Published July 10, 2021
| Version 1.0.0
Dataset
Open
ZIRFs: zero-inflated random forests for estimating gene regulatory networks from single cell RNA-seq data (assessment of predictive accuracy and VIM stability)
Authors/Creators
- 1. Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison
- 1. University of Wisconsin-Madison, Department of Biostatistics and Medical Informatics,
- 2. University of Wisconsin-Madison, Department of Biostatistics and Medical Informatics
Description
We developed a zero-inflated random forests (ZIRFs) algorithm to produce a metric of connection strength between regulator genes and target genes. This file contains SCENIC results for the aorta and diaphragm tissue data sets from the Tabula Muris Consortium results. SCENIC is a genetic regulatory network analysis published by Aibar et al. (2017). The purpose of the data sets and R source code are described by README files in each directory.
Notes
This work was supported by NIH grants HG003747 and HG011371 to S.K., and D.C. was partially supported by NLM grant 5T15LM007359.
Files
Aorta.zip
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Additional details
Funding
- National Institutes of Health
- Statistical Methods for the Analysis of ChlP-chip Data 5R01HG003747-03