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• 10x Genomics Single Cell Gene Expression for SA1091AX1XB01790

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1091 passage 1

  Dataset EGAD00001009130

• 10x Genomics Single Cell Gene Expression for SA1093CX1XB01917

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1093 passage 1

  Dataset EGAD00001009129

• 10x Genomics Single Cell Gene Expression for SA1053FX1XB01611

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009128

• 10x Genomics Single Cell Gene Expression for SA1052BX1XB01516

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1052 passage 1

  Dataset EGAD00001009127

• 10x Genomics Single Cell Gene Expression for SA1050DX1XB01437

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009126

• 10x Genomics Single Cell Gene Expression for SA1050FX1XB01446

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009125

• 10x Genomics Single Cell Gene Expression for SA604X8XB02164

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 8

  Dataset EGAD00001009118

• 10x Genomics Single Cell Gene Expression for SA604X6XB01979

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 6

  Dataset EGAD00001009117

• 10x Genomics Single Cell Gene Expression for SA1054

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 83.86

  Dataset EGAD00001009113

• 10x Genomics Single Cell Gene Expression for SA1056

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 116.126

  Dataset EGAD00001009112

• 10x Genomics Single Cell Gene Expression for SA1188

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTert L9 116.66

  Dataset EGAD00001009114

• 10x Genomics Single Cell Gene Expression for SA604X7XB02089

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 7

  Dataset EGAD00001009119

• 10x Genomics Single Cell Gene Expression for SA609X6XB01899

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA609 passage 6

  Dataset EGAD00001009120

• 10x Genomics Single Cell Gene Expression for SA1049AX1XB01417

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1049 passage 1

  Dataset EGAD00001009121

• 10x Genomics Single Cell Gene Expression for SA1052DX1XB01519

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1052 passage 1

  Dataset EGAD00001009122

• 10x Genomics Single Cell Gene Expression for SA1053EX1XB01608

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009123

• 10x Genomics Single Cell Gene Expression for SA1051AX1XB01452

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1051 passage 1

  Dataset EGAD00001009124

• 10x Genomics Single Cell Gene Expression for SA535X6XB03099

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 6

  Dataset EGAD00001009116

• 10x Genomics Single Cell Gene Expression for SA535X4XB05462

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 4

  Dataset EGAD00001009115

• 10x Genomics Single Cell Gene Expression for SA1055

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 112.109

  Dataset EGAD00001009111

• Tumour sample for patient SA530

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA530

  Dataset EGAD00001009191

• Tumour sample for patient SA404

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA404

  Dataset EGAD00001009190

• Tumour sample for patient SA402

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA402

  Dataset EGAD00001009189

• Tumour sample for patient SA398

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA398

  Dataset EGAD00001009188

• Tumour sample for patient SA395

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA395

  Dataset EGAD00001009187

• Tumour sample for patient SA394

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA394

  Dataset EGAD00001009186

• Tumour sample for patient SA287

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA287

  Dataset EGAD00001009185

• Tumour sample for patient SA283

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA283

  Dataset EGAD00001009184

• Tumour sample for patient SA279

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA279

  Dataset EGAD00001009183

• Tumour sample for patient SA276

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA276

  Dataset EGAD00001009182

• Tumour sample for patient SA275

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA275

  Dataset EGAD00001009181

• Tumour sample for patient SA274

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA274

  Dataset EGAD00001009180

• Tumour sample for patient SA272

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA272

  Dataset EGAD00001009179

• Tumour sample for patient SA219

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA219

  Dataset EGAD00001009178

• Tumour sample for patient SA218

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA218

  Dataset EGAD00001009177

• A96177B

  Whole genome sequencing for single cells for library A96177B 683 samples; filetype=bam

  Dataset EGAD00001008244

• A96174B

  Whole genome sequencing for single cells for library A96174B 1447 samples; filetype=bam

  Dataset EGAD00001008242

• A96165A

  Whole genome sequencing for single cells for library A96165A 779 samples; filetype=bam

