flotilla.data_model.gene_ontology module¶

class flotilla.data_model.gene_ontology.GeneOntologyData(data)[source]¶

Bases: object

Object to calculate enrichment of Gene Ontology terms

Acceptable Gene Ontology tables can be downloaded from ENSEMBL’s BioMart tool: http://www.ensembl.org/biomart

1. Choose “Ensembl Genes ##” (## = version number, for me it’s 78)
2. Click “Attributes”
3. Expand “EXTERNAL”
4. Check the boxes for ‘GO Term Accession’, ‘Ensembl Gene ID’, ‘GO Term Name’, and ‘GO domain’

Parameters:	data : pandas.DataFrame A dataframe with at least the following columns: ‘GO Term Accession’, ‘Ensembl Gene ID’, ‘GO Term Name’, ‘GO domain’

domains = frozenset(['molecular_function', 'cellular_component', 'biological_process'])¶

enrichment(features_of_interest, background=None, p_value_cutoff=1000000, cross_reference=None, min_feature_size=3, min_background_size=5, domain=None)[source]¶

Bonferroni-corrected hypergeometric p-values of GO enrichment

Calculates hypergeometric enrichment of the features of interest, in each GO category.

Parameters:	features_of_interest : list-like List of features. Must match the identifiers in the ontology database exactly, i.e. if your ontology database is ENSEMBL ids, then you can only provide those and not common names like “RBFOX2” background : list-like, optional Background genes to use. It is best to use a relevant background such as all expressed genes. If None, defaults to all genes. p_value_cutoff : float, optional Maximum accepted Bonferroni-corrected p-value cross_reference : dict-like, optional A mapping of gene ids to gene symbols, e.g. a pandas Series of ENSEMBL genes e.g. ENSG00000139675 to gene symbols e.g HNRNPA1L2 min_feature_size : int, optional Minimum number of features of interest overlapping in a GO Term, to calculate enrichment min_background_size : int, optional Minimum number of features in the background overlapping a GO Term domain : str or list, optional Only calculate GO enrichment for a particular GO category or subset of categories. Valid domains: ‘biological_process’, ‘molecular_function’, ‘cellular_component’
Returns:	enrichment_df : pandas.DataFrame A (n_go_categories, columns) DataFrame of the enrichment scores
Raises:	ValueError If features of interest and background do not overlap, or invalid GO domains are given