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• Dataset for identification of the dismal subtype of B-ALL with dysregulation of CDX2 and UBTF

  WGS (tumor and germline samples) was performed to identify structural variants in the UBTF/CDX2 subgroup. RNA-seq was performed to detect gene fusion in the UBTF/CDX2 subgroup. HiChIP was performed to investigate 3D chromatin architecture and enhancer landscapes of representative patient samples and cell lines harboring Type I and II FLT3-PAN3 deletions and amplifications.

  Dataset EGAD00001008416

• Single-cell expression of Hodgkin and Reed-Sternberg (HRS) cell

  Hybrid capture sequencing was performed to 3 purified Hodgkin and Reed-Sternberg (HRS) cell samples. In brief, Probes for 177 genes were designed and synthesized by Twist Bioscience. Hybridization capture of DNA libraries was performed using Twist Hybridization and Wash Kit (Twist Bioscience). The captured library was measured using Agilent Bioanalyzer High Sensitivity chip and Qubit dsDNA HS Assay Kit and run on Illumina Nextseq550. The BAM files were generated from the raw sequencing data using Cell Ranger (v6.0.2) mkfastq and count commands

  Dataset EGAD00001010892

• Raw molecular data for "Subclonal immune evasion in non-small cell lung cancer"

  Whole exome, RNA sequencing and TCR sequencing of organoid samples derived from TRACERx patients. The dataset also includes whole exome sequencing from the tumour samples from which the organoids were generated, as well as whole exome sequencing from PDX derived from said tumours.

  Dataset EGAD00001015537

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015715

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015710

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015711

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015717

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015719

• TMD-AMKL targeted follow-up part 2

  Genomic libraries will be generated from total genomic DNA derived from 200+ patients with childhood Transient Myeloproliferative Disorder (TMD) and or Acute Megakaryocytic Leukemia (AMKL) as well some matched constitutional samples (n < 50). Libraries will be enriched for a selected panel of genes using a bespoke pulldown protocol. 96 Samples will be individually barcoded and subjected to up to two lanes of Illumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the characterisation of known gene mutations in cancer as well as the validation of potentially novel variants identified by prior exome sequencing.

  Dataset EGAD00001000879

• Targeted sequencing of genes recurrently mutated in AML - part2

  Genomic libraries will be generated from total genomic DNA derived from 4000 samples with Acute Myeloid Leukaemia. Libraries will be enriched for a selected panel of genes using a bespoke pulldown protocol. 64 Samples will be individually barcoded and subjected to up to one lanes of Illumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the characterisation of known gene mutations in cancer as well as the validation of potentially novel variants identified by prior exome sequencing.

  Dataset EGAD00001000747

• Finding structural variation from the patient-derived xenografts of pediatric T-cell leukemia at the single-cell level

  In this study, we aimed to identify somatic structural variation of T-cell acute lymphoblastic leukemias (T-ALLs_ from patient-derived xenografts (PDX) at the single-cell level. For this purpose, we performed strand-specific single-cell sequencing of PDX-derived T-ALL relapse samples from two juvenile patients (P1, P33). To validate structural variation detected via scTRIP, we profiled whole exome sequencing (WES) data from P33 (samples taken during initial disease, remission, relapse), and mate-pair sequencing data from P1 (relapse).

  Dataset EGAD00001004499

• Evolution of the cancer epigenome in myeloproliferative neoplasms. (2019-04-01)

  Evolution of the cancer epigenome in myeloproliferative neoplasms. . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004879

• small RNA-sequencing and RNA-sequencing of human brain tissue with temporal lobe epilepsy

  This data set contains the raw .fastq files from two RNA-sequencing experiments and two small RNA-sequencing experiments. Both control brain tissue and tissue from sufferers of mesial temporal lobe epilepsy were sequenced. Two different brain regions were sequenced; the cortex and the hippocampus. For more details please see: Mills, James D., et al. "Coding and non-coding transcriptome of mesial temporal lobe epilepsy: Critical role of small non-coding RNAs." Neurobiology of disease 134 (2020): 104612.

