pysec2pri 0.2.2

Secondary to primary identifier mapping

pySec2Pri

Create and use mapping files for secondary (retired/withdrawn) biological database identifiers and labels to primary (current) identifiers and labels.

Outputs mappings in SSSOM format by default. Subjects are secondary, objects are primary.

Installation

uv pip install pysec2pri

Or install from source:

uv pip install git+https://github.com/jmillanacosta/pysec2pri.git

Quick Start

Generating mapping sets

Mapping sets can be generated from bash:

# ID mapping sets
pysec2pri chebi ids (--help)
pysec2pri ensembl ids (--help)
pysec2pri hgnc ids (--help)
pysec2pri vgnc ids (--help)
pysec2pri ncbi ids (--help)
pysec2pri hmdb-protein ids (--help)
pysec2pri hmdb-gene ids (--help)
pysec2pri uniprot ids (--help)
# Label mapping sets
pysec2pri chebi labels (--help)
pysec2pri hgnc labels (--help)
pysec2pri ensembl labels (--help)
pysec2pri vgnc labels (--help)

Or python:

from pysec2pri import generate_ensembl_labels, generate_ensembl

Replacing Ensembl by the supported database. These functions return either a IdMappingSet or LabelMappingSet, SSSOM MappingSets.

For more options and help on any command:

pysec2pri --help

The default output is in SSSOM (Simple Standard for Sharing Ontology Mappings) TSV format.

Updating IDs and labels

A generated mapping set can be used to update IDs and labels in Python: ChEBI synonyms:

from pysec2pri import generate_chebi_synonyms, resolve_labels
chebi_ms = generate_chebi_synonyms()
resolve_labels(["Glucose", "ATP", "Guanine"], cs)

Ensembl gene identifiers in a dataframe:

from pysec2pri import update_ids, generate_ensembl
ens_ms = generate_ensembl(version="115", species="9606")
df_with_new_column = update_ids(mapping_set=ens_ms, ids = df, at="Ensembl_id")  # `at` is the name of the column

Or from the command line, given a TSV file gene_ex.tsv:

gene	data
HGNC:131	3.5

Resolve the gene column to primary HGNC IDs (a new _primary column is added):

pysec2pri update-ids gene_ex.tsv hgnc --at gene -o gene_ex_primary.tsv
# gene        data    gene_primary
# HGNC:131    3.5     HGNC:145

The same pattern works for labels with update-labels, and multiple columns can be resolved by repeating --at:

pysec2pri update-ids data.tsv hgnc --at gene_id --at related_gene_id

To skip regenerating the mapping set, pass a pre-built mapping file:

pysec2pri hgnc ids  # outputs hgnc_{version}_sssom.tsv
pysec2pri update-ids gene_ex.tsv hgnc --at gene --mapping hgnc_{version}_sssom.tsv

Ambiguous mappings (where a deprecated ID or label serves as a recommended for another entity) are not resolved, but flagged for users to solve them manually. If the input file has a column of known aliases or synonyms for each row, pass it as a hint to resolve ambiguous names automatically:

pysec2pri update-ids data.tsv hgnc --at gene_id --synonyms gene_aliases
# Pairs gene_aliases hints with gene_id; repeat --at X--synonyms Y for more columns.

A subset with ambiguous mappings only can be generated like:

pysec2pri ambiguous hgnc-labels

Mapping types

Deprecations (IDs)

A deprecated ID is mapped to its replacement via IAO:0100001 ("term replaced by"). Each row is 1-to-1: one secondary subject_id : one primary object_id.

flowchart LR
    D["subject_id (deprecated)"]
    P["object_id (primary)"]
    D -->|"term replaced by"| P

Ambiguity happens when the same ID appears as both a subject_id (secondary) and an object_id (primary) across different mappings.

flowchart LR
    A["A (primary of C and secondary of B)"] -->|term replaced by| B["B (primary)"]
    C["C (secondary)"] -->|term replaced by| A

Labels

The same 1-to-1 pattern applies to label (or symbol) mappings: a previous or alias label (subject_label) maps to the current label (object_label) of the same entity via IAO:0100001.

