pyclusterprofiler 0.1.dev10

Tools for analyzing pathway enrichment of gene lists

pyclusterprofiler

A limited python implementation of clusterProfiler from R, borrowing some functions and concepts from sharepathway and goatools.

Currently KEGG and GO interfaces are implemented.

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Installation

You can install pyclusterprofiler via pip:

pip install pyclusterprofiler

Usage

import pyclusterprofiler

To find enriched KEGG pathways in groupings ("cluster" column) of genes ("gene_id" column) identified in df:

df_enrichment = pyclusterprofiler.compare_clusters(df,'cluster',database='KEGG')

Or using GO terms (instead using database="GO-slim" here will use reduced set of terms):

df_enrichment = pyclusterprofiler.compare_clusters(df,'cluster',database='GO')

Example filter for any pathways/annotations with significant enrichment:

significant_pathways = (df_enrichment
	.query('(corrected_pvalue<0.05)&(cluster_pathway_genes>3)')
	['pathway']
	.unique()
	)

Plot results as a dot plot:

ax = pyclusterprofiler.dotplot(df_enrichment.query('pathway in @significant_pathways'))

compare_clusters arguments

argument	description
df	dataframe with "gene_id" column containing NCBI gene id's and a column specifying group membership
grouping	column or list of columns in df to use for group membership
enrichment_threshold	threshold on ratio of observed/expected gene counts for test to include in results (default 1)
correction	method for correcting p-values for multiple hypothesis testing, used as argument to statsmodels.stats.multitest.multipletests (default "fdr_bh")
organism	organism databases to download. GO uses NCBI taxid; for KEGG see their organism list (default is human databases for each)
database	"KEGG", "GO", or "GO-slim" (default "KEGG")
exclude	pathway/annotation groupings to exclude. For KEGG, can be "human_diseases", "organismal_systems," or a list of both (see KEGG pathways). For GO, can be "molecular_function","biological_process", "cellular_component", or a list of one or more (can also use abbreviations "MF","BP","CC" respectively) (default None)
force	force fresh download of databases, otherwise uses previously downloaded files if found in the current working directory (default False)
verbose	If True, prints provided NCBI gene id's that could not be found in the database (default True)

Contributing

Contributions are very welcome.

License

Distributed under the terms of the MIT license, "pyclusterprofiler" is free and open source software.

Issues

If you encounter any problems, please file an issue along with a detailed description.