Aksha

Fast HMM-based annotation for genomes and metagenomes.

Aksha accelerates HMM-based sequence searches so you can spend more time on biology and less time waiting for annotations. Built on HMMER and PyHMMER, it combines fast CPU searches, optional NVIDIA GPU acceleration, database management and sequence retrieval in one command-line tool.

Aksha outperformed MetaCerberus 1.4 in our Pfam benchmarks on both CPU and GPU.

More than a fast search

• Search proteins or nucleotide sequences using supported databases or your own HMMs.
• Download and manage databases such as Pfam and KOfam from the same tool.
• Use a database's recommended cutoffs, or choose your own score and E-value thresholds.
• Export tabular results and optionally retrieve matching sequences for downstream analysis.

Installation

The PyPI release is being prepared. Once published:

python -m pip install aksha
# With optional GPU support:
python -m pip install 'aksha[gpu]'

Currently supported: Linux x86-64 with Python 3.12. GPU use requires a compatible NVIDIA GPU and driver. ARM, macOS and Windows are not yet supported. See the installation guide for hardware requirements, local-wheel installation and GPU setup.

Quick start

Download the Pfam protein-family database, then search your protein sequences:

aksha initialize --hmms PFAM
aksha search --prot_in proteins.faa --installed_hmms PFAM --cut_ga --outdir results

Results are written to results/. The example uses Pfam's built-in score thresholds. You can also supply your own models with --hmm_in instead of --installed_hmms. Run aksha --help or aksha search --help for more options.

The database setup guide explains available databases, storage locations and reusing existing files. For source builds, see the maintainer guide.

License

Aksha's original code is MIT-licensed; third-party components retain their own licenses. See the application license, native-code license and third-party notices.