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DeepSCENIC analyses

Analysis notebooks for the manuscript “DeepSCENIC: transfer learning from sequence-to-function models enables causal gene regulatory network inference”

DeepSCENIC combines representations learned by sequence-to-function models with single-cell RNA and ATAC measurements to infer transcription factor-to-regulatory element (TF–RE), regulatory element-to-target gene (RE–TG), and transcription factor-to-target gene (TF–TG) relationships. This repository contains the manuscript and the annotated analysis notebooks used for Figures 2–4. It does not contain the DeepSCENIC training library; that code is maintained in the DeepSCENIC repository.

Repository contents

Path Description
notebooks/Figure2.ipynb Figure 2 - ENCODE cell-line validation.
notebooks/Figure3.ipynb Figure 3 — Melanoma perturbations.
notebooks/Figure4.ipynb Figure 4 — Cross-species cortical regulation.

Analysis data and model outputs

The input data and trained model outputs to reproduce the analysis are not included in this repository. They can be downloaded from DOI: 10.5281/zenodo.20560125, or from their original publications.

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Analyses scripts for "DeepSCENIC: transfer learning from sequence-to-function models enables causal gene regulatory network inference"

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