Taxtastic is a python package used to build and maintain reference packages, i.e. collections of reference trees, reference alignments, profiles, and associated taxonomic information.
A script named taxit provides a command line interface:
% taxit -h
usage: taxit [-h] [-V] [-v] [-q]
{help,add_nodes,add_to_taxtable,check,composition,create,extract_nodes,findcompany,get_descendants,get_lineage,info,lineage_table,lonelynodes,namelookup,new_database,refpkg_intersection,reroot,rollback,rollforward,rp,strip,taxids,taxtable,update,update_taxids}
...
Creation, validation, and modification of reference packages for use with
`pplacer` and related software.
positional arguments:
{help,add_nodes,add_to_taxtable,check,composition,create,extract_nodes,findcompany,get_descendants,get_lineage,info,lineage_table,lonelynodes,namelookup,new_database,refpkg_intersection,reroot,rollback,rollforward,rp,strip,taxids,taxtable,update,update_taxids}
help Detailed help for actions using `help <action>`
add_nodes Add nodes and names to a database
add_to_taxtable Add nodes to an existing taxtable csv
check Validate a reference package
composition Show taxonomic composition of a reference package
create Create a reference package
extract_nodes Extract nodes from a given source in yaml format
findcompany Find company for lonely nodes
get_descendants Returns given taxids including descendant taxids
get_lineage Calculate the taxonomic lineage of a taxid
info Show information about reference packages.
lineage_table Create a table of lineages as taxonimic names for a
collection of sequences
lonelynodes Extracts tax ids of all lonely nodes in a taxtable
namelookup Find primary name and tax_id from taxonomic names
new_database Download NCBI taxonomy and create a database
refpkg_intersection
Find the intersection of a taxtable and a refpkg's
taxonomy.
reroot Taxonomically reroots a reference package
rollback Undo an operation performed on a refpkg
rollforward Restore a change to a refpkg immediately after being
reverted
rp Resolve path; get the path to a file in the reference
package
strip Remove rollback and rollforward information from a
refpkg
taxids Convert a list of taxonomic names into a recursive
list of species
taxtable Create a tabular representation of taxonomic lineages
update Add or modify files or metadata in a refpkg
update_taxids Update obsolete tax_ids
options:
-h, --help show this help message and exit
-V, --version Print the version number and exit
-v, --verbose Increase verbosity of screen output (eg, -v is
verbose, -vv more so)
-q, --quiet Suppress output
taxtastic requires Python 3.8+. The simplest method of installing
is using pip:
pip install taxtastic
We strongly recommend installation into a virtualenv. Instructions for
installing the taxtastic package and the taxit command line
entry point in a virtualenv are as follows:
python3 -m venv taxtastic-env source taxtastic-env/bin/activate pip install -U pip pip install taxtastic
If you prefer to install from the git repository:
git clone https://github.com/fhcrc/taxtastic.git cd taxtastic python3 -m venv taxtastic-env source taxtastic-env/bin/activate pip install .
Finally, taxit can be run from a Docker image hosted in the GitHub
Container Registry. For example, to create a new sqlite database:
docker run --rm -it -v $(pwd):/opt/run --platform=linux/amd64 ghcr.io/fhcrc/taxtastic:latest taxit new_database ncbi_taxonomy.db
Note that initial database creation (at least on MacOS using amd64 emulation) is very slow using Docker and is not recommended.
This project supports both sqlite3 and postgresql as database backends. For most applications, we recommend sqlite3: some operations (particularly initial database creation) are much faster using sqlite3.
Taxtastic uses recursive common table expressions to query the
taxonomy database, which requires that the Python sqlite3 module
is built against sqlite3 library version of 3.8.3 or higher
(http://www.sqlite.org/releaselog/3_8_3.html). You can check the
version like this:
python3 -c 'import sqlite3; print(sqlite3.sqlite_version)'
Despite some recent optimizations as of version v0.10 (in which indexes and constraints are dropped before creating the taxonomy database), operations in Postgres are somewhat slower. Note that the default Postgres configuration on MacOS is likely to be quite resource constrained; consider tuning your database configuration by consulting a site such as PGTune (https://pgtune.leopard.in.ua).