gmol.base.data.seq.mmseqs_search#

Some of the code is imported from ColabFold. See:

License

MIT License

Copyright (c) 2021 Sergey Ovchinnikov

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
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Classes

MMseqs([threads, skip_existing, mmseqs])

Functions

`get_queries`(file_path[, sort_by])	Loads sequences from a specified file (CSV, TSV, or FASTA) and returns a list of tuples containing job name, sequence(s).
`mmseqs_search_monomer`(mmseqs, qdb, ...[, ...])	Run mmseqs with a local colabfold database set

class MMseqs(threads: int = 1, skip_existing: bool = True, mmseqs: str | Path = 'mmseqs')#

createdb(query_file: Path, qdb: Path, shuffle: int = 0)#

search(qdb: Path, db: Path, res: Path, tmp: Path, additional_search_param: Iterable[str | Path] | None = None)#

mvdb(src: Path, dest: Path)#

rmdb(db: Path)#

unpackdb(db: Path, dest: Path, unpack_name_mode: int = 0, unpack_suffix: str = '.a3m')#

result2msa(qdb: Path, db: Path, res: Path, dest: Path, msa_format_mode: int = 6, db_load_mode: int = 2, additional_params: Iterable[str | Path] | None = None)#

filterresult(qdb: Path, db: Path, res: Path, dest: Path, db_load_mode: int = 2, qid: str = '0', qsc: float = 0.8, diff: int = 0, max_seq_id: float = 1.0, filter_min_enable: int = 100)#

align(qdb: Path, db: Path, res: Path, dest: Path, db_load_mode: int = 2, align_eval: int = 10, max_accept: int = 1000000, alt_ali: int = 10)#

expandaln(qdb: Path, db: Path, res: Path, db2: Path, dest: Path, db_load_mode: int = 2, additional_expand_param: Iterable[str | Path] | None = None)#

lndb(src: Path, dest: Path)#

mergedbs(qdb: Path, dest: Path, *dbs: Path)#

get_queries(file_path: Path, sort_by: 'length' | 'random' = 'length') → list[tuple[str, list[str]]]#: Loads sequences from a specified file (CSV, TSV, or FASTA) and returns a list of tuples containing job name, sequence(s). The sequences can be sorted by length or shuffled randomly.

mmseqs_search_monomer(mmseqs: MMseqs, qdb: Path, output_dir: Path, uniref_db: Path, metagenomic_db: Path | None, limit: bool = True, expand_eval: float = inf, align_eval: int = 10, diff: int = 3000, qsc: float = -20.0, max_accept: int = 1000000, prefilter_mode: int = 0, s: float | None = 8, db_load_mode: int = 2, alt_ali: int = 10)#

Run mmseqs with a local colabfold database set

db1: uniprot db (UniRef30)
db3: metagenomic db (colabfold_envdb_202108 or bfd_mgy_colabfold, the former is preferred)