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• Whole exome sequencing for HELIC

  The HELIC study has been whole genome sequencing individuals from 2 Greek isolatedpopulations at 1x depth. The genotype calling process crucially involves a VQSR stepfollowed by imputation-based refinement. We have been investigating optimal ways toincrease calling accuracy. To aid us in setting appropriate parameters for VQSR and otherQC steps, we have carried out whole exome sequencing of a small number ofHELIC samples.

  Dataset EGAD00001001638

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB22_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB22_C

  Dataset EGAD00001001706

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB27_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB27_F

  Dataset EGAD00001001719

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB33_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB33_M

  Dataset EGAD00001001732

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB42_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB42_C

  Dataset EGAD00001001745

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB4_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB4_M

  Dataset EGAD00001001756

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW50_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW50_C

  Dataset EGAD00001001835

• BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days B-glucan, on genome GRCh38

  RNA-Seq data for 4 macrophage - T=6days B-glucan sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002522

• Validation data for the SV analysis package: GRIDSS, PURPLE, LINX

  Validation data containing sequencing data of 13 samples. An hybrid capture approach was used to validate findings of both Manta and GRIDSS for the samples in the validation set. The dataset also contains the reference sequences used.

  Dataset EGAD00001005525

• Human tumour ChIP-seq.

  We profiled 16 patient tumour samples by ChIP-seq. H3K27ac and Input are provided for 16 samples and H3K27me3 is provided for 14 samples. Among the 16 samples, 9 are G34WT and 7 are G34R/V. The raw fastq or bam files are provided.

  Dataset EGAD00001006100

• Genomic and transcriptomic data of glioma specimens

  Dataset consists of 207 glioma samples of WHO grades II, III and IV. Dataset consists 182 tumor derived genomic data of ~700 cancer-related and epigenetic-related genes with matched blood samples for 48 specimens. Dataset also consists transcriptomic data for 105 specimens. In total 335 bam files were deposited.

  Dataset EGAD00001006299

• DAC for human liver NPC single cell project

  Dac EGAC00001003207

• Data Access Commitee for skin scRNA-seq

  Dac EGAC00001003129

• DAC for Rare Disease Studies from the Broad Institute

  Dac EGAC00001000566

• DAC for study PTP and Vel Exome Sequencing

  Dac EGAC00001000013

• DAC for Cell Line Data Test of TraIT

  Dac EGAC00001000436

• DAC for Department of Haematology, Aalborg University Hospital

  Dac EGAC00001000543

• DAC for Sardinia Leukocytes polyA RNAseq 624 project

  Dac EGAC00001000561

• DAC for the Prostate Cancer Lymph Node dataset

  Dac EGAC00001000586

• Data Access Committee for Institut Curie Data

  Dac EGAC00001000623

• Data Access Committee for Institut Curie

  Dac EGAC00001000670

• The Shlien Lab, The Hospital for Sick Children

  Dac EGAC00001000942

• Data Access Commitee for gastric cancer ascites

  Dac EGAC00001001026

• DAC for study EGAS00001003438: Clonal Heterogeneity in Glioblastoma

  Dac EGAC00001001118

• DAC for MCO colorectal cancer genomics at UNSW

  Dac EGAC00001001122

• The Shlien Lab, The Hospital for Sick Children

  Dac EGAC00001001125

• DAC for Genomic characterization of metastatic breast cancers

  Dac EGAC00001001129

• DAC for GAMuT Project - Peter MacCallum Cancer Centre

  Dac EGAC00001001154

• DAC for the study EGAS00001003368

  Dac EGAC00001001270

• DAC for GAMuT Project - Peter MacCallum Cancer Centre

  Dac EGAC00001001278

• DAC for Genomics of MDS Freiburg Germany

  Dac EGAC00001001294

• Max-Planck-Institute for Infection Biology, Dept. Molecular Biology

  Dac EGAC00001001295

• DAC for Angiosarcoma Study. National Cancer Centre Singapore.