  Dataset EGAD00001005735

• Regulation of T Cell CXCL13 Production

  This study evaluated the signals that regulate production of the B cell chemoattractant CXCL13 by human CD4 T cells. Single-cell and bulk RNA-seq datasets evaluated the gene expression changes induced by TGF-beta and the aryl hydrocarbon receptor (AHR), two signals that regulate CXCL13 production. Bulk ATAC-seq data evaluated the epigenetic changes in T cell stimulated with an AHR agonist or antagonist. Ex vivo bulk RNA-seq data of sorted T cell subsets from blood of patients with lupus and control donors interrogated the gene expression differences in sorted T cell subsets. Ex vivo ATAC-seq data allowed comparison of epigenetic profiles of PD-1hi Tph cells from rheumatoid arthritis synovial fluid and PD-1hi T follicular helper (Tfh) cells from tonsil to PD-1low CD4 T cells from the same samples. Single-cell RNA-seq data of T cells from lupus patients before and after treatment with anifrolumab (anti-IFNAR) allowed interrogation of T cell populations that change with anifrolumab treatment. These datasets allowed for genomic interrogation of changes induced by AHR, TGF-beta, and interferon and their relationship to CXCL13 production.

  Study phs003582

• Novel regional age-associated DNA methylation changes within human common disease-associated loci

  Background: Advancing age progressively impacts on risk and severity of chronic disease. It also modifies the epigenome, with changes in DNA methylation, due to both random drift and variation within specific functional loci. Results: In a discovery set of 2,238 peripheral-blood genome-wide DNA methylomes (MeDIP-seq) aged 19-82 years, we identified 71 age-associated Differentially Methylated Regions (a-DMRs, p < 1.85 x 10-8) within the Linkage Disequilibrium (LD) blocks of the NIH Catalogue of published GWAS SNPs. This included 52 novel regions, 29 within loci not covered by 450k or 27k Illumina array, and with marked enrichment for Poised Promoters and Enhancers across multiple cell types. In a replication set of 2,084 DNA methylomes, 95.7% of the a-DMRs showed the same direction of ageing effect, with 80.3% and 53.3% replicated to p < 0.05 and p < 1.85 x 10-8, respectively. Conclusion: By analysing the functionally enriched disease and trait-associated regions of the human genome, we identified novel epigenetic ageing changes, which could be useful biomarkers or provide mechanistic insights into age-related common diseases.

  Study EGAS00001001910

• A Single-cell Atlas of Progressive TKI Resistance in Chronic Myeloid Leukemia

  High-dimensional scRNA seq and CyTOF were used to identify features predictive of treatment outcome at diagnosis. An optimal TKI response was characterised by erythroid lineage skewing of the CD34+ HSPC compartment. While TKI-resistant CP was reminiscent of a BC-like state, where HSPCs were enriched for inflammation, stemness and quiescence. We designed a machine-learning approach which assessed the prognostic potential of all 32 sub-populations of our scRNA seq dataset. LSCs and NK populations harboured the highest prognostic power at diagnosis. Within the LSCs, erythroid lineage priming and MYC activation were features of an optimal and poor TKI responses, respectively. With the NK cell compartment, apart from a higher abundance of NK cells in TKI optimal responders, a memory-like HLA-DR+ adaptive NK and KLRC1+ NK populations were hallmarks of an optimal and poor TKI responses, respectively. Mechanistically, both cell intrinsic and extrinsic mechanisms contributed towards the higher sensitivity of EPs to TKI therapy. In summary, our high-dimensional single-cell atlas of TKI resistance highlights pivotal transcriptional features associated with TKI-resistance disease, some of which have the potential to be exploited as biomarkers.

  Study EGAS00001005509

• Detection and phasing of single base de novo mutations in biopsies from human in vitro fertilized embryos by advanced whole-genome sequencing

  Current methods available for pre-implantation genetic diagnosis (PGD) of in vitro fertilized (IVF) embryos do not detect de novo. Detection of these types of mutations requires whole genome sequencing (WGS). In this study advanced massively parallel WGS was performed on three 5-10 cell biopsies from two blastocyst-stage embryos. Overall, greater than 95% of each genome was called and experimentally derived haplotypes and barcoded read data were used to detect and phase up to 82% of de novo single base mutations with a false positive rate of ~1 error per Gb. These results suggest that phased WGS using barcoded DNA could be used in the future as part of the PGD process to maximize comprehensiveness in detecting disease causing mutations and reduce the incidence of genetic diseases.

  Study phs000858

• Sequencing Lymphoma

  This repository contains sequencing data to describe the genomic profiles of several B-cell lymphomas including follicular lymphoma and Hodgkin lymphoma. We have used several different high throughput sequencing technologies to interrogate genomic DNA and RNA from tumor cells obtained from lymph node biopsies and normal cells obtained from skin biopsies and peripheral blood mononuclear cells. A number of sequencing platforms for DNA, RNA, and protein were used to generate the data. These platforms include exome sequencing and a custom capture panel (NimbleGen) that targets 7.05 MB corresponding to the exons and splice sites of 1716 genes related to lymphoma biology (WUSM-LP). Other platforms include single-cell RNA-seq and Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), which was used to describe transcriptional and proteomic changes in immune cell subsets within lymphoma patients pre- and post-therapy.

