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3 changes: 3 additions & 0 deletions docs/acknowledgements.md
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# Acknowledgments

The [Imageomics Institute](https://imageomics.org/) is supported by the National Science Foundation under [Award No. 2118240](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118240) "HDR Institute: Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning." Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
29 changes: 29 additions & 0 deletions docs/command_line_usage/help.md
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# Help
You may view the help for the command line interface by running:

```bash
taxonopy --help
```
This will show you the available commands and options:

```
usage: taxonopy [-h] [--cache-dir CACHE_DIR] [--show-cache-path] [--cache-stats] [--clear-cache] [--show-config] [--version] {resolve,trace,common-names} ...

TaxonoPy: Resolve taxonomic names using GNVerifier and trace data provenance.

positional arguments:
{resolve,trace,common-names}
resolve Run the taxonomic resolution workflow
trace Trace data provenance of TaxonoPy objects
common-names Merge vernacular names (post-process) into resolved outputs

options:
-h, --help show this help message and exit
--cache-dir CACHE_DIR
Directory for TaxonoPy cache (can also be set with TAXONOPY_CACHE_DIR environment variable) (default: None)
--show-cache-path Display the current cache directory path and exit (default: False)
--cache-stats Display statistics about the cache and exit (default: False)
--clear-cache Clear the TaxonoPy object cache. May be used in isolation. (default: False)
--show-config Show current configuration and exit (default: False)
--version Show version number and exit
```
90 changes: 90 additions & 0 deletions docs/command_line_usage/tutorial.md
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# Command Line Tutorial

**Command ```resolve```:**
The ```resolve``` command is used to perform taxonomic resolution on a dataset. It takes a directory of Parquet partitions as input and outputs a directory of resolved Parquet partitions.
```
usage: taxonopy resolve [-h] -i INPUT -o OUTPUT_DIR [--output-format {csv,parquet}] [--log-level {DEBUG,INFO,WARNING,ERROR,CRITICAL}] [--log-file LOG_FILE] [--force-input] [--batch-size BATCH_SIZE] [--all-matches]
[--capitalize] [--fuzzy-uninomial] [--fuzzy-relaxed] [--species-group] [--refresh-cache]

options:
-h, --help show this help message and exit
-i, --input INPUT Path to input Parquet or CSV file/directory
-o, --output-dir OUTPUT_DIR
Directory to save resolved and unsolved output files
--output-format {csv,parquet}
Output file format
--log-level {DEBUG,INFO,WARNING,ERROR,CRITICAL}
Set logging level
--log-file LOG_FILE Optional file to write logs to
--force-input Force use of input metadata without resolution

GNVerifier Settings:
--batch-size BATCH_SIZE
Max number of name queries per GNVerifier API/subprocess call
--all-matches Return all matches instead of just the best one
--capitalize Capitalize the first letter of each name
--fuzzy-uninomial Enable fuzzy matching for uninomial names
--fuzzy-relaxed Relax fuzzy matching criteria
--species-group Enable group species matching

Cache Management:
--refresh-cache Force refresh of cached objects (input parsing, grouping) before running.
```
It is recommended to keep GNVerifier settings at their defaults.

**Command ```trace```**:
The ```trace``` command is used to trace the provenance of a taxonomic entry. It takes a UUID and an input path as arguments and outputs the full path of the entry through TaxonoPy.
```
usage: taxonopy trace [-h] {entry} ...

positional arguments:
{entry}
entry Trace an individual taxonomic entry by UUID

options:
-h, --help show this help message and exit

usage: taxonopy trace entry [-h] --uuid UUID --from-input FROM_INPUT [--format {json,text}] [--verbose]

options:
-h, --help show this help message and exit
--uuid UUID UUID of the taxonomic entry
--from-input FROM_INPUT
Path to the original input dataset
--format {json,text} Output format
--verbose Show full details including all UUIDs in group
```

**Command ```common-names```:**
The ```common-names``` command is used to merge vernacular names into the resolved output. It takes a directory of resolved Parquet partitions as input and outputs a directory of resolved Parquet partitions with common names.

```
usage: taxonopy common-names [-h] --resolved-dir ANNOTATION_DIR --output-dir OUTPUT_DIR

options:
-h, --help show this help message and exit
--resolved-dir ANNOTATION_DIR
Directory containing your *.resolved.parquet files
--output-dir OUTPUT_DIR
Directory to write annotated .parquet files
```

Note that the ```common-names``` command is a post-processing step and should be run after the ```resolve``` command.

## Example Usage
To perform taxonomic resolution on a dataset with subsequent common name annotation, run:
```
taxonopy resolve \
--input /path/to/formatted/input \
--output-dir /path/to/resolved/output
```
```
taxonopy common-names \
--resolved-dir /path/to/resolved/output \
--output-dir /path/to/resolved_with_common-names/output
```
TaxonoPy creates a cache of the objects associated with input entries for use with the ```trace``` command. By default, this cache is stored in the ```~/.cache/taxonopy``` directory.