  Dataset EGAD00001008239

• A96155B

  Whole genome sequencing for single cells for library A96155B 1028 samples; filetype=bam

  Dataset EGAD00001008236

• A96145A

  Whole genome sequencing for single cells for library A96145A 642 samples; filetype=bam

  Dataset EGAD00001008232

• A95732B

  Whole genome sequencing for single cells for library A95732B 655 samples; filetype=bam

  Dataset EGAD00001008231

• A95707A

  Whole genome sequencing for single cells for library A95707A 1359 samples; filetype=bam

  Dataset EGAD00001008228

• A95664B

  Whole genome sequencing for single cells for library A95664B 630 samples; filetype=bam

  Dataset EGAD00001008227

• RNA-Seq dataset for Genomic rearrangements in Pediatric Cancer

  RNA-Seq data for systematic gene fusion detection in Pediatric Cancer

  Dataset EGAD00001008152

• A96233A

  Whole genome sequencing for single cells for library A96233A 637 cells; filetype=bam

  Dataset EGAD00001007622

• A95730A

  Whole genome sequencing for single cells for library A95730A 739 cells; filetype=bam

  Dataset EGAD00001007614

• A108833B

  Whole genome sequencing for single cells for library A108833B 866 cells; filetype=bam

  Dataset EGAD00001007594

• A108735A

  Whole genome sequencing for single cells for library A108735A 714 cells; filetype=bam

  Dataset EGAD00001007593

• A96114A

  Whole genome sequencing for single cells for library A96114A 798 cells; filetype=bam

  Dataset EGAD00001007615

• RNA-sequencing of meningiomas for integrative molecular classification.

  RNA-sequencing of meningiomas for integrative molecular classification.

  Dataset EGAD00001007494

• Sequencing data for oesophageal and related samples - Xiaodun Li et al (WGS, RNA)

  Data supporting: "Esophageal adenocarcinoma organoid cultures recapitulate human disease heterogeneity and provide a model for clonality studies and precision therapeutics." Li et al. WGS (BAM files) RNAseq (BAM files) Tumours, organoids, normals

  Dataset EGAD00001004007

• PacBio WGS based analysis of complex chromosomal rearrangements

  The dataset consists of a single sample whereby the genomic DNA was analysed using PacBio WGS at 30x coverage to assess the breakpoint sites of complex chromosomal rearrangements.

  Dataset EGAD00001015593

• Mesothelioma of the peritoneum and Pseudomyxoma peritonei

  Mesothelioma of the peritoneum (n=21) and Pseudomyxoma peritonei/mucinous adenocarcinoma of the appendix (n=11)

  Dataset EGAD00001008826

• Sequencing data of the CTSC gene after WGS of samples from individuals with PLS

  The sequencing data of the CTSC gene after whole genome sequencing of blood samples from two individuals with Papillon-Lèfevre Syndrome.

  Dataset EGAD00001006961

• Genomic Characteristics of Myeloproliferative Neoplasms in Patients Exposed to Ionizing Radiation following the Chernobyl Nuclear Accident

  The study "Genomic Characteristics of Myeloproliferative Neoplasms in Patients Exposed to Ionizing Radiation following the Chernobyl Nuclear Accident" was designed as case-control study. We studied genomic characteristics of chronic Philadelphia chromosome-negative myeloproliferative neoplasm (MPNs) in Ukrainian patients who were previously exposed to Ionizing Radiation (IR) due to Chernobyl accident in comparison to unexposed MPN patients and controls (previously exposed to IR due to Chernobyl accident and unexposed people who were not diagnosed with any oncological condition at the moment of DNA sampling).

  Study phs001761

• GCAT| WGS FASTQ V1

  This dataset include FASTQ files of 808 samples from GCAT cohort. Technology used HiSeq 4000, read length 150 bp, inner mate distance 300 bp. For each sample the paired -ends are generated in separated files. Each FASTQ is splitted in multiple LANEs and grouped by the Multiplex index.

