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• Relapse series of two Pediatric ALL patients

  In this proof of principle study, we performed whole genome sequencing of two cases with multiple relapses in order to investigate whether groups of mutations separated in time show distinct mutational signatures. In patient 1, who experienced two relapses, the analysis unraveled a continuous interplay of aberrant AID/APOBEC-associated activities. Patient 2 had three relapses. We identified episodic mutational processes at diagnosis and first relapse leading to mutations resembling UV light-driven DNA damage, and thiopurine-associated damage at first relapse.

  Study EGAS00001005001

• Tissue DNA, WBC DNA and cfDNA (deep-)sequencing of mCRC patients treated with doublet chemotherapy and anti-EGFR in the CAIRO5 study

  This study assessed whether ctDNA based treatment response monitoring could be performed in a tumor tissue-independent manner by combining ultra-deep targeted sequencing analyses of cfDNA with patient-matched white blood cell (WBC) derived DNA. In total, 183 cfDNA and 49 WBC samples, along with 28 tissue samples, from 52 metastatic colorectal cancer patients participating in the prospective phase III CAIRO5 clinical trial (NCT02162563) were analyzed using the PGDx elio plasma resolve assay.

  Study EGAS00001006695

• Lung_Cell_Atlas__Paediatric_RNA

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets

  Study EGAS00001008299

• Cold Ischemia Study

  This study aimed to evaluate the impact of cold ischemia time on the expression of cancer-related genes, particularly those involved in hypoxia, apoptosis, and epithelial-to-mesenchymal transition (EMT). We performed RNA sequencing on 54 normal colon mucosa samples from nine patients undergoing colorectal cancer surgeries, freezing samples at predefined intervals ranging from 0 to 60 minutes. A total of 44 differentially expressed genes (DEGs) (p < 0.05) were identified when comparing samples frozen immediately (T0) with those frozen after 60 minutes (T5).

  Study EGAS00001008233

• Lung_Cell_Atlas__Paediatric_Spatial

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets

  Study EGAS00001008300

• Immune activation in the tumor microenvironment of renal cell carcinoma

  Study describes immunological responses to immunotherapy (anti-PD-1, pembrolizumab) and targeted therapy (VEGFR inhibition, axitinib) as well as anti-CD3/CD28/CD2 (Immunocult) in a patient-derived ex vivo tumor model of renal cell carcinoma. Patient-derived ex vivo tumor models were established and their treatment response studied using material from eight renal cell carcinoma patients. Samples were collected under informed consent in HUS Helsinki University Hospital, Finland. The study aims to understand immunological treatment responses in the patient tumor microenvironment.

  Study EGAS50000001349

• Genome and transcriptome sequence data from a metastatic cholangiocarcinoma patient

  Genome and transcriptome sequence data from a metastatic cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002976

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002972

• Genome and transcriptome sequence data from a rectal adenocarcinoma patient

  Genome and transcriptome sequence data from a rectal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002973

