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• Single cell whole genome sequencing of high hyperdiploid acute lymphoblastic leukemia

  This dataset was collected from viable bone marrow cells obtained at diagnosis from nine patients with high hyperdiploid ALL and one normal bone marrow sample. All samples were subjected to low pass single cell whole genome sequencing with the median sequencing coverage of 0.02x. Single nuclei in G0/G1 phase were isolated using a fluorescence-activated cell sorting (FACS) cytometer. DNA libraries were constructed and associated next-generation sequencing was carried out by European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. Further details regarding the DNA libraries construction are available by Bos et. al., 2019 (https://link.springer.com/protocol/10.1007/978-1-4939-8931-7_15). The dataset has been used for copy number aberrations analysis.

  Study EGAS00001006347

• ATAC-Seq of inflamed and non-inflamed biopsies

  Inflamed and non-inflamed biopsies were digested for 45 minutes at 37ºC with collagenase from Clostridium histolyticum (Sigma). Suspension cells were then stained with an antibody cocktail to sort live CD8-CD4+ T cells. After isolating crude nuclei of two thousand live CD4+ T cells, they were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry.

  Study EGAS00001007344

• EGAD00010000538

  28 unlinked autosomal microsatellite loci for 20 African and 4 philippine populations

  Dataset EGAD00010000538

• RNA Editing Exome

  Exome sequencing data for tumor and matched normal samples of the EGAS00001000495 project.

  Dataset EGAD00001000626

• TP53_KO_RPE1_SNPs

  Allelic imbalance data for cell lines derived from RPE1 with TP53 knockout

  Dataset EGAD00010001566

• SOGEN_MATRILINEAL_PUZZLE

  598764 SNPs genotyped for 719 indivuals, merge from Illumina Omni1 and Illumina Omni2.5

  Dataset EGAD00010001724

• README-for-EGAS00001004349-linking-HIPO-K09R-WGS-files

  Dataset EGAD00001006739

• Genotypes_Agta

  Genotype data for Agta hunter-gatherers Philippines

  Dataset EGAD00010002140

• Access to dataset, "Feasibility of Functional Precision Medicine for Guiding Treatment of Relapsed/Refractory Pediatric Cancers"

  Access to sequencing data from project.

  Dac EGAC50000000124

• PGx validation GSAv3

  Samples genotyped using Illumina Infinium Global Screening Array v3 for assessing pharmacogenomic genes

  Dataset EGAD00010002645

• Internal Medicine II Technical University Munich DAC

  Data sharing agreement Klinikum rechts der Isar der Technischen Universität München for MEMORI NGS files

  Dac EGAC50000000165

• PDX WES for #87, #95, #32, #217, #86

  Exome sequencing of tumour PDX and matched patient blood

  Dataset EGAD50000000215

• SMPaeds cfDNA lcWGS

  Low coverage whole genome sequencing (0.5-4X) for cfDNA collected from blood plasma.

  Dataset EGAD50000000782

• Indonesian Genome Diversity Project 3

  Term and condition for Indonesian Diversity Project v3. 254 Low Coverage genome from Wallacean and West Papuan, Indonesia

  Dac EGAC50000000312

• DAC for Hematological toxicity following CAR-T cells injection

  Data access committee to have access to Hematological toxicity following CAR-T cells injection

  Dac EGAC50000000490

• Cardiac fibroblast DAC

  DAC for reviewing requests to access data on cardiac fibroblasts as described by Aguado-Alvaro et al (Nature Communications, 2025)

  Dac EGAC50000000479

• BCR-HGBCL-DH-BCL2 project DAC

  Data Access Committee for high-grade B cell lymphomas MYC-BCL2 datasets

  Dac EGAC50000000500

• Small Intestine Adenocarcinoma Subtyping Data Access Committee

  DAC created for the Molecular classification of small intestinal adenocarcinomas Study in Amsterdam UMC.

  Dac EGAC50000000663

• RNAseq data

  RNAseq data for 10 patients: 10 tumors and 10 cell lines

  Dataset EGAD00001002691

• Brain mets discovery cohort variant calls

  These are the variant calls for the 50 brain tumour samples in the discovery cohort.

  Dataset EGAD00001005982

• Whole genome sequencing data of ccRCCs

  Whole genome sequencing data of ccRCCs were utilized for somatic variations calling.

