Datasets and Tools

Copy-scAT: An R package to infer focal and large-scale copy number alterations using scATAC-seq data

You can find our preprint here.
And you can find instructions and a tutorial for Copy-scAT on GitHub.

3D Genome Architecture

In the paper by Johnston et al (2019), we have generated sub-5 kbp resolution 3D genome maps of patient-derived GBM stem cells. This high resolution allows visualization of individual chromatin loops and enabled us to look at precise regulation of gene expression. In addition, we have generated ChIP-seq data for the looping factor CTCF and for the active enhancer/open chromatin histone mark H3K27ac. Integration of these data allows inference of enhancer/super-enhancer gene interactions.

You can use this link to access and download processed 3D genome data, CTCF ChIP-seq and H3K27ac datasets.

ChIP-seq data can also be accessed at the GEO, accession number GSE121601.

You can also visualize 3D genome information (loops, domains and compartments), together with CTCF sites, H3K27ac peaks and super-enhancer calls on the WashU Epigenome Browser using this link.

Unprocessed Hi-C data can be requested through the EGA and are available at the following link.

Linked-Read Whole Genome Sequencing of Pediatric Hign-Grade Gliomas

The WGS datasets described in the paper by Hoffman et al (2019) can be requested through the EGA. The data can be found under study ID EGAS00001003432.

scRNA-seq datasets generated from 2 patient-derived xenografts can be found at GEO with identifier GSE117599.