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awesome-grn-inference
Community-curated list of software packages and data resources for inferring gene regulatory networks (GRNs) from genomics data
https://github.com/IGVF-UCSD/awesome-grn-inference
- SCENIC - [R, Python] - SCENIC is a package to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data. [SCENIC: single-cell regulatory network inference and clustering](https://www.nature.com/articles/nmeth.4463)
- SINCERITIES - [R/Matlab] - [Inferring gene regulatory networks from time-stamped single cell transcriptional expression profiles](https://academic.oup.com/bioinformatics/article/34/2/258/4158033)
- Normalisr - [Python, Shell] - Normalisr infers Gene Regulatory Networks from Perturb-seq and other single-cell CRISPR screens. Its normalization and statistical association testing framework also unifies single-cell differential expression and co-expression. [Single-cell normalization and association testing unifying CRISPR screen and gene co-expression analyses with Normalisr](https://doi.org/10.1038/s41467-021-26682-1).
- Dictys - [Python] - Dictys reconstructs and analyzes context specific and dynamic Gene Regulatory Networks from scRNA-seq and scATAC-seq datasets. [Dictys: dynamic gene regulatory network dissects developmental continuum with single-cell multi-omics](https://doi.org/10.1101/2022.09.14.508036)
Keywords
network-inference
2
single-cell-analysis
2
gene-regulatory-network
2
association-testing
1
causal-inference
1
co-expression
1
differential-expression
1
hypothesis-testing
1
normalization
1
scrna-seq
1
single-cell
1
single-cell-crispr-screening
1
dynamic-network
1
network-analysis
1
network-visualization
1
single-cell-multiomics
1
single-cell-network
1