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002991

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002996

• WGS and RNA-Seq data from a GBM patient PT-AB6372

  WGS and RNA-Seq data from a GBM patient PT-AB6372

  Dataset EGAD00001004222

• WGS and RNA-Seq data from a GBM patient PT-AL4257

  WGS and RNA-Seq data from a GBM patient PT-AL4257

  Dataset EGAD00001004225

• WGS and RNA-Seq data from a GBM patient PT-AR5365

  WGS and RNA-Seq data from a GBM patient PT-AR5365

  Dataset EGAD00001004227

• WGS and RNA-Seq data from a GBM patient PT-CA2271

  WGS and RNA-Seq data from a GBM patient PT-CA2271

  Dataset EGAD00001004230

• WGS and RNA-Seq data from a GBM patient PT-CM1209

  WGS and RNA-Seq data from a GBM patient PT-CM1209

  Dataset EGAD00001004231

• WGS and RNA-Seq data from a GBM patient PT-DF5919

  WGS and RNA-Seq data from a GBM patient PT-DF5919

  Dataset EGAD00001004232

• WGS and RNA-Seq data from a GBM patient PT-DS9789

  WGS and RNA-Seq data from a GBM patient PT-DS9789

  Dataset EGAD00001004233

• WGS and RNA-Seq data from a GBM patient PT-EV3071

  WGS and RNA-Seq data from a GBM patient PT-EV3071

  Dataset EGAD00001004234

• 16S-based fecal microbiota composition

  The dataset reports the 16S rRNA gene sequencing of the fecal microbiota of donors from the Milieu Intérieur Cohort. The Milieu Intérieur cohort includes a total of 1,000 healthy individuals of western European ancestry, recruited in France as part of the Milieu Intérieur project. To assess their fecal microbiota composition, 16S rRNA profiles were generated from stool samples of 863 of the 1,000 donors. Human stool samples were produced at home no more than 24 hours before the scheduled medical visit and collected in a double-lined sealable bag maintaining strict anaerobic conditions. Upon reception at the clinical site, the fresh stool samples were aliquoted and stored immediately at -80°C. DNA was extracted from stool and barcoding PCR was carried out using indexed primers targeting the V3-V5 region of the 16S rRNA gene. Equal volumes of normalized PCR reaction were pooled and thoroughly mixed. The amplicon libraries were sequenced on Illumina MiSeq.

  Dataset EGAD00001004979

• WGS and RNA-Seq data from a GBM patient PT-RV2286

  WGS and RNA-Seq data from a GBM patient PT-RV2286

  Dataset EGAD00001008527

• WGS and RNA-Seq data from a GBM patient PT-WR7927

  WGS and RNA-Seq data from a GBM patient PT-WR7927

  Dataset EGAD00001008531

• WGS and RNA-Seq data from a GBM patient PT-WT4796

  WGS and RNA-Seq data from a GBM patient PT-WT4796

  Dataset EGAD00001008532

• WGS and RNA-Seq data from a GBM patient PT-DM9089

  WGS and RNA-Seq data from a GBM patient PT-DM9089

  Dataset EGAD00001008518

• WGS and RNA-Seq data from a GBM patient PT-BM8772

  WGS and RNA-Seq data from a GBM patient PT-BM8772

  Dataset EGAD00001008516

• WGS and RNA-Seq data from a GBM patient PT-CM3220

  WGS and RNA-Seq data from a GBM patient PT-CM3220

  Dataset EGAD00001008517

• WGS and RNA-Seq data from a GBM patient PT-GE7528

  WGS and RNA-Seq data from a GBM patient PT-GE7528

  Dataset EGAD00001008519

• WGS and RNA-Seq data from a GBM patient PT-GI2070

  WGS and RNA-Seq data from a GBM patient PT-GI2070

  Dataset EGAD00001008520

• WGS and RNA-Seq data from a GBM patient PT-JR9883

  WGS and RNA-Seq data from a GBM patient PT-JR9883

  Dataset EGAD00001008521

• WGS and RNA-Seq data from a GBM patient PT-LC6372

  WGS and RNA-Seq data from a GBM patient PT-LC6372

  Dataset EGAD00001008522

• WGS and RNA-Seq data from a GBM patient PT-ML9537

  WGS and RNA-Seq data from a GBM patient PT-ML9537

  Dataset EGAD00001008523

• WGS and RNA-Seq data from a GBM patient PT-PR5617

  WGS and RNA-Seq data from a GBM patient PT-PR5617

  Dataset EGAD00001008525

• Roche multiple sclerosis dataset

  The Roche multiple sclerosis dataset (Roche_MS) consists of 166 cortical grey matter (GM) and white matter (WM) samples from 83 unique individuals (29 controls and 54 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 EGAD00001009169

• Bulk RNAseq gene expression of baseline tumors from metastatic urothelial bladder cancer patients (IMvigor210) and metastatic renal cell carcinoma (IMmotion150)

  We examined tumors from a large cohort of patients with metastatic urothelial bladder cancer (mUC) and metastatic renal cell carcinoma (mRCC) treated with an anti-PD-L1 agent (atezolizumab) and found that high tumor IL8 gene expression was associated with worse overall survival (OS). We further identified the tumoral immune presence based on Teff signature. We found that high tumor IL8 expression continued to be associated with worse OS even in inflamed tumors in mUC and mRCC.

