PyLiger: scalable single-cell multi-omic data integration in Python

Abstract

Motivation: LIGER (Linked Inference of Genomic Experimental Relationships) is a widely used R package for single-cell multi-omic data integration. However, many users prefer to analyze their single-cell datasets in Python, which offers an attractive syntax and highly optimized scientific computing libraries for increased efficiency.

Results: We developed PyLiger, a Python package for integrating single-cell multi-omic datasets. PyLiger offers faster performance than the previous R implementation (2-5× speedup), interoperability with AnnData format, flexible on-disk or in-memory analysis capability and new functionality for gene ontology enrichment analysis. The on-disk capability enables analysis of arbitrarily large single-cell datasets using fixed memory.

Availability and implementation: PyLiger is available on Github at https://github.com/welch-lab/pyliger and on the Python Package Index.

Supplementary information: Supplementary data are available at Bioinformatics online.