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NESS: Vector-based Alignment-free Sequence Search

Project description

NESS

NESS is an alignment-free tool for sequence search based on word embedding an approximate nearest neighbor (ANN) search. The tool is still under development and the code present in this repository is a proof of concept distributed under the GPL v3 license.

Installation

$ pip install ness-search

Usage

Currently the NESS CLI interface provides the following commands:

ness build_model

Creates a Word2Vec model from a multi FASTA file. For DNA sequences, use --both-strands.

$ ness build_model \
    --input swissprot.fasta \
    --output swissprot.model

ness build_database

Similarly to makeblastdb, formats a sequence database with vectors computed using a model previously built. For DNA sequences, use --both-strands.

$ ness build_database \
    --input swissprot.fasta \
    --model swissprot.model \
    --output swissprot

ness search

Similarly to the blast* programs, compares a multi FASTA file with the previously formated database.

$ ness search \
    --input sequences.fasta \
    --database swissprot \
    --output hits.csv

Cite

Kremer, FS et al (2021). NESS: an word embedding-based tool for alignment-free sequence search. Available at: https://github.com/omixlab/ness.

Acknownledgements

NESS was supported by grants from Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS) and is developed in partership with BiomeHub.

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