  Study phs001229

• Spatial and temporal diversity in genomic instability processes define early stage lung cancer evolution.

  Deciphering the complexity of non-small cell lung cancer (NSCLC) evolutionary histories may elucidate the basis for its dismal outcome. We performed multi-region sequencing on 25 regions from seven early-stage NSCLCs. Spatial dissection revealed branched tumor evolution, with driver mutations occurring before and after subclonal diversification. Intra-tumor heterogeneity in DNA copy number alterations, translocations and endogenous APOBEC mutational processes, demonstrates that NSCLC may follow multiple distinct evolutionary trajectories simultaneously. In smokers, despite maintained carcinogen exposure, temporal dissection reveals a proportional decrease in smoking-related mutations during tumor progression, accompanied by an increase in APOBEC-related mutations. We observed genome-doubling events early in tumor development of ex-smokers, suggesting prolonged latency periods before clinical detection. Multi-region sequencing demonstrates the relentless and heterogeneous nature of genomic instability processes in early-stage NSCLCs.

  Study EGAS00001000840

• Cancer of Low survival and UnMet Need – Pathologist Initiated

  Despite significant advances in diagnostic cancer histopathology, a subset of tumors remain unable to be classified using WHO criteria. The resulting diagnostic uncertainty can result in inappropriate clinical management and negative patient outcomes. We investigated whether combining histopathology with whole genome and transcriptome sequencing (WGTS) could improve the classification of tumors that posed diagnostic dilemmas despite extensive histopathology and standard molecular work-up at a quaternary oncology center. We successfully sequenced 45 tumors from an initial set of 54 unclassified tumors (83% success rate). A confident diagnosis was made for 38/45 tumors (84%). Additionally, potential treatment targets were identified in 21/45 tumors (47%). Theoretical comparison with alternative assays demonstrated that WGTS was uniquely capable of detecting critical diagnostic findings in 15/38 tumors (39%). This work supports augmenting histopathology and standard molecular pathology with WGTS in the classification of difficult-to-diagnose tumors.

  Study EGAS00001008112

• Research for drug discovery and elucidation of pathophysiology using disease-specific iPS cells

  We investigated roles of KRAS on stemness maintenance and differentiation propensity in the context of induced pluripotent stem cells (iPSCs) using isogenic KRAS mutant (G13C/WT) and wild-type (WT/WT) iPSCs from the same RAS-associated autoimmune lymphoproliferative syndrome-like disease (RALD) patients. Exome-seq analysis was conducted to compare gene profiles of WT/WT and G13C/WT iPS cells. We have not found any differences of gene mutation in the two genotypes.

  Study JGAS000136

• Single-Nuclei RNA Sequencing and Spatial Transcriptomics of Human Heart Right Atrial Appendage and Pericardial Fluid in Cardiovascular Disease

  This dataset includes single-nuclei RNA sequencing (snRNA-seq) and spatial transcriptomics data from biopsies of the right atrial appendage and pericardial fluid, collected during open-heart surgeries. The samples represent various clinical contexts, including control, ischemic heart disease, heart failure, and myocardial infarction. For each biopsy, nuclei were isolated, and RNA sequencing libraries were prepared using the 10x Genomics Chromium v3 platform. Additionally, spatial transcriptomics was performed on the heart samples. The dataset provides raw sequencing data, which includes fastq files generated from these libraries, offering valuable insights into the cellular composition of heart tissues and associated fluids across different disease states.

  Dataset EGAD50000000927

• RNA-sequencing on thyroid samples from fetuses with Down syndrome and fetuses with no genetic/developmental abnormality

  The current data pertains RNA-sequencing reads obtained from thyroid samples acquired from fetuses with Down syndrome and fetuses with no genetic/developmental abnormality. Total RNA was isolated from left lobe from thyroid samples using a hand-held homogenizer and the Promega ReliaPrep RNA Miniprep System (Thermo Fisher Scientific). RNA yield was determined with the NanoDrop Microvolume Spectrophotometer (Thermo Fisher Scientific). Fragmentation and mRNA library preparation was performed using the Kapa mRNA Hyperprep Kit (Roche, Basel, Switzerland). Libraries were equimolar pooled and quality was checked on a TapeStation system using the DNA1000 ScreenTape (Agilent Technologies, Santa Clara, CA, USA). Libraries were sequenced with poly(A) selection to sequence all messenger RNA for gene expression analysis on the NovaSeq6000 PE150 (Illumina, San Diego, CA, USA), producing at least 40M 150-bp paired-end reads per library.

