logomaker
Package for making Sequence Logos
Decision gist · record as of 2026-08-14
Yes, if you work with sequence alignments in bioinformatics. Logomaker fills a specific, well-defined role—rendering sequence logos with matplotlib—and has no known vulnerabilities. Install friction is low and the MIT license is permissive. The aging maintenance status is a minor concern but not a blocker; the package solves a stable problem and the repository remains active. Suitable for research, analysis, and visualization pipelines.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.8 or later; matplotlib and numpy must be available in the environment for rendering.
- Low install friction; depends on three common scientific libraries (matplotlib, numpy, pandas).
- Maintenance status is aging—last commit was 2026-01-06 and the package has not released since 2025-03-25, though the repository remains active and not archived.
License · maintenance · safety
permissive license (permissive) — MIT License permits unrestricted use, modification, and distribution with only attribution and liability disclaimer required—no restrictions on commercial or proprietary use.
last release 2025-03-25 (507 days) · last repo commit 2026-01-06 · 214 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 155,330 downloads/mo, #10,823 on PyPI
Alternatives
Verify before relying
pip install logomaker
import logomaker
import pandas as pd
# Create a simple sequence logo from position-weight matrix data
logo = logomaker.Logo(pd.DataFrame(...))- Whether the package handles large-scale sequence datasets efficiently or has known performance limitations.
- Current state of documentation completeness and whether examples cover common bioinformatics workflows.
- Whether the aging maintenance status reflects active use or declining adoption in the bioinformatics community.
What it is and what it does
Logomaker is a Python library for generating sequence logos—graphical representations of sequence alignments where nucleotides or amino acids are stacked at each position with heights proportional to their frequency or information content. It wraps matplotlib to render these plots with high customization, allowing researchers to visualize DNA, RNA, or protein sequence motifs and alignments. The package depends on numpy for numerical operations, pandas for data handling, and matplotlib for rendering, making it part of the standard scientific Python stack.
The library is designed for bioinformatics workflows where sequence logos are a standard communication tool—showing conserved positions, variable regions, and motif strength at a glance. It supports reading alignment data into pandas DataFrames and converting them into publication-ready visualizations. The package has been in development since 2017 and maintains support for current Python versions (3.8+), though recent maintenance activity has slowed.
Use it for
- Visualize DNA binding site motifs from ChIP-seq or SELEX experiments as stacked nucleotide logos.
- Display protein sequence conservation across multiple sequence alignments for functional domain annotation.
- Generate publication-ready sequence logos for research papers and presentations on sequence analysis.
- Explore position-specific scoring matrices (PSSMs) or information content at each alignment position.
- Create custom logos with styled fonts, colors, and annotations for bioinformatics reports.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with sequence alignments in bioinformatics.
Logomaker fills a specific, well-defined role—rendering sequence logos with matplotlib—and has no known vulnerabilities. Install friction is low and the MIT license is permissive. The aging maintenance status is a minor concern but not a blocker; the package solves a stable problem and the repository remains active. Suitable for research, analysis, and visualization pipelines.
Install
logomaker on PyPI
Before you install
Low install friction; depends on three common scientific libraries (matplotlib, numpy, pandas). Maintenance status is aging—last commit was 2026-01-06 and the package has not released since 2025-03-25, though the repository remains active and not archived.
Requires Python 3.8 or later; matplotlib and numpy must be available in the environment for rendering.
License in practice
MIT License permits unrestricted use, modification, and distribution with only attribution and liability disclaimer required—no restrictions on commercial or proprietary use.
Quickstart
pip install logomaker
import logomaker
import pandas as pd
# Create a simple sequence logo from position-weight matrix data
logo = logomaker.Logo(pd.DataFrame(...))Verify before relying
- Whether the package handles large-scale sequence datasets efficiently or has known performance limitations.
- Current state of documentation completeness and whether examples cover common bioinformatics workflows.
- Whether the aging maintenance status reflects active use or declining adoption in the bioinformatics community.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesmatplotlibnumpypandas |
| Maintenance | Aging 507 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 155,330 / month, #10,823 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3.12Topic :: Scientific/Engineering :: Bio-Informatics |
Evidence: logomaker-0.8.7-py3-none-any.whl
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