Description
This model maps HPO codes to their associated gene symbol(s), based on gene-phenotype associations curated by the Human Phenotype Ontology (HPO) project. Codes linked to more than one gene return every associated gene via the all_k_resolutions metadata field. Trained on the Human Phenotype Ontology (HPO) 2026-06-23 release.
Live Demo Open in Colab Copy S3 URI
How to use
document_assembler = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("document")
chunk_assembler = Doc2Chunk()\
.setInputCols(["document"])\
.setOutputCol("hpo_code")
hpo_code_gene_mapper = ChunkMapperModel.pretrained("hpo_code_gene_mapper", "en", "clinical/models")\
.setInputCols(["hpo_code"])\
.setOutputCol("mappings")\
.setRels(["gene"])
pipeline = Pipeline(stages=[document_assembler, chunk_assembler, hpo_code_gene_mapper])
data = spark.createDataFrame([["HP:0000002"], ["HP:6001080"], ["HP:0009484"]]).toDF("text")
result = pipeline.fit(data).transform(data)
document_assembler = nlp.DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("document")
chunk_assembler = nlp.Doc2Chunk()\
.setInputCols(["document"])\
.setOutputCol("hpo_code")
hpo_code_gene_mapper = medical.ChunkMapperModel.pretrained("hpo_code_gene_mapper", "en", "clinical/models")\
.setInputCols(["hpo_code"])\
.setOutputCol("mappings")\
.setRels(["gene"])
pipeline = nlp.Pipeline(stages=[document_assembler, chunk_assembler, hpo_code_gene_mapper])
data = spark.createDataFrame([["HP:0000002"], ["HP:6001080"], ["HP:0009484"]]).toDF("text")
result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val chunkAssembler = new Doc2Chunk()
.setInputCols("document")
.setOutputCol("hpo_code")
val hpoCodeGeneMapper = ChunkMapperModel
.pretrained("hpo_code_gene_mapper", "en", "clinical/models")
.setInputCols(Array("hpo_code"))
.setOutputCol("mappings")
.setRels(Array("gene"))
val pipeline = new Pipeline().setStages(Array(documentAssembler, chunkAssembler, hpoCodeGeneMapper))
val data = Seq("HP:0000002", "HP:6001080", "HP:0009484").toDF("text")
val result = pipeline.fit(data).transform(data)
Results
| hpo_code | gene | all_k_resolutions |
|:-----------|:--------|:--------------------------------------------------------------------------------------------------------|
| HP:0000002 | TBCB | TBCB:::DUSP6:::FGF8:::FGFR1:::GNRH1:::GNRHR:::HIVEP2:::KISS1:::LRP5:::NHLH2:::PDGFRB:::TAC3:::TACR3:... |
| HP:6001080 | HSD11B1 | HSD11B1::: |
| HP:0009484 | SHH | SHH:::LMBR1 |
Model Information
| Model Name: | hpo_code_gene_mapper |
| Compatibility: | Healthcare NLP 6.4.0+ |
| License: | Licensed |
| Edition: | Official |
| Input Labels: | [ner_chunk] |
| Output Labels: | [mappings] |
| Language: | en |
| Size: | 973.5 KB |