  Dataset EGAD50000000387

• Estimating transcription factor variability in PC-9 cells using scRNA-seq

  PC-9 cells were barcoded following protocol from Chang et al. Nature Biotech. 2021, which does not affect downstream analysis. PC-9 cells were trypsinized into single-cell suspensions and processed using Chromium Single Cell Gene Expression 3’ Library and Gel Bead Kit V2.0 following the manufacturer’s instructions (10X Genomics). Cells were counted and checked for viability using Vi-CELL XR cell counter (Beckman Coulter), and then injected into microfluidic chips to form Gel Beads-in-Emulsion (GEMs) in the 10X Chromium instrument. Reverse transcription was performed on the GEMs, and RT products were purified and amplified. Expression libraries were made from the cDNA and profiled using the Bioanalyzer High Sensitivity DNA kit (Agilent Technologies) and quantified with Kapa Library Quantification Kit (Kapa Biosystems). Illumina HiSeq2500 (Illumina) was used to sequence the libraries.

  Dataset EGAD00001011041

• The Natural History of Human Prostate Cancer

  Whole genome DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of 3 men. For each of three different prostates, multiple tumour samples (4, 5, and 3 depending on the case) and one normal tissue sample were whole genome sequenced with a matched blood sample using the Illumiuna HiSeq platform. Tumour samples were sequenced to a target depth of 50X and normals and blood to a target depth of 30X. As of September 2020, some of the studies using these data include: Cooper et al, Nature Genetics 2015 (PMID: 25730763) Wedge et al, Nature Genetics 2018 (PMID: 29662167) Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)

  Dataset EGAD00001000689

• Clinical Utility of BRCA Research by Inocras, CMC and SMC (CUBRICS)

  This dataset consists of transcriptome data available for most cases of the whole-genome sequences from 1,364 Korean breast cancers

  Dataset EGAD50000001993

• Nanopore Telomere Sequencing of II.3, II.4, and III.4

  This datasets contains the putative telomeric sequences isolated by TARPON in ubam format after using a Duplex Capture Based Enrichment Protocol for patients II.2, II.4, and III.4.

  Dataset EGAD50000002363

• HOVON152 Trial Targetted Sequencing

  Associated with Molecular profiling of HGBCL-DH-BCL2 patients treated in the HOVON-152 triaL. Targeted sequencing of 30 samples from 30 High-grade B-cell lymphoma patients. Targeted sequencing was used for identify genomic alterations associated with patient outcome.

  Dataset EGAD50000002093

• NICHE - DNA-seq of MMR proficient early stage colon cancers

  The dataset includes 152 FASTQ files from paired-end WXS sequencing on Illumina HiSeq2500 or Novaseq 6000 for 31 pMMR patients. This includes 31 tumor DNA and 31 blood germline samples.

  Dataset EGAD50000001247

• RNAseq TPM

  RNAseq TPM matrix (transcriptome profiling by high-thoughput sequencing) Matrix (30,727 features by 2,803 samples) of log2-transformed TPM counts from RNAseq data for the four IMvigor trials.

  Dataset EGAD50000001100

• Whole Genome - HAP-1 clones

  Whole genome sequencing on HAP-1 clones wild-type or knockout for MBD4 and/or TDG. Libraries were prepared using the Kapa HyperPrep kit (Roche, 07962363001). Paired-end libraries (2 x 100 bp) were sequenced on a NovaSeq 6000 instrument (Illumina).

  Dataset EGAD50000000765

• WES patients with colorectal polyposis

  Twenty-seven patients were included and subjected to germline WES using NovaSeq 6000 platform. After filtering out variants for sequencing quality, variant allele fraction frequency, and population frequency, variants were manually prioritized by the ACMG criteria.

  Dataset EGAD50000000842

• Dataset for WGS head and neck cancer samples

  This dataset contain WGS sequencing data of head and neck cancer samples as well as blood plasma controls. Sequencing was performed on Illumina Novaseq 6000 using KAPA HyperPrep Kit. The sequencing was always paired.

  Dataset EGAD50000000233

• Pacbio_methylation_cases

  The PacBio cases dataset for differential methylation analysis included 10 case samples with known KMT2A loss-of-function variants, 2 VUS samples. All samples were sequenced using PacBio Revio® HiFi reads at a matched coverage of 15X, and methylation was called using pb-cpg-tools on aligned BAM files.

