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ktmeaton/NCBImeta

Efficient and comprehensive metadata acquisition from NCBI databases (includes SRA).

License: MIT Build Status codecov status GitHub issues PyPI version Anaconda-Server Badge

Why NCBImeta?

NCBImeta is a command-line application that retrieves and organizes metadata from the National Centre for Biotechnology Information (NCBI). While the NCBI web browser experience allows filtered searches, the output does not facilitate inter-record comparison or bulk record retrieval. NCBImeta tackles this issue by creating a local database of NCBI metadata constructed by user-defined search criteria and customizable metadata columns. The output of NCBImeta, optionally a SQLite database or text files, can then be used by computational biologists for applications such as record filtering, project discovery, sample interpretation, or meta-analyses of published work.

Requirements

  • NCBImeta is written in Python 3 and supported on Linux and macOS.
  • Dependencies that will be installed are listed in requirements.txt.
  • Python Versions:
    • 3.7
    • 3.8
    • 3.9
  • Operating Systems:
    • Ubuntu
    • macOS

Conda is the recommended installation method. To install with pip, gcc is required.

Installation

There are three installation options for NCBImeta:

1. Conda*

* mamba is strongly recommended over conda!

conda env create -f environment.yaml
conda activate ncbimeta

2. PyPI*

* gcc is required.

pip install ncbimeta

3. Github

git clone https://github.com/ktmeaton/NCBImeta.git
cd NCBImeta
pip install .

Test that the installation was successful:

NCBImeta --version

Command-Line Parameters

usage: NCBImeta [-h] --config CONFIGPATH [--flat] [--version]
                   [--email USEREMAIL] [--api USERAPI]
                   [--force-pause-seconds USERFORCEPAUSESECONDS]

NCBImeta: Efficient and comprehensive metadata retrieval from the NCBI
databases.

optional arguments:
  -h, --help            show this help message and exit
  --config CONFIGPATH   Path to the yaml configuration file (ex. config.yaml).
  --flat                Don't create sub-directories in output directory.
  --version             show program's version number and exit
  --email USEREMAIL     User email to override parameter in config file.
  --api USERAPI         User API key to override parameter in config file.
  --force-pause-seconds USERFORCEPAUSESECONDS
                        FORCE PAUSE SECONDS to override parameter in config
                        file.
  --quiet               Suppress logging of each record to the console.

Quick Start Example

Access the quick start config file

Download the NCBImeta github repository to get access to the example configuration files:

git clone https://github.com/ktmeaton/NCBImeta.git
cd NCBImeta

Run the program

Download a selection of genomic metadata pertaining to the plague pathogen Yersinia pestis.

NCBImeta --flat --config test/test.yaml

(Note: The 'quick' start config file forces slow downloads to accommodate users with slow internet. For faster record retrieval, please see the config file docs to start editing config files.)

Example output of the command-line interface (v0.6.1): asciicast

Annotate the database with the user's custom metadata

NCBImetaAnnotate \
  --database test/test.sqlite \
  --annotfile test/test_annot.txt \
  --table BioSample

Note that the first column of your annotation file MUST be a column that is unique to each record. An Accession number or ID is highly recommended. The column headers in your annotation file must also exactly match the names of your columns in the database.

NCBImetaAnnotate by default replaces the existing annotation with the data in your custom metadata file. Alternatively, the flag --concatenate can be specified. This will concatenate your custom metadata with the pre-existing value in the database cell (separated by a semi-colon).

NCBImetaAnnotate \
  --database test/test.sqlite \
  --annotfile test/test_annot.txt \
  --table BioSample \
  --concatenate

Join NCBI tables into a unified master table

NCBImetaJoin \
  --database test/test.sqlite \
  --final Master \
  --anchor BioSample \
  --accessory "BioProject Assembly SRA Nucleotide" \
  --unique "BioSampleAccession BioSampleAccessionSecondary BioSampleBioProjectAccession"

The rows of the output "Master" table will be from the anchor table "BioSample", with additional columns added in from the accessory tables "BioProject", "Assembly", "SRA", and "Nucleotide". Unique accession numbers for BioSample (both primary and secondary) and BioProject allow this join to be unambiguous.

Export the database to tab-separated text files by table.

NCBImetaExport \
  --database test/test.sqlite \
  --outputdir test

Each table within the database will be exported to its own tab-separated .txt file in the specified output directory.

Explore!

  1. Explore your database text files using a spreadsheet viewer (Microsoft Excel, Google Sheets, etc.)
  2. Browse your SQLite database using DB Browser for SQLite (https://sqlitebrowser.org/)
  3. Use the columns with FTP links to download your data files of interest.

Example database output (a subset of the BioSample table)

NCBImetaDB

Currently Supported NCBI Tables

  • Assembly
  • BioProject
  • BioSample
  • Nucleotide
  • SRA
  • Pubmed

Recent and Upcoming Features

Documentation

To get started with customizing the search terms, database, and metadata fields, please read:

  1. Config File Docs
  2. Schema File Docs

Issues, Questions, and Suggestions

Please submit your questions, suggestions, and bug reports to the Issue Tracker.

Please do not hesitate to post any manner of curiosity in the "Issues" tracker :) User-feedback and ideas are the most valuable resource for emerging software.

GitHub not your style? Join the NCBImeta Slack Group to see release alerts, chat with other users, and get insider perspective on development.

Contributing

Want to add features and fix bugs? Check out the Contributor's Guide for suggestions on getting started.

Citation

Eaton, K. (2020). NCBImeta: efficient and comprehensive metadata retrieval from NCBI databases. Journal of Open Source Software, 5(46), 1990, https://doi.org/10.21105/joss.01990

Authors

Author: Katherine Eaton ([email protected])

Additional Contributors

Those who have filed issues, pull-requests, and participated in discussions.

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