  Dataset EGAD00001004588

• Exome sequencing VCF files for glioma progression

  Exome sequencing VCF files describing mutations during glioma progression.

  Dataset EGAD00001001887

• Biomarker Data Subset

  This dataset contains data for CBC counts and absolute protein abundance measurements from ELISA experiments.

  Dataset EGAD00001011163

• Phylogenetic reconstruction of breast cancer

  This dataset contains the fastq files used for this study

  Dataset EGAD00001006121

• Genome-wide DNA Methylation Analysis Reveals a Unique Methylation Pattern for Pleural Mesothelioma Compared to Healthy Pleura and Other Lung Diseases

  Study EGAS00001007783

• CPTAC: Microscaled Proteogenomic Methods for Precision Oncology

  Cancer proteogenomics combines genomics, transcriptomics and mass spectrometry-based proteomics to gain insights into cancer biology and treatment outcomes. To promote clinical investigation, we developed a "microscaled" proteogenomics approach for tumor-rich frozen core needle biopsies. Tissue-sparing specimen processing ("Biopsy Trifecta EXTraction", BioTExt) and microscaled proteomics (MiProt) generated deep-scale proteogenomics datasets. As a proofof- concept, biopsies were accrued from ERBB2 positive (ERBB2+) breast cancers before and 48 to 72 hours after the first dose of neoadjuvant trastuzumab-based chemotherapy. Multi-omics comparisons were conducted between samples associated with residual disease versus complete pathological response (pCR). Integrated analyses diagnosed diverse molecular causes of treatmentresistance including: 1) absence of ERBB2 amplification (false-ERBB2&#43); 2) insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification (pseudo-ERBB2&#43); 3) resistance features in true-ERBB2+ cases including androgen receptor signaling, mucin expression and an inactive immune microenvironment; 4) lack of acute phospho-ERBB2 down-regulation in nonpCR cases. We conclude microscaled cancer proteogenomics could improve diagnostic precision.

  Study phs001907

• ABO: a 3D stroma-supported culture platform enabling full human B lymphopoiesis for disease modeling and gene therapy development

  Defective B-cell development underlies a large proportion of inborn errors of immunity, but progress in understanding disease mechanisms and of developing therapies has been limited by inadequate human in vitro models. Here, we establish a 3D aggregate culture platform composed of hematopoietic stem and progenitor cells (HSPCs) and mouse bone marrow stromal cells as an assay for efficient B-cell output (the ABO platform). ABOs supported progression through pro-B, pre-B, immature, and transitional B-cell stages, with a transcriptional profile and B-cell receptor (BCR) repertoire diversity closely resembling human bone marrow B-cell ontogeny. ABO-derived B cells exhibited functional signaling and differentiated into class-switched memory and antibody-secreting B cells following CD40-mediated stimulation. The ABO platform reproduced the arrest in B-cell development observed in RAG1-SCID patient–derived HSPCs, which was corrected by lentiviral RAG1 gene therapy. Thus, ABOs provide a clinically relevant platform for modeling B-cell immunodeficiencies and evaluating therapeutic strategies.

  Study EGAS50000001693

• Rb and p53-Deficient Myxofibrosarcoma and Undifferentiated Pleomorphic Sarcoma Require Skp2 for Survival

  Myxofibrosarcoma (MFS) and undifferentiated pleomorphic sarcoma (UPS) are highly genetically complex soft tissue sarcomas. Up to 50% of patients develop distant metastases, but current systemic therapies have limited efficacy. MFS and UPS have recently been shown to commonly harbor copy number alterations or mutations in the tumor suppressor genes RB1 and TP53. As these alterations have been shown to engender dependence on the oncogenic protein Skp2 for survival of transformed cells in mouse models, we sought to examine its function and potential as a therapeutic target in MFS/UPS. Comparative genomic hybridization (CGH) and next-generation sequencing (NGS) confirmed that a significant fraction of MFS and UPS patient samples (n=94) harbor chromosomal deletions and/or loss-of-function mutations in RB1 and TP53 (88% carry alterations in at least one gene; 60% carry alterations in both). Tissue microarray (TMA) analysis identified a correlation between absent Rb and p53 expression and positive expression of SKP2. Downregulation of SKP2 or treatment with Skp2 Inhibitor C1 revealed that Skp2 drives proliferation of patient-derived MFS/UPS cell lines deficient in both Rb and p53 by degrading p21 and p27. Inhibition of Skp2 using the neddylation-activating enzyme (NAE) inhibitor pevonedistat decreased growth of Rb/p53-negative patient-derived cell lines and mouse xenografts. These results demonstrate that loss of both Rb and p53 renders MFS and UPS dependent on Skp2, which can be therapeutically exploited and could provide the basis for promising novel systemic therapies for MFS and UPS.