  Dataset EGAD00001008201

• Mutational_Signatures_of_relapse_in_rectal_cancer_FFPE_samples_in_the_CR07_clinical_trial

  The CRO7 clinical trial recruited patients with clinically operable rectal adenocarcinoma. Patients were randomized to either pre-operative short course surgery followed by chemo-radiotherapy only in those patients at high risk of local relapse. Patients in both arms the received standard %-FU based adjuvant chemotherapy as per local policy. We intend to use FFPE derived DNA from the primary tumours to identify patterns of mutations or copy number alterations that are predictive of local or distant relapse.

  Study EGAS00001000651

• Single-cell RNA-sequencing and cellular indexing of transcriptomes and epitopes of peripheral blood mononuclear cells and peritoneal fluid from patients with achalasia

  The data published here contains cellular indexing of transcriptomes and epitopes (CITE-seq) and single-cell RNA- sequencing (scRNAseq) data on patients with achalasia. Paired PBMC and PF were subjected to 3' scRNAseq and CITE-seq, respectively. All single-cell data was generated using the 10X Genomics (Chromium Single Cell 3’ Reagent) and sequenced in a paired-ended fashion on the NovaSeq6000.

  Study EGAS50000000174

• Whole genome sequencing of PDAC tissues an PDOs

  whole genome sequencing (WGS) on 48 PDOs (established from 39 tumors) and 4 tissues samples. The majority of PDOs were established from treatment-naive and localized tumors. Histopathologically, the majority of PDAC tumors from which PDOs were established displayed a conventional morphological pattern, with two containing squamous components (defined as adenosquamous), and one classified as a signet-ring tumour. 7 of the PDOs were grown in a culture medium lacking both WNT3A and RSPO1.

  Study EGAS50000000193

• APCDR AGV Project: Whole genome sequencing of 3 African populations (curated data)

  The African Genome Variation Project (AGVP) provides a resource to help design, implement and interpret genomic studies in sub-Saharan Africa (SSA) and worldwide. The AGVP represents dense genotypes from 1,481 and whole genome sequences (WGS) from 320 individuals across SSA. As part of the AGVP we sequenced 3 African populations; Baganda from Uganda (4x), Zulu from South Africa (4x), Gumuz, Wolayta, Oromo, Somali and Amhara from Ethiopia (8x).

  Study EGAS00001000960

• Bulk RNA-sequencing data of advanced hepatocellular carcinoma (HCC) patients treated with atezolizumab plus bevacizumab.

  The dataset includes FASTq files and normalised gene expression counts from bulk RNA-sequencing of pre-treatment tumour (n=39) and adjacent non-tumour tissue samples (n=13) from advanced hepatocellular carcinoma (HCC) patients treated with atezolizumab plus bevacizumab. Specifically, RNA was extracted from the FFPE tumour tissue using RNeasy Plus Mini Kit (Qiagen), according to the manufacturer’s instructions. RNA quality and quantity were evaluated using Agilent RNA 600 Pico Chips (Agilent Technologies). Sequencing libraries were prepared using the SMARTer Stranded Total RNA-seq kit v3 (Takara Bio). Sequencing was performed on an Illumina NovaSeq 6000 system. After obtaining the Fastq files, read 2 UMIs and adapters were trimmed using seqtk (v1.2), reads were aligned using STAR (v2.7.7a) to the human reference genome (GRCh38) and quantified with HTSeq (v2.0.2).

  Dataset EGAD50000001227

• Cell of Origin and Early Evolution of Leukemia in Down Syndrome

  To investigate the mechanism by which GATA1s and STAG2 deficiency contribute to Down Syndrome leukemogenesis, specifically within the propagating CD34/CD117 cell fractions from primary xenografts, we carried out transcriptional and epigenetic profiling by RNAseq and ATACseq. The chromatin accessibility landscape was compared to bulk ATACseq of individually sorted N-FL HSPC subpopulations. To investigate the mechanism underlying the synergy between T21 and GATA1s in driving preleukemia development, we analyzed the binding occupancy of GATA1. We performed Cut&Run assays to profile genome-wide GATA1 binding sites and also to quantify binding changes upon GATA1s editing in N-FL and T21-FL CD34+ enriched HSPCs. Lastly, we profiled miRNAs from N-FL and T21-FL CD34+ enriched HSPCs by miRNA-Seq.

