Explore Our Datasets
Browse through a collection of comprehensive datasets used for epigenomic studies across various cancers. Each dataset provides insights into different biological contexts, cohort sizes, and sources.
| Dataset ID | Biological Context | #Tumor tissues | #Tumor adjacent tissues | Source |
|---|---|---|---|---|
| DS001 | H3K27ac ChIP-seq profiles on tumor tissues of lung adenocarcinoma patients (GII:high risk, GI:low risk) | 42 | NA | Yuan et al. Genome Biology 2021 |
| DS002 | ATAC-seq profiles on tumor tissues of non-small cell lung cancer patients | 34 | NA | Wang et al. Cancer Research 2019 |
| DS003 | ATAC-seq profiles on tumor tissues of 23 cancer types | 410 | NA | Corces et al. Science 2018 |
| DS004 | ATAC-seq profiles on thyroid cancer | 227 | 74 | Akshay et al. Nature Communications 2021 |
| DS005 | ATAC-seq profiles on pancreatic cancer patient derived organoids | 44 | NA | Shi et al. Nature Communications 2022 |
| DS006 | H3K27ac ChIP-seq profiles on gastric cancer cell lines representing the Mesenchymal(Mes) amd non-Mesenchymal(nMes) subtypes | 26 | NA | Ho et al. Gut 2023 |
| DS007 | H3K27ac ChIP-seq profiles on colorectal cancer patients' tumor and adjacent normal tissues | 147 | 73 | Li et al. Nature Communications 2021 |
| DS008 | ATAC-seq profiles on glioblastoma separated these samples into three subgroups, C3(Low risk), C1(Medium risk), C2(High risk) | 126 | NA | Lu et al. Nature Communications 2022 |
| DS009 | ATAC-seq profiles on human hematopoiesis and leukemia evolution | 160 | 107 | Corces et al. Nature Genetics 2016 |
| DS010 | H3K4me3 ChIP-seq profiling of the NCI-60 panel of cell lines | 60 | NA | Gopi et al. Nature Communications 2021 |