Statistics
This module provides helper function for statistical analysis of HPOSet or annotations.
HPOEnrichment
class
- class pyhpo.stats.HPOEnrichment(category)[source]
Calculates the enrichment of HPO Terms in an Annotation set.
You can use this class for the following example use cases:
You have a list of genes and want to see if some HPO terms are enriched in that group. (e.g. RNAseq differential gene expression)
You have a list of OMIM diseases and want to see if they have some underlying HPO symptom.
- Parameters:
category (str) –
String to declare if enrichment is done for genes or for OMIM diseases
Options are:
gene
omim
enrichment
- HPOEnrichment.enrichment(method, annotation_sets)[source]
Calculates the enrichment of HPO terms in the provided annotation set
- Parameters:
method (str) –
The statistical test for enrichment
hypergeom Hypergeometric distribution test
annotation_sets (list of
annoation
) – Everyannotation
item in the list must have an attributehpos
, being a list of HPO-Term indicies
- Returns:
The enrichment of every HPO term in the
annotation_sets
list, sorted by descending enrichment. Every dict has the following keys:hpo:
HPOTerm
count: Number of appearances in the sets
enrichment: Enrichment score
- Return type:
list of dict
EnrichmentModel
class
- class pyhpo.stats.EnrichmentModel(category)[source]
Calculates the enrichment of annotations in an
HPOSet
.You can use this class for the following example use cases:
You have a set of HPOTerms and want to find the most likely causative gene
You have a set of HPOTerms and want to find the underlying disease
- Parameters:
category (str) –
String to declare if enrichment is done for genes or for OMIM diseases
Options are:
gene
omim
orpha
decipher
enrichment
- EnrichmentModel.enrichment(method, hposet)[source]
Calculates the enrichment of annotations in the provided HPOSet
- Parameters:
method (str) –
The statistical test for enrichment
hypergeom Hypergeometric distribution test
hposet (
HPOSet
) –
- Returns:
The enrichment of every annotation item sorted by descending enrichment. Every dict has the following keys:
item: Gene or OMIM or Decipher annotation item
count: Number of appearances in the sets
enrichment: Enrichment score
- Return type:
list of dict