically scaled instead of linearily.
Tree Output
--write-newick-tree	If set, the tree is written to a Newick file.
--write-nexus-tree	If set, the tree is written to a Nexus file.
--write-phyloxml-tree	If set, the tree is written to a Phyloxml file.
--write-svg-tree	If set, the tree is written to a Svg file.
Svg Tree Output
--svg-tree-shape	TEXT in {circular,rectangular}=circular Shape of the tree.
--svg-tree-type	TEXT in {cladogram,phylogram}=cladogram Type of the tree.
--svg-tree-stroke-width	FLOAT=5 Svg stroke width for the branches of the tree.
--svg-tree-ladderize	If set, the tree is ladderized.

Description

Performs Squash Clustering. The command is a re-implementation of guppy squash, see there for some details.

Details

The main output of the command is a cluster hierarchy tree that shows which input jplace samples are clustered close to each other. Although the tree is written to Newick format, it is not a phylogeny, as its tips represent samples (jplace files). The inner node labels are numbered consecutively starting at n, with n being the number of samples used as input.

When one of the --write-...-tree options is used, the mass trees representing the samples (tips of the cluster tree) and the mass trees of the inner nodes (average masses of the corresponding tips) are written for visualization. Their numbering is 0 to n-1 for the tips (samples), and n to 2n-2 for the inner nodes (cluster averages). These trees can help to explore how and why the samples were clustered during the algorithm.