Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets
Creators
- 1. Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI, USA
Description
The uploaded files are source datasets for the scMTNI algorithm. scMTNI is a multi-task learning framework that integrates the cell lineage structure, scRNA-seq and scATAC-seq measurements to enable joint inference of cell type-specific GRNs. See more details at Preprint: https://biorxiv.org/cgi/content/short/2022.07.25.501350v1.
The source data scMTNI_sourcedata.tar.gz contain the following 3 parts:
1) The cluster-specific scRNA-seq matrices and the prior networks for all three datasets and scMTNI inferred consensus networks.
2) Gold standard human and mouse datasets for evaluation.
3) Source data for scMTNI figures 2-8 and supplementary figures. The key for each figure and its corresponding file path is in SourceData_Key_v2.xlsx.
The source data Buenrostro_Hematopoiesis.tar.gz contains the scRNA-seq data for human hematopoietic differentiation downloaded from Data S2 of Buenrostro et al.
Files
Files
(958.5 MB)
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md5:740fe635c587bffe0314e1e2ebea4518
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md5:3f6b378112c0eceab68323a4230ccafb
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670.9 MB | Download |