  Study phs001982

• NICHD Genomic and Proteomic Network for Preterm Birth Research (GPN)

  We performed genome-wide association studies (GWAS) to study the Spontaneous Preterm birth (SPTB). Maternal and neonatal DNA from 743 SPTB (20 to and less than 34 weeks), and 752 controls (39 to and less than 42 weeks) who fully consented for public research usage were collected from participants in several clinical centers in Alabama, Illinois, New York, North Carolina, Rhode Island, Texas, and Utah. Cases were 1:1-matched with controls according to race/ethnicity (White, Hispanics, African Americans, and Others), maternal age (<20, 20-29, 30-39, 40+), and parity (yes or no). To determine the case-control status for each participant, a Gestational Age (GA) was determined. DNA samples were taken from blood or saliva if blood was not available. Automated DNA extractions were performed on the Qiagen M48 robot, and samples were organized in 96-well plates with barcoding and sample tracking systems. Subsequent manipulations were performed on the Biomek FX liquid handling workstation with 96-channel pipetting. DNA quantitation was performed by dye-based assay on a Molecular Devices SpectraMax Plus plate reader. Samples were genotyped using Affymetrix Genome-Wide Human SNP Array 6.0. This work was conducted at the Microarray Facility at the University of Pennsylvania. Patient data were collected through chart reviews and patient interviews, which included Demographic information (parental age, race, ethnicity, etc.); Medical history (pre-pregnancy weight, height, medications, STD history, medical conditions, etc.); Social history (marital status, years of education, alcohol use and tobacco use); Obstetrical history including outcome of all prior pregnancies and dates of termination; History of preterm labor or premature rupture of membranes symptoms, evaluation or hospitalization for those symptoms in current pregnancy; Medications taken during current pregnancy; History of cervical evaluation (manually or ultrasonographically) or fetal fibronectin measurements; Pregnancy complications; Labor (type, indications, membrane status, and induction method); Delivery type and indications for cesarean section; Neonatal outcome (sex, weight, length, Apgar score, neonatal complications, admission to intensive care unit, etc.); and Maternal family history of SPTB.

  Study phs000714

• SEARCH for Diabetes in Youth Study - Genetic Risk Score

  Genetic risk scores (GRS) quantify polygenic disease risk into a single measure and can aid in disease classification. GRS studies have focused primarily on adult populations of recent European ancestry. We aimed to assess the utility of GRS in classification of diabetes type among racially/ethnically diverse youth in the United States. We used data from SEARCH baseline visits and follow up visits for which key data elements were available. 2260 participants are included. Phenotypic Data to be submitted here include: Self-reported sex, race and ethnicity Diabetes type determined by provider Etiologic diabetes type T1D (antibody positive, or antibody negative/missing and insulin sensitive) T2D (antibody negative and insulin resistant) Diabetes duration (years) Age at diagnosis (years) Measures from baseline, SEARCH 3 (follow-up) and SEARCH 4 (follow-up): Age Height Weight Waist circumference HbA1c Fasting/non-fasting glucose C-peptide Triglycerides HDL LDL Systolic Blood Pressure Diastolic Blood Pressure Measures from SEARCH 3 and 4:Arterial stiffness as characterized by PWVRetinopathy Measures from SEARCH 4 only: LV structure and diastolic function measurements from echocardiogram GAD autoantibody IAD autoantibody ZnT8 autoantibody We performed genotyping using the Illumina Multi-Ethnic Global Array (MEGA) array with 1,697,069 genotyped variants including 748,291 with minor allele frequency <0.01. Genotyping and preliminary quality control checks were performed at the Colorado Center for Personalized Medicine. After additional quality control, 2,238 samples and 900,743 variants remained for analyses. Samples genotyped on the MEGA array were categorized using SEARCH etiologic type and consisted of predominantly type 1 diabetes cases (n=2,051) but also those with other diabetes (n=133 type 2 diabetes, n=52 other diabetes including monogenic diabetes; genetic confirmation with either a genetic clinical test or test performed as an ancillary study to SEARCH). The median reported age at DNA collection was 11.2 years (interquartile range 7.6 – 14.1) with a minimum age of 1.9 years and maximum of 21.9 years. We used additional data genotyped on the Affymetrix 500K imputation scaffold chip with 239,279 genotyped variants. This cohort consisted of predominantly type 2 diabetes cases (n=417) but also those with type 1 (n=104), and other diabetes types (n=16). After additional quality control, 537 samples and 235,967 variants remained. The median reported age at collection was 11.2 years (quartile range 8.1 – 14.2) with a minimum of 2.0 years and a maximum of 21.1 years. About 100 type 2 diabetes cases were also genotyped using the MEGA chip to ensure concordance between the data sets and facilitate strand alignment between the two chips before genotypic imputation. The data sets had n=230,228 genotyped variants in common and concordance between the genotypes was high (mean correlation r2 for SNPs used in GRS=0.95). We used the 1000 Genomes reference panel to impute each data set separately, resulting in a total of 34.5M and 27.8M well-imputed variants (r2>0.8) for the MEGA and Affymetrix data sets respectively. We combined high quality imputed variants for analysis.