  Study EGAS00001004386

• A Single Cell Atlas of MMRd and MMRp Colorectal Cancer

  Immune responses to cancer vary across cancer types and patients. Colorectal cancer tumors with mismatch repair-deficiency (MMRd) show an elevated immune cell activity as compared to mismatch repair proficient (MMRp) tumors. To understand the immune response patterns in these two types of colorectal cancer, we transcriptionally profiled 371,223 tumor and adjacent normal cells from 28 MMRp and 34 MMRd patients. Unsupervised analysis identified 88 cell subsets, from 7 distinct cell clusters (that contain epithelial, malignant, stromal and immune cell lineages), and an associated compendium of 204 gene expression programs. Examination of these cell subsets and programs revealed extensive transcriptional and spatial remodeling of malignant, stromal and immune cells in MMRd and MMRp tumors. This dataset was generated as part of a published study (Pelka, Hofree, Chen, et al., Cell 2021 Sep 2;184(18):4734-4752; PMID: 34450029).

  Study phs002407

• A mechanistic classification of clinical phenotypes in neuroblastoma

  Clinical courses of the pediatric tumor neuroblastoma range from fatal progression to spontaneous regression. To gain insights into the pathogenesis of these divergent subtypes, we performed massively parallel sequencing of 416 pretreatment neuroblastomas and assessed telomere maintenance mechanisms in 208/416 cases. We observed that telomere maintenance and mutations in RAS or p53 pathway genes strongly affected disease courses. Fatal outcome occurred only in the presence of telomere maintenance, whereas patients whose tumors lacked such mechanisms had excellent outcome. In patients with telomere maintenance-positive tumors, survival was dramatically inferior when additional RAS/p53 pathway mutations were present. By contrast, spontaneous regression occurred both in the presence and absence of RAS/p53 pathway mutations in patients with telomere maintenance-negative tumors. Together, our data provide a precise mechanistic classification of clinical neuroblastoma phenotypes based on telomere maintenance mechanisms and genetic alterations of the tumor.

  Study EGAS00001003244

• 13 WGS and 8 TCS data of ENKL patients treated with pembrolizumab.

  Whole-genome sequencing (WGS) was performed for 13 pairs of tumor-normal samples from patients diagnosed with NKTL. Genomic DNA from tumor tissue was extracted with QIAamp DNA Mini Kit. The DNA for the matching normal was obtained from blood or buccal swabs and purified by Blood and Cell Culture DNA Mini kit or E.Z.N.A. Tissue DNA Kit (Omega Bio-tek) according to manufacturer’s instructions. The quantity and quality were assessed by Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen) and agarose gel electrophoresis. All sequencing libraries were prepared using TruSeq Nano DNA Library Prep Kit (Illumina). Paired-end sequencing was performed on Illumina HiSeq 2000 or HiSeq X Ten as 2x101 bp or 2x151 bp, respectively. 8 NKTL FFPE specimens were screened for somatic mutations using deep targeted capture sequencing (TCS). FFPE rolls or slides were extracted using QIAamp DNA FFPE Tissue kit (QIAGEN). The FFPE genomic DNA was treated with NEBNext FFPE DNA Repair Mix and assessed by Quant-it PicoGreen dsDNA Assay Kit (Invitrogen). The library was generated from 10-200 ng DNA with SureSelectXT Low Input Target Enrichment System for Illumina Paired-End Sequencing Library (Agilent Technologies) according to manufacturer’s instructions. RNA based probe was designed with SureDesign (Agilent Technologies) to target-capture 140 genes. Next, the captured libraries were pooled in equimolar concentration and sequenced on Illumina Novaseq 6000 platform with SP or S1 chip. Reads aligning to 40 selected genes were isolated post-alignment for this submission. Prefix used in filenames: T - Tumor samples N - Matched-Normal samples