Ambiguity appears when the same label is both a subject_label (previous name, secondary) and an object_label (current name, primary) across different mappings.

Aliases / synonyms

Alias mappings use oboInOwl:hasExactSynonym. The alias is the subject_label and the authoritative name is the object_label/object_id.

flowchart LR
    A["subject_label (alias / synonym)"]
    P["object_label/object_id (primary)"]
    A -->|"oboInOwl:hasExactSynonym"| P

Resolving ambiguity with alias/synonym hints

When a name is ambiguous, alias mappings are used as evidence. For each candidate interpretation the resolver checks whether any user-supplied hint matches a known alias of that candidate's primary entity. A hit on the secondary candidate's target confirms the name is being used as a previous name; a hit on the primary candidate's own aliases confirms it is already current.

flowchart TD
    Name["ambiguous name"]
    Hint["Alias hint"]
    Check{"Hint matches alias of…"}
    SecPath["Replacement target: replace"]
    PriPath["Name itself: keep"]
    Blank["Neither: flag for manual review"]
    Name --> Check
    Hint -.-> Check
    Check -->|secondary candidate| SecPath
    Check -->|primary candidate| PriPath
    Check -->|no match| Blank

Disambiguation with context (label / id / xref)

Alias hints are one kind of context: a per-row piece of independent evidence that helps decide which entity an ambiguous name actually means. update_ids and update_labels support three kinds, via pysec2pri.context.ContextSpec:

• label -- an alias/synonym string (the synonyms=/--synonyms shown above).
• id -- a related/foreign identifier string, matched the same way.
• xref -- a cross-reference token (e.g. an Ensembl ID) resolved through an independent crosswalk table (pysec2pri.context.XrefMapping), rather than the mapping set's own alias index.

All three only ever touch cells already flagged ambiguous, and every attempt can be written to an auditable decision log:

from pysec2pri import generate_hgnc_labels, update_labels
from pysec2pri.context import load_xref_mapping

label_ms = generate_hgnc_labels()
ensembl_to_hgnc = load_xref_mapping("ensembl_to_hgnc.tsv")  # subject_id/object_id/object_label

resolved = update_labels(
    df, label_ms, at="gene_name",
    xref="ensembl",                # column with each row's Ensembl ID
    xref_mapping=ensembl_to_hgnc,
    report_path="decisions.tsv",   # stage, token, predicate_id, candidate, accepted, reason
)

The same options are available on the CLI:

pysec2pri update-labels genes.tsv hgnc --at gene_name \
  --xref ensembl --xref-source hgnc_custom --xref-on ensembl \
  --report decisions.tsv

crosswalk: a direct identifier lookup helper

For the common case of "map this one column of identifiers to an HGNC ID (or back to a symbol)", crosswalk is a thin wrapper over the same machinery:

pysec2pri crosswalk --value TP53 --from symbol --to hgnc_id
pysec2pri crosswalk genes.tsv --from ensembl --to hgnc_id --at ensembl_id -o out.tsv

from pysec2pri import crosswalk
crosswalk("TP53", frm="symbol", to="hgnc_id")          # {'TP53': 'HGNC:11998'}
crosswalk("ENSG00000141510", frm="ensembl", to="symbol")  # via HGNC's own crosswalk

Consolidating mapping dates across releases

A single release snapshot only presents each mapping's last-seen date. consolidate builds a first-seen-date index by walking a datasource's historical archive (or, where the parser already exposes a real per-row date such as HGNC's date_symbol_changed, a single fast pass) and writes it back out as a real SSSOM mapping set whose mapping_date is each mapping's true first appearance:

pysec2pri chebi consolidate --mode release   # walks ~250 ChEBI releases; slow, run as a one-off
pysec2pri hgnc consolidate --mode date       # fast: uses HGNC's own per-row date

