Skip to main content

A Python tool for fetching metadata for bacterial genomes.

Project description

FetchM: Metadata Fetching and Analysis Tool

Overview

FetchM is a Python-based tool for fetching and analyzing genomic metadata from NCBI BioSample records. When you download ncbi_dataset.tsv from the NCBI genome database, the metadata fields such as 'Collection Date', 'Host', 'Geographic Location', and 'Isolation Source' are missing. This tool helps fetch the associated metadata for each BioSample ID. FetchM requires an input file (ncbi_dataset.tsv) from the NCBI genome database, retrieves additional annotations from NCBI, filters the data based on quality thresholds, and generates visualizations to help interpret the results. You can also download the filtered sequences.

Features

  • Fetch metadata from NCBI BioSample API.
  • Filter genomes based on CheckM completeness and ANI check status.
  • Generate metadata summaries and annotation statistics.
  • Create various visualizations for geographic distribution, collection dates, gene counts, continent, and subcontinent.
  • Download genome sequences (optional).
  • Download sequences after filtering by host species, year, country, continent, and subcontinent.

Installation

Install in a New Conda Environment

conda create -n fetchm python=3.9
conda activate fetchm
pip install fetchM

Usage

Run FetchM with the following command:

fetchM --input input.tsv --outdir results/

For retrieving all available sequence data

fetchM --input input.tsv --outdir results/ --checkm 0 --ani all

For downloading sequences with sequence information

fetchM --input input.tsv --outdir results/ --seq

For downloading filtered sequences add the available Options below:

Options:

  • --checkm CHECKM (Minimum CheckM completeness threshold, default: 95)
  • --ani (Filter genomes by ANI status. Choices: OK, Inconclusive, Failed, all. Default is OK)
  • --sleep (Time to wait between requests, default: 0.5s)
  • --seq (Enable sequence download mode)

Downloading sequences based on different criteria

  • --host HOST [HOST ...] (Filter by host species, e.g., "Homo sapiens" "Bos taurus")
  • --year YEAR [YEAR ...] (Filter by year or year range, e.g., "2015" "2018-2025")
  • --country COUNTRY [COUNTRY ...] (Filter by country, e.g., "Bangladesh" "United States")
  • --cont CONT [CONT ...] (Filter by continent, e.g., "Asia" "Africa")
  • --subcont SUBCONT [SUBCONT ...] (Filter by subcontinent, e.g., "Southern Asia" "Western Africa")

Input

Download ncbi_dataset.tsv of your target organism(s) from the NCBI genome database. -ncbi_dataset.tsv

📋 Required Columns for ncbi_dataset.tsv in FetchM

Before running FetchM, ensure that your ncbi_dataset.tsv file includes the following columns. These columns are necessary for metadata enrichment, quality filtering, and downstream analysis.


🧬 Required Columns

Column Name Description
Assembly Accession Unique identifier for the assembly
Assembly Name Name of the genome assembly
Organism Name Scientific name of the organism
ANI Check status Status of Average Nucleotide Identity (ANI) check
Annotation Name Annotation version or label used
Assembly Stats Total Sequence Length Total length (in base pairs) of all sequences in the assembly
Assembly BioProject Accession Accession ID for the related BioProject
Assembly BioSample Accession Accession ID for the related BioSample
Annotation Count Gene Total Total number of genes annotated
Annotation Count Gene Protein-coding Number of protein-coding genes
Annotation Count Gene Pseudogene Number of pseudogenes
CheckM completeness Completeness score from CheckM (in %)
CheckM contamination Contamination score from CheckM (in %)

✅ Tips

  • The file must be tab-separated (.tsv format).
  • Don't change Column headers

Output

FetchM creates a subdirectory in /results/ based on the organism name provided in the input file. Inside this subdirectory, the following folders are created:

  • Metadata summaries in metadata_output/
    • annotation_summary.csv
    • assembly_summary.csv
    • metadata_summary.csv
    • ncbi_clean.csv
    • ncbi_filtered.csv
    • ncbi_dataset_updated.tsv
  • Figures in figures/
    • Annotation Count Gene Protein-coding_distribution.tiff
    • Annotation Count Gene Pseudogene_distribution.tiff
    • Annotation Count Gene Total_distribution.tiff
    • Assembly Stats Total Sequence Length_distribution.tiff
    • Collection Date_bar_plots.tiff
    • Continent_bar_plots.tiff
    • Geographic Location_bar_plots.tiff
    • Geographic Location_map.jpg
    • Host_bar_plots.tiff
    • scatter_plot_gene_protein_coding_vs_collection_date.tiff
    • scatter_plot_gene_total_vs_collection_date.tiff
    • scatter_plot_total_sequence_length_vs_collection_date.tiff
    • Subcontinent_bar_plots.tiff
  • Sequences in sequences/ (if --seq is enabled, it will contain the downloaded genome sequences).

Visualizations

Annotation Distributions

Annotation Count Gene Protein-coding Annotation Count Gene Pseudogene Annotation Count Gene Total

Assembly Statistics

Assembly Sequence Length

Metadata Summaries

Collection Date Distribution Geographic Location Map Geographic Location Distribution Host Distribution Continent Distribution Subcontinent Distribution

Scatter Plots

Gene Protein Coding vs Collection Date Gene Total vs Collection Date Sequence Length vs Collection Date

License

This project is licensed under the MIT License.

Author

Developed by Tasnimul Arabi Anik.

Contributions

Contributions and improvements are welcome! Feel free to submit a pull request or report issues.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fetchm-0.1.6.tar.gz (16.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

fetchM-0.1.6-py3-none-any.whl (14.7 kB view details)

Uploaded Python 3

File details

Details for the file fetchm-0.1.6.tar.gz.

File metadata

  • Download URL: fetchm-0.1.6.tar.gz
  • Upload date:
  • Size: 16.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.3

File hashes

Hashes for fetchm-0.1.6.tar.gz
Algorithm Hash digest
SHA256 273c82bda3b8a9de900b29d3d66713d0716dab94b58e142cf346c0c0af40314e
MD5 e52089448e7472b48e43dba23de39e33
BLAKE2b-256 6c95f90169e537903722ccf04a2449363f24a328cdd9773cd7ee7c39f307c1ab

See more details on using hashes here.

File details

Details for the file fetchM-0.1.6-py3-none-any.whl.

File metadata

  • Download URL: fetchM-0.1.6-py3-none-any.whl
  • Upload date:
  • Size: 14.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.3

File hashes

Hashes for fetchM-0.1.6-py3-none-any.whl
Algorithm Hash digest
SHA256 3b7398f130442997d5758df9d9d3dd0b32886999e52e9fd16d249a29098fc54a
MD5 fbf81d832ea60cd254606252e24bfbd5
BLAKE2b-256 59ef7beacb7c914f5833cae7325e24213e964e56cdb83acb66847ebfb9f29b46

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page