FastTENET: an accelerated TENET algorithm based on manycore computing in Python.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 39570606.
- Also identified by DOI 10.1093/bioinformatics/btae699 and PMC identifier 11645435.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
TENET reconstructs gene regulatory networks from single-cell RNA sequencing (scRNAseq) data using the transfer entropy (TE), and works successfully on a variety of scRNAseq data. However, TENET is limited by its long computation time for large datasets. To address this limitation, we propose FastTENET, an array-computing version of TENET algorithm optimized for acceleration on manycore processors such as GPUs. FastTENET counts the unique patterns of joint events to compute the TE based on array computing. Compared to TENET, FastTENET achieves up to 973× performance improvement. FastTENET is available on GitHub at https://github.com/cxinsys/fasttenet.
Medical subject headings
- Algorithms
- Software