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ATLAS - Advanced Trajectory Learning from multi-omics At Single-cell resolution

Research datakeyboard_double_arrow_right Dataset Under curationPublisher:Zenodo
Authors: Leclercq, Alessia; Martini, Lorenzo; Bardini, Roberta; Savino, Alessandro; Di Carlo, Stefano;

doi: 10.5281/zenodo.20611526

ATLAS - Advanced Trajectory Learning from multi-omics At Single-cell resolution

Abstract

This repository contains sythetic data generated in ATLAS (Advanced Trajectory Learning from multi-omics At Single-cell resolution). Data were generated using scMultiSim v1.0.0 and R v4.4.1. True transcript and chromatin-accessibility counts were generated with the sim_true_counts function, using the built-in 100-genes GRN (GRN_params_100) and both three- and five-branches differentiation trees (Phyla3 and Phyla5) and multiple values for the cif.sigma and the diff.cif.fraction parameters. Data are structured in sub-folders according to the differentiation tree. simulated_data - three_branches - five_branches Within each sub-folder, data files follows the following naming conventions: <diff.cif.fraction>_<cif.sigma>_spliced.tsv <diff.cif.fraction>_<cif.sigma>_unspliced.tsv <diff.cif.fraction>_<cif.sigma>_atac.tsv <diff.cif.fraction>_<cif.sigma>_activity.tsv <diff.cif.fraction>_<cif.sigma>_metadata.tsv

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