  Dac EGAC00001001311

• DAC for "Cell type transcriptomics of EAC"

  Dac EGAC00001001397

• DAC for the study EGAS00001004301

  Dac EGAC00001001571

• Department for BioMedical Research (DBMR), University of Bern

  Dac EGAC00001001677

• The Shlien Lab, The Hospital for Sick Children

  Dac EGAC00001002051

• The Shlien Lab, The Hospital for Sick Children

  Dac EGAC00001002053

• DAC for Genomics of MDS Freiburg Germany

  Dac EGAC00001002202

• Data Access Committee for data from EGAS00001005196

  Dac EGAC00001002215

• Data access committee for the ADJUVANT biomarker study

  Dac EGAC00001002333

• DAC for Department of Hematology, University of Tsukuba

  Dac EGAC00001002378

• DAC for Genomics of MDS Freiburg Germany

  Dac EGAC00001002393

• Data Access Commitee for COVID-19 longitudinal data

  Dac EGAC00001002396

• Data Access Committee for the Radovanovic group

  Dac EGAC00001002942

• Data Access Committee for EGA study accession EGAS00001006831

  Dac EGAC00001002988

• Data Access Commitee for sputum bacterial microbiome data

  Dac EGAC00001003004

• Homopolymer switches DAC

  DAC for homopolymer switches project

  Dac EGAC50000000159

• Data Access Committee for data from EGAS00001007708

  Dac EGAC00001003486

• DAC_ICARUS_BREAST01

  Data access committee for ICARUS BREAST 01

  Dac EGAC50000000344

• AG_Kramann

  Data policy for Prof. Dr. Rafael Kramann

  Dac EGAC50000000422

• Institute for Translational Epigenetics

  Dac EGAC50000000057

• Data Access Committee for data from EGAS00001007484

  Dac EGAC00001003459

• Trial of Late Surfactant for Prevention of Bronchopulmonary Dysplasia: A Study in Ventilated Preterm Infants Receiving Inhaled Nitric Oxide (TOLSURF-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To assess whether late surfactant treatment in extremely low gestational age newborn (ELGAN, ≤28 week gestation) infants requiring ventilation at 7-14 days safely improves survival without bronchopulmonary dysplasia.Background: Bronchopulmonary dysplasia (BPD) is the most common form of chronic lung disease in children with an estimated 15,000 new cases annually in the United States. BPD affects infants born prematurely, is a major contributor to the cost of prematurity each year, and is associated with long-term pulmonary disability, neurodevelopmental abnormalities and death.Increases in the survival of ELGAN infants have resulted in another form of BPD, which is characterized by impaired alveolar and microvascular development with excess tone and reactivity of airway smooth muscle. Despite treatments to enhance lung maturation, premature infants often need prolonged intubation and mechanical ventilation and/or oxygen support. When mechanical ventilation is required longer than 7 days, BPD results in 70% of surviving ELGAN infants. Most of these infants experience clinical episodes of increased requirement for ventilatory support that are associated with dysfunctional surfactant, which is primarily due to low surfactant protein B (SP-B). In pilot studies of late surfactant treatment in premature infants, there was short-term improvement in SP-B content. These prior studies provided the rationale for a larger clinical trial for later doses of surfactant treatment to prevent episodes of respiratory decompensation and BPD. Participants: 511 infants were eligible for randomization of the 2693 infants screened. Of the 511 infants eligible for randomization, there were 252 infants allocated to the treatment arm and 259 infants allocated to the placebo arm.Design: The study was designed to assess the effect of late doses of surfactant on survival without BPD at 36 weeks post menstrual age (PMA) in ELGAN infants who required intubation and mechanical ventilation between 7 and 14 days of age and were receiving Inhaled nitric oxide (iNO). Infants were stratified within clinical centers and gestational age groups and randomized to treatment with calfactant, a natural surfactant extracted from bovine lung lavage fluid, or a sham procedure.All infants received iNO according to the protocol used in the Nitric Oxide Chronic Lung Disease (NOCLD) trial. A masked syringe containing either a standard dose of calfactant for the treatment group, or air for the placebo group, was administered to the infant behind a screen by staff not involved in providing the infant's clinical care. Monitor and ventilator alarms were turned off during dosing to avoid unblinding of clinical staff. To accommodate research staff availability and infant instability, the dosing interval was not strictly set but could be repeated every 24 – 72 hours up to 5 doses if the infant still required intubation. Dosing could be discontinued by physician request or parental withdrawal from the study. Due to parental preference, the first infant in a multiple birth was randomized according to the randomization schedule and subsequent infants were assigned to the same treatment group. Follow-up to assess pulmonary and neurologic development continued until 2 years of age, with treatment group blinding maintained. The primary outcome was survival without BPD at 36 weeks PMA. Secondary outcomes included BPD at 40 weeks PMA, pulmonary outcome at 12–24 months of age, and neurodevelopmental outcome at 2 years of age. Conclusions: There were no significant differences observed between the treatment group and the control group for survival without BPD at 36 weeks or 40 weeks.

