azulejo 0.9.2

tile phylogenetic space with subtrees

azulejo noun INFORMAL a glazed tile, usually blue, found on the inside of churches and palaces in Spain and Portugal.

azulejo

azulejo azulejo tiles phylogenetic space with subtrees normalizes and validates genomic data files prior to further processing or inclusion in a data store such as that of the Legume Federation.

Prerequisites

Python 3.6 or greater is required. This package is tested under Linux using Python 3.8. azulejo relies on usearch for clustering, which you must download and install manually due to licensing restrictions (free download, no registration required at the link). azulejo also uses MUSCLE and requires version 3.8.1551 or greater. MUSCLE is in the public domain and can be downloaded and built from source here.

Installation for Users

Install via pip or (better yet) pipx:

pipx install azulejo

azulejo contains some long commands and many options. To enable command-line completion for azulejo commands, execute the following command if you are using bash as your shell:

eval "$(_AZULEJO_COMPLETE=source_bash azulejo)"

For Developers

If you plan to develop azulejo, you’ll need to install the poetry dependency manager. If you haven’t previously installed poetry, execute the command:

curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python

Next, get the master branch from GitHub

git clone https://github.com/legumeinfo/azulejo.git

Change to the azulejo/ directory and install with poetry:

poetry install -v

Run azulejo with poetry:

poetry run azulejo

Usage

Installation puts a single script called azulejo in your path. The usage format is:

azulejo [GLOBALOPTIONS] COMMAND [COMMANDOPTIONS][ARGS]

Master Input File

azulejo uses a configuration file in TOML format as the master input that associates files with phylogeny. The format of this file is the familiar headings in square brackets followed by configuration values:

[glycines]
rank = "genus"
name = "Glycine"

[glycines.glyso]
rank = "species"
name = "Glycine soja"

[glycines.glyso.PI483463]
rank = "strain"
gff = "glyso.PI483463.gnm1.ann1.3Q3Q.gene_models_main.gff3.gz"
fasta = "glyso.PI483463.gnm1.ann1.3Q3Q.protein_primaryTranscript.faa.gz"
uri = "https://v1.legumefederation.org/data/index/public/Glycine_soja/PI483463.gnm1.ann1.3Q3Q/"
comments = """
Glycine soja accession PI 483463 has been identified as being unusually
salt-tolerant (Lee et al., 2009)."""

• [headings]

  There can be only one top-level heading, and that will be the name of the resulting output set. This name will be the name of an output directory that will be created in the current working directory, so this heading (and all subheadings) must obey UNIX filesystem naming rules or an error will result. Each heading level (indicated by a “.”) will result in another taxonomic level and another directory level in the output directory. Depths do not need to be consistent.

• rank

  Each level defined must have a rank defined, and that rank must match one of the taxonomic ranks defined by azulejo, which you can view and test using the check-taxonomic-rank command. There are 24 major taxonomic ranks, each of which may be modified by 16 different prefixes for a total of 174 taxonomic levels (some of which are synonoymous).

• name

  Each level may (and usually should) have a name defined. This name is intended to be human-readable with no restrictions on the characters used, but it goes into plot legends in places, so it’s best to not make it too long. If the name is not specified, it will be taken from the level name enclosed in single quotes (e.g., ‘PI483463’ for the example above).

• fasta

  If the level specifies a genome, it must have a fasta entry corresponding to the name of the protein FASTA file. In eukaryotes, the FASTA file should be a file of primary (generally longest) protein transcripts, if available, rather than all protein transcripts (i.e., not including splice variants). Sequences will be cleaned of dashes, stops, and other out-of-alphabet characters. Ambiguous residues at the beginnings and ends of sequences will be trimmed. Zero-length sequences will be discarded, which can result in a smaller number of sequences out. These files may be compressed, with extensions .gz or .bz2.

• gff

  If the level specifies a genome, it must have a gff entry corresponding to a version 3 Genome Feature File (GFF3) containing CDS entries with ID values matching those IDs in the FASTA file. The same compression extensions as for fasta entries apply. If the SOURCE fields in those CDS entries (which contain the names of the DNA fragments such as scaffolds that the CDS came from) contain dot-separated components, those components that are identical across the entire file will be discarded by default. There is an opportunity later in the process to remap DNA source names to a common dictionary for comparison among chromosomes and plastids.

• uri

  This optional field may contain a a uniform resource identifier such as https://sitename/dir/. azulejo uses smart-open for doing transparent on-the-fly decompression from a variety of file systems including HTTPS, HDFS, SSH, and SFTP (but not FTP). If this field is not supplied, local file access is assumed with paths relative to the current working directory. The URI will be prepended to fasta and gff paths, allowing for convenient downloading on-the-fly from sites such as LegumeInfo or GenBank. Downloads are not cached, so if you intend to run azulejo multiple times on the same input data, you will save time by downloading and uncompressing files to local storage.

• preference

  This optional field may be used to override the genome preference heuristic that is the fall-thru preference after proxy-gene heuristics have been applied. This is an integer value, with lower integers getting the highest priority. Set this value to zero if you know in advance that one of the input genomes is considered the reference genome and, all things being equal, you would prefer to select proxy genes from this genome. You may also set these preference values later, after the default genome preference (genomes will be preferred in order of the most genes in a single DNA fragment) has already been applied, but before proxy gene selection.

• other info

  A design goal for azulejo was to not lose metadata, even if it was not used by azulejo itself, while keeping metadata out of file names. As an aid in that goal, for each (sub)heading level/output directory, azulejo creates a JSON file named node_properties.json at each node in the output hierarchy that containing all information from this file as well as other information calculated at ingestion time by azulejo. You may specify any additional data you would like to pass along (e.g., for later use in a web page) and it will be translated from TOML to JSON and passed along, such as the multi-line comments field in the example. Examples of useful metadata that may be easier to enter at ingestion time than to garner later include taxon IDs of the level and its parent, common names, URLs of papers describing the genome, and geographic origin of the sample.

A copy of the input file will be saved in the output directory under the name input.toml. See the examples in the tests/testdata repository directory for examples of input data.

Global Options

The following options are global in scope and, if used must be placed before COMMAND:

-v, –verbose	Log debugging info to stderr.
-q, –quiet	Suppress logging to stderr.
–no-logfile	Suppress logging to file.
-e, –warnings_as_errors	Treat warnings as fatal (for testing).

Commands

A listing of commands is available via azulejo --help. The currently implemented commands are:

analyze-clusters	Statistics of clustering as function of identity.
calculate-proxy-genes	Calculate a set of proxy genes from synteny files.
change-compression	Change the compression type of a Parquet file.
check-taxonomic-rank	Check/show a lit of taxonomic ranks.
cluster-in-steps	Cluster in steps from low to 100% identity.
clusters-to-histograms	Compute histograms from cluster file.
combine-clusters	Combine synteny and homology clusters,
compare-clusters	compare one cluster file with another
dagchainer-synteny	Read DAGchainer synteny into homology frames.
do-homology	Calculate homology clusters, MSAs, trees.
ingest-sequence-data	Marshal protein and genome sequence information.
length-std-dist	Plot length distribution of singletons in clusters
outlier-length-dist	Plot length distribution of outliers in clusters.
parquet-to-tsv	Reads parquet file, writes tsv.
prepare-protein-files	Sanitize and combine protein FASTA files.
proxy-genes	Calculate a set of proxy genes from synteny files.
synteny-anchors	Calculate synteny anchors.
usearch-cluster	Cluster at a global sequence identity threshold.

Each command has its COMMANDOPTIONS, which may be listed with:

azulejo COMMAND --help

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