  Dataset EGAD00001006555

• Mutational_burden_in_oesophagus_following_chemotherapy_and_radiotherapy_treatment_WGS

  We wish to assess the changes in signature and mutational burden in patients who have undergone either chemotherapy or chemotherapy + radiotherapy. Using duplex sequencing will assess the mutational landscape in oesophageal epithelia in patients who have undergone these treatment regimes.

  Study EGAS00001007415

• Monotherapy_Breast_Cancer

  These samples are from locally advanced breast cancers that have been treated with epirubicin monotherapy before surgery. We will sequence some samples from patients with good response to the therapy and some with poor response to the therapy.

  Study EGAS00001000165

• Discovery_of_resistance_mechanisms_to_the_BRAF_inhibitor_vemurafenib_in_metastatic_BRAF_mutant_melanoma

  Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma by massively-parallel sequencing of tumour samples. Comparison of genomic characteristics of pretreatment ‘sensitive’ to recurrence ‘resistant’ tumours to identify the genetics of drug resistance.

  Study EGAS00001000551

• G3BP2-KIT drives leukemia amenable to kinase inhibition in Ph-like ALL

  We describe a patient with Ph-like ALL, in which leukemic cells harbored an in-frame fusion between the GTPase-activating protein (SH3 domain)-binding protein 2 (G3BP2) and the KIT proto-oncogene.

  Study EGAS00001005181

• COIN CRC GWAS data

  Genotype data from the COIN and COIN-B trials of advanced/metastatic colorectal cancer. Data provided in plink format, and has been quality controlled. Control data used was from the WTCCC2 project National Blood Donors (NBS) Cohort (EGAD00000000024).

  Study EGAS00001005421

• INDIA

  We collected PBMCs from 10 Indian and 10 Dutch individuals before BCG vaccination and 10-12 post-vaccination. We assessed the open chromatin profiles under baseline conditions, and the transcriptomic profiles upon stimulation with Influenza and SARS-CoV-2.

  Study EGAS00001006417

• M116 DNA Methylation Array

  DNA samples were quantified with Qubit BR kit on a Qubit2.0 fluorimeter (ThermoFisher Scientific), and integrity was checked using agarose gel electrophoresis. DNA from samples passing the quality control was bisulfite-converted using the EZ DNA Methylation-Gold™ Kit (Zymo Research, Cat. D5005) following the manufacturer's instructions. Then, bisulfite-converted DNA was hybridized into the Methylation EPICv1.0 BeadChip (Illumina) array interrogating > 850,000 CpG sites according to manufacturer's instructions

  Dataset EGAD50000001678

• Single-cell transcriptomic analyses of peritoneal metastases from patients with colorectal cancer metastasized to the peritoneum

  The data published here contains single-cell RNA-sequencing (scRNAseq) data as obtained using the 3' scRNAseq using Chromium Single Cell 3’ Reagent from 10X Genomics on peritoneal metastases (PM) from patients with colorectal cancer (CRC) and PM. Sequencing was performed in a paired-ended fashion on the NovaSeq6000.

  Dataset EGAD50000000249

• Single-cell transcriptomic analyses of peritoneal fluid from patients with colorectal cancer metastasized to the peritoneum

  The data published here contains single-cell RNA-sequencing (scRNAseq) data as obtained using the 3' scRNAseq using Chromium Single Cell 3’ Reagent from 10X Genomics on peritoneal fluid (PF) from patients with colorectal cancer (CRC) and peritoneal metastases (PM). Sequencing was performed in a paired-ended fashion on the NovaSeq6000.

  Dataset EGAD50000000248

• Whole exome sequencing data of Hispanic hepatocellular carcinoma

  The paired-end reads were aligned to the human reference genome (hg19) with decoy sequences (as used in the 1000 Genomes Project) using BWA (v0.7.5a) software. The duplicate reads were marked and subsequently removed using Picard (v1.140) (https://broadinstitute.github.io/picard/) and SAMtools (v0.1.19), respectively. Local realignment around insertions/deletions (indels) and base quality recalibration were performed using GATK (v3.6).

