BigDataBiology / GMSC-api

GMSC API

API Endpoints

• https://{{base_url}}/v1/seq-info/{{gmsc_id}}

Where {{gmsc_id}} is of the form GMSC10.100AA.xxx_xxx_xxx or GMSC10.90AA.xxx_xxx_xxx.

Returns

{
    "id": "GMSC10.xxAA.xxx_xxx_xxxx",
    "nucleotide": "ATC...",
    "aminoacid": "MAV...",
    "taxonomy": "s__Bacteroides_vulgatus",
    "habitat": "human gut"
}

• https://{{base_url}}/v1/seq-info-multi/

This is a POST-only endpoint, expecting a JSON package consisting of a dictonary with an entry seq_ids, which is a list of strings (identifiers). For example:

{
    "seq_ids": [
            "GMSC10.90AA.123_456_789",
            "GMSC10.90AA.123_456_790",
            ...]
}

Returns a list of entries like the outputs of seq-info.

• https://{{base_url}}/v1/seq-filter/

POST endpoint, with arguments:

• hq_only: boolean. Currently must be true
• habitat: str. mandatory
• taxonomy: str. optional

habitat is treated as a comma separated list (e.g., you can use marine,freshwater to match all the entities that are present in both marine and freshwater).

taxonomy is a substring match so you can pass any taxonomic level (e.g., passing o__Pelagibacterales will match d__Bacteria;p__Proteobacteria;c__Alphaproteobacteria;o__Pelagibacterales;f__Pelagibacteraceae;g__AAA240-E13).

Returns

{
    "status":"Ok",
    "results": [
            {
                "habitat":"marine,plant associated,sediment",
                "seq_id":"GMSC10.90AA.000_013_322",
                "taxonomy":"d__Bacteria"},
                ....
    ]
}

At most 1,001 entries are returned.

• https://{{base_url}}/v1/cluster-info/{{gmsc_90AA_id}}

Returns the membership of the given cluster. At most 20 results are thick (meaning that metadata is also returned). For the rest, only identifiers are returned. Example output

{
	"status":" Ok",
	"cluster": [
		{
			"aminoacid":"MAAAGFLIVSFKPFEKPSRNAATTAGFSAENFEFTMIALPYSLRP",
			"habitat":"soil",
			"nucleotide":"ATGGCCGCGGCCGGATTCTTGATCGTGTCCTTCAAGCCTTTCGAGAAGCCTTCGAGAAACGCCGCGACGACGGCCGGCTTCTCGGCCGAGAATTTCGAGTTCACGATGATCGCGCTGCCGTACAGCTTGAGACCGTAA",
			"seq_id":"GMSC10.100AA.547_444_661",
			"taxonomy":"d__Bacteria;p__Proteobacteria;c__Alphaproteobacteria;o__Rhizobiales;f__Xanthobacteraceae;g__VAZQ01;s__VAZQ01 sp005883115"
		}, ...
		]
}

Sequence search interface (non-public interface)

NOTE. These are not recommended for public use. For large-scale analyses, we recommend you use the GMSC-mapper command line tool locally. Public API endpoints will be maintained for the long-term. No such commitment is made for endpoints marked internal. You have been warned.

• https://{{base_url}}/internal/seq-search (POST)

Arguments:

• sequence_faa: FASTA formatted set of sequences
• is_contigs: bool (when True, inputs are assumed to be DNA contigs)

Returns

{
    "status": "message (normally 'Ok')",
    "search-id": "xxxxx"
}

• https://{{base_url}}/internal/seq-search/{{search_id}}

Returns

{
    "search_id": "str",
    "status": "str",
    "results": [
        {
            "query_id": "query_1",
            "aminoacid": "MHEDVIQFARNEVWSLV....",
            "taxonomy": "s__Bacteroides_vulgatus",
            "habitat": "human gut",
            "hits": [
                { "id": "GMSC10.xxAA.xxx_xxx_xxxx",
                  "e_value": "2.1e-23",
                  "aminoacid": "MHEELIQFARNEV...",
                  "identity": "98.4"
                }, ...
            ]
        }, ...]

status will be one of Running (if the results are not yet ready), Done, or Expired. In the case of Done, the results field will be filled in.

Install & Testing

Dependencies

• flask
• numpy
• pandas

Running this (in test mode) can be done with

python -m flask run

Testing can be done with curl:

curl http://127.0.0.1:5000/v1/seq-info/GMSC10.100AA.000_000_002

These examples assume you are running the test version on http://127.0.0.1:5000/. Adapt as necessary.

Searching requires using POST and a FASTA file. For example, if you have the file example.faa, you can use

curl -X POST --form "sequence_faa=$(cat example.faa)" http://127.0.0.1:5000/internal/seq-search/

The output will look something like this:

{"search_id":"1-jmgi","status":"Ok"}

You can later use the given ID (in this case 1-jmgi, but it will be different every time the app runs) to retrieve the results:

curl http://127.0.0.1:5000/internal/seq-search/1-jgmi

Results will look like one of the following

1. {"search_id":"1-jmgi","status":"Running"}
2. {"search_id":"1-jmgi","status":"Done", results":[...]}
3. {"search_id":"1-jmgi","status":"Expired"}

Search ID are of the form #-xxxx where # is just an index counting up and xxxx is a random string.

Indexing

Indexing is done by the make-indices.py Jug script. It expects FASTA and other files to be present in the gsmc-db subdirectory.