Supported for chebi, ensembl, hgnc, ncbi, uniprot, and vgnc. Ensembl additionally supports label-history, which derives previous-symbol -> current-symbol transitions by diffing each release's labels per stable ID (Ensembl has no previous-symbol table of its own):

pysec2pri ensembl label-history --species 9606

Diffing mapping sets

diff compares two SSSOM files (e.g. two releases of the same mapping set) and reports added/removed/changed rows:

pysec2pri diff old.sssom.tsv new.sssom.tsv --datasource hgnc -o diff.tsv

Documentation

Full documentation: https://pysec2pri.readthedocs.io/

Supported Databases

Datasource	license	citation
ChEBI	CC BY 4.0.	Hastings J, Owen G, Dekker A, et al. ChEBI in 2016: Improved services and an expanding collection of metabolites. Nucleic Acids Research. 2016 Jan;44(D1):D1214-9. DOI: 10.1093/nar/gkv1031. PMID: 26467479; PMCID: PMC4702775.
Ensembl	link	Martin FJ, Amode MR, Aneja A, et al. Ensembl 2023. Nucleic Acids Res. 2023 Jan 6;51(D1):D933-D941. doi: 10.1093/nar/gkac958. PMID: 36318249; PMCID: PMC9825606.
HMDB	CC BY 4.0	Wishart DS, Guo A, Oler E, Wang F, Anjum A, Peters H, Dizon R, Sayeeda Z, Tian S, Lee BL, Berjanskii M, Mah R, Yamamoto M, Jovel J, Torres-Calzada C, Hiebert-Giesbrecht M, Lui VW, Varshavi D, Varshavi D, Allen D, Arndt D, Khetarpal N, Sivakumaran A, Harford K, Sanford S, Yee K, Cao X, Budinski Z, Liigand J, Zhang L, Zheng J, Mandal R, Karu N, Dambrova M, Schiöth HB, Greiner R, Gautam V. HMDB 5.0: the Human Metabolome Database for 2022. Nucleic Acids Res. 2022 Jan 7;50(D1):D622-D631. doi: 10.1093/nar/gkab1062. PMID: 34986597; PMCID: PMC8728138.
HGNC	link	Seal RL, Braschi B, Gray K, Jones TEM, Tweedie S, Haim-Vilmovsky L, Bruford EA. Genenames.org: the HGNC resources in 2023. Nucleic Acids Res. 2023 Jan 6;51(D1):D1003-D1009. doi: 10.1093/nar/gkac888. PMID: 36243972; PMCID: PMC9825485.
NCBI	link	Sayers EW, Bolton EE, Brister JR, Canese K, Chan J, Comeau DC, Connor R, Funk K, Kelly C, Kim S, Madej T, Marchler-Bauer A, Lanczycki C, Lathrop S, Lu Z, Thibaud-Nissen F, Murphy T, Phan L, Skripchenko Y, Tse T, Wang J, Williams R, Trawick BW, Pruitt KD, Sherry ST. Database resources of the national center for biotechnology information. Nucleic Acids Res. 2022 Jan 7;50(D1):D20-D26. doi: 10.1093/nar/gkab1112. PMID: 34850941; PMCID: PMC8728269.
UniProt	CC BY 4.0	UniProt Consortium. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res. 2021 Jan 8;49(D1):D480-D489. doi: 10.1093/nar/gkaa1100. PMID: 33237286; PMCID: PMC7778908.
VGNC	link	Tweedie S, Braschi B, Gray KA, Jones TEM, Seal RL, Yates B, Bruford EA. Genenames.org: the HGNC and VGNC resources in 2021. Nucleic Acids Res. 2021 Jan 8;49(D1):D939-D946. doi: 10.1093/nar/gkaa980. PMID: 33152070; PMCID: PMC7779007.
Wikidata		Vrandecic, D., Krotzsch, M. Wikidata: a free collaborative knowledgebase. Communications of the ACM. 2014. doi: 10.1145/2629489.

License

MIT License. See LICENSE for details.