  Dataset EGAD00001011158

• BELOB: Ribo-minus RNA-seq data corresponding to 96x GBM samples from the BELOB trial.

  Ribo-minus RNA-seq data corresponding to 96x GBM samples from the BELOB trial.

  Study EGAS00001004570

• The genomic landscape of acute lymphoblastic leukemia with intrachromosomal amplification of chromosome 21

  Use scRNA-seq data from 4 iAMP21 patients to study the clonal evolution of iAMP21.

  Study EGAS00001006577

• HSP90 inhibitor resistant cells

  K562 cells were treated with different HSP90 inhibitors (PuH71 and Coumermycin A1) and the CNV profil was compared to the parental K562 (untreated). In addition, the CNV profile of HSP90AB1 knockout K562 cells was analyzed.

  Dataset EGAD00010002336

• The WID-BC-index identifies women with primary poor prognostic breast cancer based on DNA methylation in cervical samples

  A surrogate marker based on the epigenome that captures these components in easily accessible epithelial tissue could potentially identify women at risk. The WID-BC-index identifies women with breast cancer based on a DNA methylation signature derived from cervical smear samples.

  Study EGAS00001005055

• Columbia Alzheimer's sample (white matter)

  The Columbia Alzheimer’s dataset (white matter) consists of 24 white matter individuals (12 controls, 12 cases). A total of 12,000 estimated cells from each sample were loaded on the 10x Single Cell Next GEM G Chip. cDNA libraries were prepared using the Chromium Single Cell 3’ Library and Gel Bead v3 kit according to the manufacturer’s instructions. cDNA libraries were sequenced using the Illumina NovaSeq 6000 System and NovaSeq 6000 S2 Reagent Kit v1.5 (100 cycles), aiming at a sequencing depth of minimum 30K reads/nucleus.

  Dataset EGAD00001009168

• Intra-tumor heterogeneity and clonal evolution of papillary renal cell carcinoma

  Limited knowledge of intratumor heterogeneity (ITH), and clonal evolution of papillary renal cell carcinoma (pRCC) and rare kidney tumor subtypes hinders understanding of tumorigenesis and therapeutic efficacy. We conducted an integrative genomic and epigenomic ITH analysis and studied clonal evolutionary history of pRCC and rare kidney tumor subtypes. We dissected multiple consecutive samples from the center of the tumor towards the tumor's periphery, a normal sample ~5 cm distant from the tumor, and, where feasible, metastatic regions in the adrenal gland. Specifically, we performed 60X multi-region whole-genome sequencing (mWGS), both genome-wide methylation and SNP array profiling, and deep targeted sequencing (average 500X coverage) of 254 cancer driver genes (PMID:24390350). The study population comprises 39 patients with kidney cancers, including 23 with papillary type 1 (pRCC1), 12 with papillary type 2 (pRCC2), one of which also had areas of clear cell, and one each with collecting duct tumor (cdRCC), renal fibrosarcoma rSRC, mixed pRCC1/pRCC2, and an unclassified renal cancer with mixed features of pRCC2 and cdRCC. Based on DNA sample availability, we conducted whole genome sequencing (WGS) on 124 samples from 29 subjects, deep targeted sequencing on 139 samples from 38 subjects, SNP array genotyping on 101 samples from 38 subjects, and genome-wide methylation profiling on 139 samples from 28 subjects. All assays were performed on tumor, metastasis and normal tissue samples, with the exception of the SNP array genotyping, which was conducted only on tumor samples.

