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Welcome to the scENDO_scOVAR_2020 wiki!

Each page on the right outlines the code and necessary scripts to generate each main figure from our manuscript titled, "A multi-omic single-cell landscape of human gynecological malignancies." Herein, we present matched transcriptome (scRNA-seq) and chromatin accessibility profiles (scATAC-seq) at single-cell resolution from 11 human ovarian and endometrial tumors processed immediately following surgical resection. This unprecedented dataset provides the resolution to reveal the complex cellular heterogeneity of these tumors and has enabled us to link changes in chromatin accessibility to changes in gene expression. These data offer mechanistic insights into how cancer cells repurpose and acquire non-coding distal regulatory elements to drive oncogenic transcriptional programs.

To download the data, please visit the Gene Expression Omnibus (GEO) accession GSE173682.