  Dataset EGAD00001004140

• DAC for achalasia risk consortium (arc)

  Dac EGAC00001000394

• DAC for aflatoxin project Qidong patient samples

  Dac EGAC00001000679

• DAC for the cfSort study (tissue deconvolution)

  Dac EGAC00001003222

• DAC for seminoma genomic data

  Dac EGAC00001000231

• DAC for study WES of pituitary tumors

  Dac EGAC00001000443

• Data Access Committee for Hui Lab

  Dac EGAC00001000454

• INRP - Italian Network for Research on Psychoses

  Dac EGAC00001000576

• DAC for MOMA, Short QT Exome data

  Dac EGAC00001000730

• DAC for Dissecting Tumor Microenvironment with Tumorgrafts

  Dac EGAC00001000809

• Data Access Committee for data from EGAS00001002840

  Dac EGAC00001000834

• DAC for human single nuclei RNAseq of Epilepsy

  Dac EGAC00001000860

• Data Access Committee for the CentralAfricanCMC_Pemberton dataset

  Dac EGAC00001000896

• Laboratory for Neurobiology (VIB-KU Leuven)

  Dac EGAC00001001282

• DAC for HSTCL study. National Cancer Centre Singapore.

  Dac EGAC00001001302

• DAC for MEITL study. National Cancer Centre Singapore.

  Dac EGAC00001001323

• DAC for Phylogenetic reconstruction of breast cancer

  Dac EGAC00001001572

• Center for Technology Licensing at Cornell University

  Dac EGAC00001001587

• Data Access Commitee for single-cell analysis

  Dac EGAC00001001600

• DAC for Stuttgart Breast Cancer Cohort

  Dac EGAC00001001693

• Data Access Committee for data from EGAS00001004619

  Dac EGAC00001001712

• DAC for 16 year brca case report

  Dac EGAC00001001714

• Data Access Committee for data from EGAS00001004666

  Dac EGAC00001001756

• Data Access Committee for data from EGAS00001004455

  Dac EGAC00001001798

• Genentech DAC for IMmotion151

  Dac EGAC00001001813

• Single cell multi-omics (scNOVA) group for AML

  Dac EGAC00001001866

• Data Access Committee for IPF Collaboration

  Dac EGAC00001001878

• Center for Medical Genetics Data Access Commitee

  Dac EGAC00001001892

• DAC for cell free DNA TAPS study

  Dac EGAC00001001903

• Data access committee for lung cancer

  Dac EGAC00001001942

• Data Access Committee for the MPNST project

  Dac EGAC00001001987

• DAC for single cell RNAseq in FL project

  Dac EGAC00001002114

• DAC-for-UniExome-EGA-upload-2021

  Dac EGAC00001002168

• DAC for Germline biallelic mutation

  Dac EGAC00001002423

• DAC for Identification of Germline Monoallelic Mutations

  Dac EGAC00001002461

• DAC for studying human normal breast cells

  Dac EGAC00001002481

• DAC for studying human normal breast cells

  Dac EGAC00001002498

• Annie Huang and the Hospital for Sick Children

  Dac EGAC01000000015

• Data Access Committee for the Berardi group

  Dac EGAC00001003392

• DAC for the study EGASXXX

  Dac EGAC00001002746

• DAC for Castleman. National Cancer Centre Singapore.