  Study phs002703

• UCSF Sebaceous Carcinoma DAC for review of sequence data release from manuscript in Nature Communications, based in the UCSF Departments of Dermatology and Pathology

  Dac EGAC00001000850

• DATA FILES FOR SJHYPO

  Hypodiploid acute lymphoblastic leukemia whole genome sequencing

  Dataset EGAD00001000260

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - side_cases_barretts

  Dataset EGAD00001001379

• TwinsUK_EpiTwin_DNA_Methylome

  MeDIP-seq RPM chromsome BED files for Peripheral Blood from EPITWIN Project (Columns 4-4353 represent samples)

  Dataset EGAD00010000983

• BLEMD (arrays set)

  Circulating tumor cells for comprehensive and multiregional non-invasive genetic characterization of multiple myeloma (arrays set)

  Dataset EGAD00010001857

• dataset_raw_NativesAmericans_LDGH_august2020

  Genome-wide data for 98 Native American individuals from Andes and Amazon

  Dataset EGAD00010001958

• Dataset for study EGAS00001004946 (Endothelium-derived stromal cells contribute to bone marrow niche formation)

  Dataset EGAD00001006914

• BreastCancer_Miroarrays

  Genotyping array data for breast cancer and matched normal mammary gland samples

  Dataset EGAD00010002251

• LOPEZ_2019.vcf.gz

  Genotype data for new samples in Lopez et al 2021

  Dataset EGAD00010002100

• Inherited Corneal Dystrophies - Institute of Ophthalmology, University College London (IoO, UCL)

  DAC created for access to data published by Dr. Alice E Davidson

  Dac EGAC50000000213

• ITER-FIISC Data Access Committee

  DAC for whole-genome variant calling data of individuals from the study of allergic diseases in the Canary Islands.

  Dac EGAC50000000180

• RNAseq for 190 AML patients

  This dataset contains 190 fastq files sequenced with Illumina HiSeq500.

  Dataset EGAD50000000490

• Mechanism of Decitabine response in MDS/AML patients

  Data access agreement for access to scRNASeq data of serial AML/MDS patients undergoing decitabine treatment.

  Dac EGAC50000000550

• Clonotype Analysis Data

  This dataset includes: amplicon sequencing data for a total of 3 BCP-ALL patients - fastq files

  Dataset EGAD50000001518

• Exome sequencing for identifying point mutations driving M haemophilum susceptibility

  To understand non tuberculous Mycobacterial susceptibility

  Study EGAS50000001076

• SiMSen‑Seq

  High resolution amplicon-bases sequencing o screen for PIK3CA hot spot mutations

  Dataset EGAD50000001668

• UROMOL 2020 - RNA-seq data for validation

  Total RNAseq data from 47 patients with NMIBC.

  Study EGAS00001005050

• Reference epigenome OB56_N_PreA_WGBS data generated from KEP study

  A OB56_N_PreA_WGBS paired end data for Preadipocytes(fat)

  Dataset EGAD00001003479

• Microsatellite unstable colorectal cancers

  Mapped data for 10 Colon MSI cancer samples

  Dataset EGAD00001004500

• IMpower133 subtype assignments

  This dataset contains subtype assignments for 271 tumor samples profiled by RNA-seq.

  Dataset EGAD00001006926