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• Reference epigenome ADMSC03_smRNA-Seq data generated from KEP study

  A ADMSC03_smRNA-Seq single end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003869

• Reference epigenome KNIH005 WGBS data generated from KEP study

  A KNIH005 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002753

• Reference epigenome KNIH006 WGBS data generated from KEP study

  A KNIH006 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for beta cells

  Dataset EGAD00001002754

• Reference epigenome KNIH007 WGBS data generated from KEP study

  A KNIH007 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for adipocytes

  Dataset EGAD00001002755

• Reference epigenome KNIH009 WGBS data generated from KEP study

  A KNIH009 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for preadipocytes

  Dataset EGAD00001002757

• Reference epigenome KNIH001 WGBS data generated from KEP study

  A KNIH001 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002749

• Reference epigenome KNIH002 WGBS data generated from KEP study

  A KNIH002 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002750

• Reference epigenome KNIH003 WGBS data generated from KEP study

  A KNIH003 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002751

• Reference epigenome KNIH004 WGBS data generated from KEP study

  A KNIH004 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002752

• CYP2C19 long-read sequencing

  We have assessed the added value of long-read sequencing for PGx focusing on the clinically important and highly polymorphic CYP2C19 gene within 48 samples.

  Dataset EGAD00001009883

• Hi-C of cohesin-mutated and wildtype adult AMLs

  High-throughput chromosome conformation capture (Hi-C) data generated for cohesin-mutated (STAG2 or RAD21) and cohesin-wildtype AMLs.

  Dataset EGAD00001011198

• A Phase Ib/II Study of Regorafenib and Paclitaxel in Beyond First-line Advanced Esophagogastric Carcinoma (REPEAT)

  Regorafenib showed promising results in gastric cancer. We aimed to assess the tolerability of regorafenib and paclitaxel in advanced esophagogastric cancer (EGC) patients refractory to first-line treatment and explore potential biomarkers.. We performed enzyme-linked immunosorbent assay measurements of galectin-1, RNA sequencing, and shallow wholegenome sequencing of metastatic tumor biopsies for biomarker analyses.

  Study EGAS00001006054

• Tumor-resident T-cell regulate responses to checkpoint blockade immunotherapies

  In cancer models, CD103+CD8 TRM cells are implicated in the response to anti-PD-1 immunotherapy, and a subset of CD4 TRM cells expressing the integrin CD49a is required for response to anti-CTLA-4 immunotherapy. We performed single-cell RNA sequencing on tumour-infiltrating T lymphocytes (TILs) isolated from colon carcinoma et unsupervised analyses reveal several TRM populations.

  Study EGAS50000000826

• LuCaP cell line ChIP-seq

  ChIP-seq of 2 LuCaP cell lines with different factors. LuCaP cell line 189.4 was ChIP-sequenced for 6 factors with different conditions as well as the input DNA (n=31 in total). LuCaP 189.4 ChIP-sequence experiments include; 3 H3K27ac/DMSO, 3 H3K27ac/vorinostat, 3 H3K27ac/dexamethasone, 3 H3K27ac/dexamethasone/vorinostat, 3 GR dexamethasone, 3 GR dexamethasone/vorinostat, 3 HDAC3/DMSO, 3 AR, 3 FOXA1, 3 H3K27ac and 1 input sample. LuCaP 35 ChIP-sequence experiments as well as input include (n=10 in total); 3 H3K27ac, 3 AR, 3 FOXA1 and 1 input sample. All 41 samples were sequenced using paired-end reads on Illumina NovaSeq 6000. Each sample has 2 fastq files, one for the forward and reverse read, respectively.

  Dataset EGAD50000001345

• SCRNA10X_SA_CHIP0080_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0080_001 1 samples; filetype=fastq

  Dataset EGAD00001006461

• SCRNA10X_SA_CHIP0080_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0080_002 1 samples; filetype=fastq

  Dataset EGAD00001006462

• SCRNA10X_SA_CHIP0006_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0006_001 1 samples; filetype=fastq

  Dataset EGAD00001006460

• SCRNA10X_SA_CHIP0141_004

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0141_004 1 samples; filetype=fastq

  Dataset EGAD00001006463

• SCRNA10X_SA_CHIP0142_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0142_001 1 samples; filetype=fastq

  Dataset EGAD00001006464

• SCRNA10X_SA_CHIP0142_003

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0142_003 1 samples; filetype=fastq

  Dataset EGAD00001006465

• SCRNA10X_SA_CHIP0146_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0146_002 1 samples; filetype=fastq

  Dataset EGAD00001006466

• SCRNA10X_SA_CHIP0149_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0149_001 1 samples; filetype=fastq

  Dataset EGAD00001006467

• SCRNA10X_SA_CHIP0149_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0149_002 1 samples; filetype=fastq

  Dataset EGAD00001006468

• SCRNA10X_SA_CHIP0150_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0150_001 1 samples; filetype=fastq

  Dataset EGAD00001006469

• SCRNA10X_SA_CHIP0150_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0150_002 1 samples; filetype=fastq

  Dataset EGAD00001006470