  Dataset EGAD00010002807

• WCDT deep RNA-seq

  This dataset includes fastq files for total RNAseq of 104 patient biopsies with metastatic castration resistant prostate cancer. The RNAseq libraries were rRNA depleted and sequenced at 150bp paired-end on Illumina Novaseq.

  Dataset EGAD00001008799

• Treatment arm information and sample sheet

  Table of treatment arm information for the 418 RNAseq evaluable population.

  Dataset EGAD00001009502

• Persistent Mutation Burden Drives Sustained Anti-Tumor Immune Responses.

  Data includes whole exome sequenced bam files for matched tumor-normal pairs from the study.

  Dataset EGAD00001009697

• Additional RNAseq data of metastatic breast cancer samples

  Paired-end RNA sequencing data from 33 metastatic breast cancer samples. Sequencing was performed on the Illumina NovSeq 6000 using NEBNext Single Cell and Low Input RNA Library Prep Kit for Illumina.

  Dataset EGAD00001015678

• Genomic and transcriptomic determinants of host susceptibility, protection, and viral mutation in experimental SARS CoV-2 infection: RNA (2025-08-11)

  Single-cell profiling of healthy adult volunteers that were inoculated with SARS-CoV-2. . This dataset contains all the data available for this study on 2025-08-11.

  Dataset EGAD00001015679

• Dataset for ARHGAP11A knockout and control organoid cells.

  This dataset contains 9 RNA sequencing samples of hiPSC-derived forebrain organoid ARHGAP11A knockout and hiPSC-derived forebrain organoid control cells. Sequencing was performed on Illumina NovaSeq 6000. The sequencing was always paired.

  Dataset EGAD00001015706

• Dataset for ChIP and Transcriptomic sequencing of neuroblastoma tumor samples(hipo)

  This dataset contains ChIP and Transcriptomic sequencing of 32cneuroblastoma tumor samples. The sequencing was performed on Illumina HiSeq 2000 and Illumina HiSeq 4000 respectively.

  Dataset EGAD00001015808

• DEEP-IHEC-release-2017

  Raw data files for the German Epigenome Project (DEEP), IHEC/EpiRR submission of 2017. metadata available at: http://deep.dkfz.de/#/experiments

  Dataset EGAD00001003974

• RNA-Seq files for SJHGG study

  RNA-Seq files accompanying the paper titled "Somatic Histone H3 Mutations in Diffuse Intrinsic Pontine Gliomas and Non-Brainstem Paediatric Glioblastomas".

  Dataset EGAD00001003905

• NKI-AvL OpACIN RNA-seq of stage III melanoma patients

  The dataset “NKI-AvL OpACIN RNA-seq of stage III melanoma patients" includes 18 FASTQ files from single-end total RNA sequencing on Illumina HiSeq2500 for 18 stage III melanoma patients.

  Dataset EGAD00001004216

• NKI-AvL CRC-OVC DNA-seq

  The dataset “NKI-AvL CRC-OVC DNA-seq" includes 4 normal and 4 tumor BAM files from paired-end whole exome sequencing on Illumina HiSeq2500 and Illumina NovaSeq6000 for 2 colorectal cancer and 2 ovarian cancer patients.

  Dataset EGAD00001004340

• ATAC-Seq of human CD4 Treg cells

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs). It includes whole genome sequence data for ATAC-seq (114 samples) The final quality filtered set included 73 individuals with ATAC-seq.

  Dataset EGAD00001005002

• DESIGN-NKI RNA-seq

  RNA-Seq data of 36 HPV-negative HNSCC specimens from patients treated at The Netherlands Cancer Institute, Amsterdam. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for polyA mRNA sequencing.

  Dataset EGAD00001005715

• DESIGN-NKI low coverage WGS

  Low-coverage whole genome sequencing data of 37 HPV-negative HNSCC specimens from patients treated at The Netherlands Cancer Institute. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for WGS to a depth of approx. 0.5X.

  Dataset EGAD00001005718

• DESIGN-VUMC low coverage WGS

  Low-coverage whole genome sequencing data of 37 HPV-negative HNSCC specimens from patients treated at the VU Medical Centre, Amsterdam. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for WGS to a depth of approx. 0.5X.

  Dataset EGAD00001005719

• NKI-MET HNSCC RNA-Seq

  RNA-Seq data of 8 HNSCC specimens from patients diagnosed with metastatic disease at The Netherlands Cancer Institute, Amsterdam. Primary HNSCC biopsy samples obtained prior to treatment were used for polyA mRNA sequencing.

  Dataset EGAD00001005720