CellCraft: an extensible visual programming application for gene regulatory network inference.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 41452748.
- Also identified by DOI 10.1093/bioinformatics/btaf684 and PMC identifier 12858299.
- 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
Reconstructing gene regulatory networks (GRNs) from single-cell RNA sequencing (scRNA-seq) data is fundamental for understanding cellular dynamics at the molecular level but requires sophisticated workflows. Here, we introduce CellCraft, a web-based application designed to streamline GRN inference. CellCraft integrates multiple GRN reconstruction tools, including TENET, within a unified web application featuring an intuitive graphical user interface. Notably, CellCraft provides a visual programming interface that simplifies the design and execution of complex multistep analyses, thereby enhancing accessibility and facilitating the visualization and interpretation of computational experiments. Furthermore, its modular plugin architecture ensures extensibility, enabling the incorporation of newly developed single-cell analysis algorithms. Consequently, CellCraft provides a user-friendly and extensible application for integrative GRN analysis of scRNA-seq datasets. CellCraft is available on GitHub at https://github.com/cxinsys/cellcraft. The source code has been archived on Zenodo at 10.5281/zenodo.17865848.
Medical subject headings
- Software
- Gene Regulatory Networks
- Computational Biology