A python command-line utility for the generation of comprehensive reports on the quality of ribosome profiling (Ribo-Seq) datasets
Free software: MIT license
Documentation: https://RiboMetric.readthedocs.io.
Installation
To install RiboMetric:
$ pip install RiboMetric
For PDF export support (adds ~30 dependencies):
$ pip install RiboMetric[pdf]
Usage
Create annotation files from gff files:
$ RiboMetric prepare -g gff_file.gff
Use the annotation file to run RiboMetric on a bam file:
$ RiboMetric run -b bam_file.bam -a annotation_RiboMetric.tsv
By default, RiboMetric calculates standard Ribo-Seq QC metrics. To enable optional (theoretical) metrics:
$ RiboMetric run -b bam_file.bam -a annotation_RiboMetric.tsv --enable-optional-metrics
Or enable specific metrics:
$ RiboMetric run -b bam_file.bam -a annotation_RiboMetric.tsv --enable-metric periodicity_fourier
For more information on how to use RiboMetric, see the documentation or use --help
Features
RiboMetric calculates comprehensive quality metrics for Ribo-Seq data:
- Default Metrics (Standard Ribo-Seq QC):
Read length distribution (IQR, coefficient of variation, max proportion)
Terminal nucleotide bias (5’ and 3’ ligation bias detection)
3-nt periodicity (frame dominance and information content)
Metagene uniformity (entropy-based)
CDS coverage
Regional distribution (5’UTR, CDS, 3’UTR proportions and ratios)
- Optional Metrics (Theoretical/Experimental):
Alternative periodicity methods (autocorrelation, Fourier transform, Trips-Viz)
Alternative uniformity methods (autocorrelation, Theil index, Gini index)
Additional read length metrics (bimodality, normality tests)
Use --enable-optional-metrics to calculate all metrics, or --enable-metric <name> for specific ones.
Output Formats
RiboMetric provides multiple output formats for different use cases:
- For Pipeline Integration:
Summary TSV - One-line summary per sample for quick QC decisions
QC Status JSON - Machine-readable pass/warn/fail with thresholds
Comparison CSV - Wide format for multi-sample comparison
- For Sample Review:
Interactive HTML - Professional reports with executive summary and searchable metrics
PDF - Archivable reports for documentation
Metrics Table CSV - Detailed metrics with read-length breakdowns
See REPORTING_GUIDE.md for complete documentation and examples.
Requirements
Transcriptomic alignments are required in BAM format
GFF annotations from Ensembl are also required
Testing
RiboMetric has a comprehensive test suite to ensure reliability:
$ pip install -r requirements_test.txt
$ pytest
For more information, see TESTING.md
Credits
This project was worked on by Lukas Wierdsma during his Internship at the UCC for Bioinformatics, Howest in 2023.
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
Metadata
Release files for ribometric 0.1.13
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| ribometric-0.1.13.tar.gz | 44.7 MB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ribometric-0.1.13-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 44.8 MB
Release files / ribometric-0.1.13.tar.gz
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