Home - RegnerM2015/scENDO_scOVAR_2020 GitHub Wiki

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 gynecologic 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 distal regulatory elements to drive oncogenic transcriptional programs.

Table legend: The last two columns reflect the number of cells obtained post QC and in parentheses the total number of cells estimated by Cell Ranger. Asterisks in the Tumor site column denote a metastatic event. Race column abbreviations: African American (AA), Caucasian (CAU), Asian (AS).

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

Interested in more exciting research in cancer genomics? Visit https://www.thefrancolab.org/ to learn more!