  Study phs001573

• Mapping the Human Connectome - Structure, Function, and Heritability: Healthy Young Adults (Age 22-35 Years) Including Twins and their Non-Twin Siblings

  The Human Connectome Project (HCP) has acquired vast amounts of data about the pattern of long-distance connections (wiring) in the brains of large numbers of healthy participants aged 22-35 using cutting-edge MRI and MEG neuroimaging, and extensive behavioral testing. Types of MR data collected included diffusion MRI (dMRI), resting-state functional MRI (r-fMRI), and structural MRI at both 3T and 7T, and task-evoked functional MRI (t-fMRI) at 3T. Following an extensive period of development and optimization of data acquisition and analysis methods, at Washington University in St. Louis we studied 1,206 participants comprising twins and their non-twin siblings. A subset of 184 twins was scanned again at the University of Minnesota using a 7T scanner. A different subset of 95 twins was studied at St. Louis University using combined resting state and/or task-activated MEG. We were able to collect genetic data on 1142 of our 1206 participants, including 149 pairs of genetically-confirmed monozygotic twins (298 participants) and 94 pairs of genetically-confirmed dizygotic twins (188 participants). Overall, there are 457 different families in the study, as determined by genetic analysis. Our rich set of imaging, behavioral and genetic data - available through the Human Connectome database - will enable many types of analysis of brain circuitry, its relationship to behavior, and the contributions of genetic and environmental factors to brain circuits.

  Study phs001364

• Analysis of the lung gene expression profile in COPD

  Samples obtained from patients with COPD and from controls by bronchoscopy from the lung were subjected to RNA seq.

  Study EGAS00001001472

• CRC GWAS on the Spanish population

  Genome-wide association study performed on the EPICOLON2 cohort, comprising colorectal cancer cases and matched controls of Spanish origin.

  Study EGAS00001003633

• analysis of T cell receptor repertoirs

  Full information about the T cell receptor (CR) variable regions found in the sequences of the vdj region. Columns: barcode is_cell contig_id high_confidence length chain v_gene d_gene j_gene c_gene full_length productive cdr3 cdr3_nt reads umis raw_clonotype_id raw_consensus_id

  Dataset EGAD00001008109

• The transcription factor GABP selectively binds and activates the mutant TERT promoter in cancer

  Dataset contains Exome-seq and RNA-seq from 2 GBM patients, as well as RNA-seq from the derived cultured cells (GNS).

  Dataset EGAD00001001359

• The Oral Microbiome and Head and Neck Cancer

  Oral microbiota may influence head and neck squamous cell carcinoma (HNSCC) development, potentially related to carcinogen metabolism. The human oral cavity hosts a diverse microbiota, including bacteria and fungi. We performed shotgun sequencing and ITS1 sequencing on 236 HNSCC case participants who developed HNSCC during a mean follow-up of 5.1 years and 458 matched controls who remained HNSCC-free. Oral samples were obtained from a prospective nested case-control study within three epidemiological cohorts: the American Cancer Society Cancer Prevention Study II Nutrition Cohort (ACS CPS-II), the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), and the Southern Community Cohort Study (SCCS). Control participants were selected using 2:1 frequency matching based on cohort, age, sex, race and ethnicity, and time since oral sample collection.

  Study phs004018

• The Dutch retinoblastoma research team from the VU University medical center

  Dac EGAC00001000431

• The APL DAC comprises a clinician and biologist who conducted the study.

  Dac EGAC00001000865

• Genomic Variation in Diffuse Large B Cell Lymphomas

  Integrative analysis of genetic lesions in 574 diffuse large B cell lymphomas (DLBCL). The study investigates genomic structural variation, genetic alteration and its effect on the development and biology of lymphomas by using high throughput sequencing, gene expression, and methylation status.

  Study phs001444

• Massively Parallel Single-Cell RNA-Sequencing of Chronic Rhinosinusitis Nasal and Sinus Tissue

  Single-cell RNA sequencing (scRNA-seq) using the SeqWell V1 platform on sinus mast cells flow cytometrically sorted from the nasal polyps of patients with chronic rhinosinsusitis (CRS) with nasal polyps (CRSwNP) and aspirin-exacerbated respiratory disease (AERD).

