SimiCPipeline

Python package for phenotype-specific GRN inference and Regulon Activity Score (RAS) calculation.

SimiCPipeline is the Python component of SimiC-Suite. It supports phenotype-specific gene regulatory network (GRN) inference from single-cell RNA-seq data and calculation of Regulon Activity Score (RAS) values for downstream interpretation.

SimiCPipeline builds on the SimiC framework for phenotype-aware regulatory network analysis. Please cite the original SimiC work when using SimiCPipeline where appropriate.

View SimiCPipeline on GitHub

Tutorials

The tutorials below are local rendered copies of the Jupyter notebooks from the ML4BM-Lab/SimiCPipeline repository. They are rendered without executing code during website publication.

Full Pipeline Tutorial

Complete SimiCPipeline walkthrough, including initialization, parameter configuration, GRN inference, RAS calculation, and downstream result inspection.

Open tutorial Download notebook

Preprocessing Tutorial

Notebook covering data preparation steps for SimiCPipeline inputs, including expression data, transcription factor lists, and phenotype labels.

Open tutorial Download notebook

Visualization Tutorial

Notebook focused on inspecting and visualizing SimiCPipeline outputs after GRN inference and RAS calculation.

Open tutorial Download notebook

Helper Scripts

These reference scripts are copied from the SimiCPipeline notebook folder.