---
id: abnumber
version: "0.4.4"
license: MIT
license_treatment: permissive
maintenance: aging
---

# abnumber — AbNumber - Antibody numbering using ANARCI

License: permissive · Maintenance: aging · Downloads: 78.6K/mo

## What it is and what it does

AbNumber wraps ANARCI to provide a Python-friendly interface for antibody sequence analysis. It lets you load an antibody sequence into a Chain object, then identify CDR regions, access positions using standard antibody numbering schemes (IMGT, Chothia), slice and iterate over sequences by position, and align sequences to each other or to human germlines. The package handles the complexity of ANARCI's command-line interface and sequence alignment logic, exposing it through object methods like chain.cdr3_seq, chain.regions, and chain.align().

The core use case is immunology and antibody engineering workflows where you need to work with antibody sequences in their standard numbering systems rather than raw coordinates. It depends on biopython for sequence handling, pandas for data manipulation, and anarcii for the underlying numbering and alignment engine. The package requires Python 3.6 or later and runs only on Unix and macOS due to HMMER dependencies.

Use it for:

- Extract and analyze CDR regions from antibody sequences for epitope prediction or humanization design.
- Align antibody sequences to nearest human germlines to assess how close a candidate is to natural repertoire.
- Graft CDRs from one antibody onto a human germline framework for humanization workflows.
- Index and slice antibody sequences by standard numbering (e.g., chain['H2':'H5']) for position-specific analysis.
- Batch-process antibody libraries to identify conserved regions or perform comparative sequence analysis.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

AbNumber provides Python APIs to number and align antibody sequences using ANARCI, enabling CDR region identification, sequence indexing by antibody numbering schemes, and alignment to human germlines.

Yes, if you work with antibody sequences and need standard numbering and alignment. The low install friction, permissive license, and clean API make it straightforward to adopt. However, note the aging maintenance status (452 days since last release) and Unix/macOS-only requirement. For production immunology pipelines, verify that anarcii remains stable and that the package's dependencies are current before committing to it.

## Install

pip install abnumber
uv add abnumber
poetry add abnumber

## Installing abnumber

Before you install: Low friction install as a pure Python wheel. Maintenance status is aging—last release was 452 days ago—but the repository remains active and unarchived with 128 stars. Note: Windows is not supported due to HMMER dependency; Unix and macOS only.

License in practice: MIT license is permissive, allowing commercial and private use with minimal restrictions. No licensing friction for most use cases.

Quickstart:

from abnumber import Chain

seq = 'QVQLQQSGAELARPGASVKMSCKASGYTFTRYTMHWVKQRPGQGLEWIGYINPSRGYTNYNQKFKDKATLTTDKSSSTAYMQLSSLTSEDSAVYYCARYYDDHYCLDYWGQGTTLTVSSAKTTAPSVYPLA'
chain = Chain(seq, scheme='imgt')
print(chain.cdr3_seq)  # ARYYDDHYCLDY

Windows is not supported; HMMER dependency requires Unix or macOS.

Verify before relying:

- Whether anarcii (the runtime dependency) is a maintained fork or wrapper of ANARCI, and its current stability status.
- Performance characteristics when processing large antibody sequence batches or multiple alignments.
- Whether the package is actively maintained or in maintenance-only mode given the 452-day gap since last release.

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: aging
- Downloads: 78.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

antibody numbering python, CDR region identification, immunoglobulin sequence analysis, antibody sequence alignment, ANARCI wrapper, antibody humanization, immunology bioinformatics, bioinformatics, antibody-engineering, immunology

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