  Study phs002333

• Resolution of Ring Chromosomes, Robertsonian Translocations, and Complex Structural Variants from Long-Read Sequencing and Telomere-to-Telomere Assembly

  These data were generated to test the hypothesis that long-read whole genome sequencing and optical genome mapping could resolve clinically relevant human structural genomic variation involving complex and/or repetitive portions of the genome.

  Study phs003779

• Single-cell gene expression profiling of human iPSCs-derived cortical organoids

  To investigate the relationships between cerebral cortical organoid morphological characteristics and cellular composition, we morphologically classifi ed human iPSC-derived cortical organoids and analyzed the cellular makeup of each morphological type by single-cell gene expression profi ling.

  Study JGAS000726

• exploration of biomarkers in colorectal cancer

  Targeted therapies based on the molecular and histological features of cancer types are becoming standard practice. To understand the molecular basis of colorectal cancer, we performed CAGE (Cap Analysis of Gene Expression) to quantify promoter activities on 45 colorectal cancers.

  Study JGAS000489

• Elucidation of molecular mechanisms of tumorigenesis and development of diagnoses and treatments based on comprehensive genomic analyses in pancreatic tumors, duodenal tumors and biliary tumors

  We performed whole genome and whole exome sequencing analyses of pancreatic tumors, duodenal tumors and biliary tumors and investigated the molecular mechanisms of tumorigenesis based on the comprehensive genome profiling.

  Study JGAS000359

• RNA-Sequencing data of patient derived normal fibroblasts (NFs), cancer associated fibroblasts (CAFs) and tumor spheroid samples

  RNA-Sequencing data of patient derived normal fibroblasts (NFs), cancer associated fibroblasts (CAFs) and tumor spheroid samples performed in the context of the characterization of an IL1R1 positive CAF population in CRC tumour samples.

  Study EGAS00001007205

• Mutational_burden_in_oesophagus_following_chemotherapy_and_radiotherapy_treatment

  We wish to assess the changes in signature and mutational burden in patients who have undergone either chemotherapy or chemotherapy + radiotherapy. Using duplex sequencing will assess the mutational landscape in oesophageal epithelia in patients who have undergone these treatment regimes.

  Study EGAS00001005552

• WGS_skin_punches

  We wish to understand the degree of copy number alterations in normal human sun exposed skin. We have collected small punches of epithelia and using a bait set design have shown the these span a clone. WGS will provide copy number information on these.

  Study EGAS00001004465

• Paroxysmal_Neurological_Disorders___rare_epilepsies

  We are sequencing the exomes of patients with paroxysmal neurological disorders mainly focusing on migraine and epilepsy. Cases are collected from performance sites of members of EuroEPINOMICS. Most cases have a strong family history. The study sample will include both cases and controls.

  Study EGAS00001000421

• Low-coverage whole-sequencing of metastasised colorectal cancer samples treated with bevazicumab

  Low-coverage whole-genome sequencing (LC-WGS) was performed on tumor tissue, normal tissue and plasma samples collected from mCRC patients from the AC-ANGIOPREDICT Phase II trial (NCT01822444) and the University Medical Center Mannheim (UMM).

  Study EGAS50000000131

• Colorectal cancer functional annotation - MPRA

  We performed a Massively Parallel Reporter Assay (MPRA) in colorectal cancer (CRC) cell lines HT29 and SW403 and normal colon cell line HCEC-1CT. We specifically targeted the regions around the CRC GWAS loci to identify which variants alter transcription.

  Study EGAS50000000406

• Single-cell transcriptomics of neuroblastoma tumors

  Single-cell RNA-sequencing (CITE-seq) and single-nucleus RNA-sequencing data were generated from neuroblastoma patient tumors to uncover transcriptional heterogeneity at a single-cell resolution. In addition, we used the data to validate our findings of the NBAtlas.

  Study EGAS50000000223

• Transposome_Bisulfite_Sequencing

  DNA belonging to 16 tumour/normal samples were treated with bisulfite, then up to 5 different bisulfite PCRs were performed in each one of the samples. Amplicons form the same sample were pooled and submitted to sequencing on a MiSeq platform.

  Study EGAS00001000751