  Dac EGAC00001003328

• Data access committee for the HOMOCULTURGEN dataset

  Dac EGAC00001003485

• DAC for the study EGAS00001007247

  Dac EGAC00001003262

• PDiamond. DAC

  DAC for pdiamond project

  Dac EGAC50000000377

• DAC - Institute for Pharmacology and Toxicology

  Dac EGAC00001003385

• DAC_iCope

  DAC for the iCope submission

  Dac EGAC50000000696

• DAC for ALSPAC whole exome sequencing data

  Dac EGAC00001003496

• DAC for NMIBC study - UCLouvain

  Dac EGAC50000000789

• Data Access Committee for data from EGAS00001004454

  Dac EGAC00001002077

• LUMC Department Pediatrics, Laboratory for Pediatric Immunology

  Dac EGAC50000000822

• Data Access Committee for data from EGAS00001006662

  Dac EGAC00001003009

• Data Access Committee for data from EGAS00001005944

  Dac EGAC00001002583

• Tumor educated platelets for BrCA

  Study EGAS00001006821

• RNASeq for BMI GL study

  Study EGAS00001004127

• EGAD00010000606

  SNP6 data for matched normal samples

  Dataset EGAD00010000606

• Exome sequencing of Congenital Heart Disease families Toronto

  The exome sequencing is performed using Agilent SureSelect 50Mb exome v3 and Hiseq 75bp paired reads with an mean sequencing coverage target of 50X.

  Dataset EGAD00001000799

• Genetic analysis in lifestyle-related disease, arteriosclerotic disease, and aging-related diseases.

  Exome sequence analysis was conducted in patients with hypertension (Stage 3). Rare variants in candidate susceptible genes discovered by previous GWASs were prioritised and further analysed for an additional case-control association study.

  Study JGAS000016

• Mitochondrial DNA Mutations at Low-level Heteroplasmy in Chronic Kidney Disease

  To explore for relationship between somatic or heteroplasmic mutations of mtDNA and kidney function, we here performed ultra-deep sequencing based on long-range PCR from DNAs of 78 CKD kidney tissues.

  Study JGAS000611

• A_study_of_the_molecular_pathogenesis_of_Splenic_Marginal_Zone_and_Diffuse_Large_B_Cell_Lymphoma

  We will perform exome sequencing on selected cases of splenic marginal zone lymphoma (SMZL) and diffuse large B-cell lymphoma (DLBCL) in order to characterise their genetic makeup and identify biomarkers for prognosis and prediction of treatment response.

  Study EGAS00001000335

• CIAO Clinical Trial

  Whole exome and RNA sequencing for samples from CIAO (Checkpoint Inhibitors Assessment in Oropharynx cancer) (NCT03144778) clinical trial testing neoadjuvant anti-PD-L1 durvalumab with or without the anti-CTLA-4 tremelimumab in oropharynx cancer

  Study EGAS50000001174

• Diverse Cellular Composition in Alveolar Rhabdomyosarcoma Revealed by Single Cell RNA Sequencing

  Using single cell RNAseq data to characterize tumor composition and cellular states for Alveolar Rhabdomyosarcoma. We find that that ARMS tumors harbor phenotypically and transcriptionally distinct malignant subpopulations within an immune-influenced microenvironment.

  Study EGAS50000001564

• Whole-exome analysis of corticotropin-independent Cushing's syndrome

  We performed WES for 8 cases with corticotropin-independent Cushing’s syndrome, in whom paired tumor and normal DNA was obtained from fresh frozen adenomas and either normal adrenal tissues or peripheral blood, respectively.

  Study EGAS00001000661

• Genetics_and_Networks_of_Congenital_Heart_Defects

  Exome sequencing of families with Congenital Heart Defects of diverse sub-phenotypes. Comprises both parent-offspring trios for sporadic cases and multiplex families. Collaboration with David Brook, University of Nottingham. Funded by the British Heart Foundation.

  Study EGAS00001000762

• Single-sell RNA sequencing counts from 7 acute myeloid leukemia patients and 3 healthy donors

  This dataset contains count data (from 10X CellRanger) and metadata from 7 acute myeloid leukemia subjects treated with chemotherapy, as well as data from 3 healthy donors. Additionally, the dataset includes VDJ data for all subjects except for 31_base and the 3 healthy donors (TCRseq not performed).

  Dataset EGAD50000000525