## Development

See the [Wiki Development Page](https://github.com/Imageomics/TaxonoPy/wiki/Development) for development instructions.
68 changes: 68 additions & 0 deletions docs/index.md
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# TaxonoPy

Welcome! This is the initial MkDocs site for the TaxonoPy project.

TaxonoPy (taxon-o-py) is a command-line tool for creating an internally consistent taxonomic hierarchy using the [Global Names Verifier (gnverifier)](https://github.com/gnames/gnverifier)
. See below for the structure of inputs and outputs.

## Purpose
The motivation for this package is to create an internally consistent and standardized classification set for organisms in a large biodiversity dataset composed from different data providers that may use very similar and overlapping but not identical taxonomic hierarchies.

Its development has been driven by its application in the TreeOfLife-200M (TOL) dataset. This dataset contains over 200 million samples of organisms from four core data providers:

- [The Global Biodiversity Information Facility (GBIF)](https://www.gbif.org/)
- [BIOSCAN-5M](https://biodiversitygenomics.net/projects/5m-insects/)
- [FathomNet](https://www.fathomnet.org/)
- [The Encyclopedia of Life (EOL)](https://eol.org/)

The names (and classification) of taxa may be (and often are) inconsistent across these resources. This package addresses this problem by creating an internally consistent classification set for such taxa.

## Input
A directory containing Parquet partitions of the seven-rank Linnaean taxonomic metadata for organisms in the dataset. Labels should include:

- **uuid**: a unique identifier for each sample (required).
- **kingdom, phylum, class, order, family, genus, species**: the taxonomic ranks of the organism (required, may have sparsity).
- **scientific_name**: the scientific name to the most specific rank available (optional).
- **common_name**: the common (i.e. vernacular) name of the organism (optional).



See the example data in:
```

- `examples/input/sample.parquet`
- `examples/resolved/sample.resolved.parquet` (generated with `taxonopy resolve`)
- `examples/resolved_with_common_names/sample.resolved.parquet` (generated with `taxonopy common-names`)

```


## Challenges
This taxonomy information is provided by each data provider and original sources, but the classification can be:

- **Inconsistent** — between and within sources (e.g., kingdom *Metazoa* vs. *Animalia*)
- **Incomplete** — missing ranks or containing "holes"
- **Incorrect** — spelling errors, nonstandard terms, or outdated classifications
- **Ambiguous** — homonyms, synonyms, and terms with multiple interpretations

Taxonomic authorities exist to standardize classification, but:

- There are multiple authorities
- They may disagree
- A given organism may be missing from some

## Solution
TaxonoPy uses the taxonomic hierarchies provided by the TOL core data providers to query GNVerifier and create a standardized classification for each sample in the TOL dataset. It prioritizes the [GBIF Backbone Taxonomy](https://verifier.globalnames.org/data_sources/11), since this represents the largest part of the TOL dataset. Where GBIF misses, backup sources such as the [Catalogue of Life](https://verifier.globalnames.org/data_sources/1) and [Open Tree of Life (OTOL) Reference Taxonomy](https://verifier.globalnames.org/data_sources/179) are used.

## Installation
TaxonoPy can be installed with pip after setting up a virtual environment.

### User Installation with pip
To install the latest version of TaxonoPy, run:

``` bash

pip install taxonopy

```

37 changes: 37 additions & 0 deletions mkdocs.yml
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site_name: TaxonoPy
site_description: Documentation for the TaxonoPy package

repo_url: https://github.com/Imageomics/taxonopy
repo_name: Imageomics/taxonopy

nav:
- Home: index.md
- Command Line Usage:
- Tutorial: command_line_usage/tutorial.md
- Help: command_line_usage/help.md
- Acknowledgements: acknowledgements.md

theme:
name: material
features:
- navigation.tabs
- navigation.tabs.sticky
- content.code.copy
- content.code.annotate

plugins:
- search
- mkdocstrings:
handlers:
python:
paths: [src] # search packages in the src folder
options:
docstring_style: google
merge_init_into_class: true
markdown_extensions:
- admonition
- attr_list
- md_in_html
- pymdownx.blocks.caption
- pymdownx.details
- pymdownx.superfences
6 changes: 6 additions & 0 deletions pyproject.toml
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"jupyterlab",
"marimo[recommended]"
]
docs = [
"mkdocs",
"mkdocs-material",
"mkdocs-material-extensions",
"mkdocstrings-python"
]

[project.urls]
Documentation = "https://github.com/Imageomics/TaxonoPy"
Expand Down