RUST
Unit step transformation of Ribo-Seq data
Decision gist · record as of 2026-08-14
No. The project is abandoned (last commit March 2023, over 1200 days ago) with no maintenance signal and zero repository stars. While the MIT license is permissive and installation friction is low, the lack of active maintenance means bugs, security issues, or compatibility problems with current dependency versions will not be fixed. For active Ribo-seq analysis work, seek a maintained alternative or fork.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.8 or later; pysam may require system-level dependencies
- Installation is straightforward with low friction.
- However, the project is abandoned as of March 2023 with no recent maintenance, and the last release was over 1200 days ago, meaning any bugs or compatibility issues discovered will not be addressed.
License · maintenance · safety
MIT license (permissive) — MIT license is permissive, allowing free use, modification, and distribution with minimal restrictions, making it suitable for academic and commercial projects.
last release 2023-05-02 (1200 days) · last repo commit 2023-03-30
0 known vulnerabilities (OSV.dev, 2026-08-14) · 276,812 downloads/mo, #8,157 on PyPI
Alternatives
Verify before relying
pip install RUST
import RUST
# Apply unit step transformation to Ribo-seq data- Whether pysam, matplotlib, and numpy versions have known compatibility constraints with Python 3.10
- Whether the package has been tested against current versions of its dependencies
- Specific performance characteristics or scalability limits for large Ribo-seq datasets
- Exact API surface and usage patterns beyond the installation documentation provided
What it is and what it does
RUST is a normalization method for ribosome profiling (Ribo-seq) data that addresses the characteristic problem of high-density peaks and alignment gaps in ribosome footprint measurements. It implements a unit step transformation designed to reduce the impact of data heterogeneity and noise, making it easier to identify which mRNA sequence features correlate with ribosome footprint densities.
The package depends on pysam for sequence alignment handling, matplotlib for visualization, and numpy for numerical computation. It targets Python 3.8 and later. The tool was developed as part of published research demonstrating that RUST outperforms other normalization techniques and can extract parameters sufficient for predicting experimental densities with high accuracy.
Use it for
- Normalize Ribo-seq datasets before analyzing how codon usage or secondary structure affects ribosome occupancy
- Perform quality control on ribosome profiling experiments to identify protocol-related artifacts before downstream analysis
- Extract normalized ribosome footprint parameters for predictive modeling of local ribosome densities
- Compare ribosome decoding rates across different mRNA regions after removing heterogeneous noise
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
No.
The project is abandoned (last commit March 2023, over 1200 days ago) with no maintenance signal and zero repository stars. While the MIT license is permissive and installation friction is low, the lack of active maintenance means bugs, security issues, or compatibility problems with current dependency versions will not be fixed. For active Ribo-seq analysis work, seek a maintained alternative or fork.
Install
rust on PyPI
Before you install
Installation is straightforward with low friction. However, the project is abandoned as of March 2023 with no recent maintenance, and the last release was over 1200 days ago, meaning any bugs or compatibility issues discovered will not be addressed.
Requires Python 3.8 or later; pysam may require system-level dependencies
License in practice
MIT license is permissive, allowing free use, modification, and distribution with minimal restrictions, making it suitable for academic and commercial projects.
Quickstart
pip install RUST
import RUST
# Apply unit step transformation to Ribo-seq dataVerify before relying
- Whether pysam, matplotlib, and numpy versions have known compatibility constraints with Python 3.10
- Whether the package has been tested against current versions of its dependencies
- Specific performance characteristics or scalability limits for large Ribo-seq datasets
- Exact API surface and usage patterns beyond the installation documentation provided
Package facts
| License | MIT license permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagespysammatplotlibnumpy |
| Maintenance | Abandoned 1,200 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 276,812 / month, #8,157 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 2 - Pre-AlphaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9 |
Evidence: RUST-1.3.1-py3-none-any.whl
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