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Rosa (version 0.7.7)

Rosa--Regulon Structure-based Activity inference

version 0.7.7

The statsitical model of Rosa

Rosa performs regulon structure-based activity inference, a statistical model for quantitative inference of protein activities using gene regulatory networks reverse-engineered from scRNA-seq. Rosa calculates a normalized enrichment score (NES) that represents the protein activities of the candidate regulators. Rosa is inspired by Viper, a popular R package developed by Dr. Andrea Califano’s Lab.

The network-based inference framework

Gene Regulatory Network Preparation

Run ARACNe/ARACNe-AP, which was developed by Dr. Andrea Califano's lab. See the instructions at https://github.com/califano-lab/ARACNe-AP.

Protein Activity Inference

Run Rosa. See the instructions at the Tutorials section.

Tutorials

Protein activity inference and essential regulator prediction of retinal cell classes

https://github.com/JunqiangWang/Rosa/blob/main/tutorial/Lamprey.pa.analysis.Rmd.
The code provided in this tutorial is used to generate the figures presented in the paper: Wang J, Zhang L, Cavallini M, Pahlevan A, Sun J, Morshedian A, Fain GL, Sampath AP, Peng YR. Molecular characterization of the sea lamprey retina illuminates the evolutionary origin of retinal cell types. Nat Commun. 2024 Dec 30;15(1):10761. doi: 10.1038/s41467-024-55019-x. PMID: 39737973; PMCID: PMC11685597.

Author

Junqiang Wang

Email: junqiangwang333@gmail.com