  Study phs003899

• Varieties of Impulsivity in Opiate and Stimulant Users

  The study was conducted in Bulgaria as a collaboration between Virginia Commonwealth University (Richmond, VA, USA), the Bulgarian Addictions Institute (Sofia, Bulgaria), the Molecular Medicine Center/Medical University (Sofia, Bulgaria), and Indiana University (Bloomington, IN, USA). The overall aim of this study is to investigate the role of impulsivity as an endophenotype for drug addiction. Although impulsivity is considered one of the strongest candidate endophenotypes for addiction, progress in the field is hampered by the heterogeneity of impulsivity, characterized by multiple personality, psychiatric, and neurocognitive dimensions, rarely examined concurrently in the same population; and the heterogeneity of addiction phenotypes, due in part to the high rates of polysubstance dependence among substance users. To address these challenges, we have developed a program of addiction research in Bulgaria, a key transit country for heroin trafficking due to its strategic geographical location on the "Balkan Drug Route" and a major European center for production of synthetic amphetamine-type stimulants. This has allowed us to access rare populations of predominantly mono-substance dependent heroin and amphetamine users, many in protracted abstinence. Our preliminary results reveal a complex relationship between trait and neurocognitive (state) dimensions of impulsivity, often manifested in opposite directions in heroin and amphetamine dependent individuals. Pilot computational modeling analyses of decision-making, a central neurocognitive aspect of impulsivity, have proved particularly informative by indicating that different mechanisms may underlie the impaired decision-making of opiate and stimulant users. A different modeling approach, i.e. phenotypic modeling, holds significant promise to address the pervasive "missing heritability" problem in genetic studies. While genetic heterogeneity is often invoked as an explanation, the manner in which complex phenotypic traits are measured and modeled is equally important contributor to the missing heritability problem but has received much less attention in the literature. Despite the multidimensionality of traits measured by psychometric, diagnostic, and neurocognitive instruments, most GWAS studies typically use aggregate sum scores that do not reflect the underlying phenotypic multidimensionality. Therefore, at least part of the missing heritability problem may originate in misspecification of the phenotypic models. Consequently, sample sizes requirements may increase from ~800 subjects in correctly specified models to 6,000-16,000 subjects in incorrectly specified models. The current study aims to increase our understanding of the complex relationship between multiple putative impulsivity endophenotypes to help redefine endophenotypes as multi-level combination of measures that could inform multivariate multilevel models of complex phenotypes. The specific aims of the study are to: (1) Assess the utility of various personality, psychiatric, and neurocognitive indices of impulsivity (either individually or in combination) as candidate endophenotype(s) for drug addiction in general and for opiate and stimulant addictions in particular; (2) Evaluate the viability of computational model parameters modeling various neurocognitive dimensions of impulsivity as novel endophenotype(s) for addiction; and (3) Test the external validity of the optimal endophenotype(s) by evaluating their associations with HIV and other risk behaviors in opiate and stimulant users in protracted abstinence, a question of critical importance for prevention and intervention efforts in this much less-well understood stage of the addiction cycle.

  Study phs001647

• Associate Vice President for Research Administration & Director

  Dac EGAC00001003114

• DAC for Duke-NUS genomic sequencing projects

  Dac EGAC00001000256

• DAC for Whole Genome Sequencing of ASD quartet families

  Dac EGAC00001000288

• The Shlien Lab, The Hospital for Sick Children

  Dac EGAC00001000289

• DAC for IGMM / Usher Institute, University of Edinburgh

  Dac EGAC00001000365

• DAC for esophageal squamous cell carcinoma genomic data

  Dac EGAC00001000444

• MacFeeters Hamilton Centre for Neuro-Oncology Research (MHC-NOR)

  Dac EGAC00001000510

• DAC for Dave Lab, Duke University

  Dac EGAC00001000538

• DAC for Single Cell Transcriptomics of Colorectal Cancer

  Dac EGAC00001000550

• Data access committee for BAMS exome sequencing data.

  Dac EGAC00001000583

• DAC for DCM-cases (149 human DCM samples)

  Dac EGAC00001000673

• DAC for DCM-controls (113 human non-DCM samples)

  Dac EGAC00001000674

• DAC for AA HCC patient from National Taiwan University

  Dac EGAC00001000708

• Institut Jules Bordet Data Access Committee for EGAS00001002685 study

  Dac EGAC00001000748

• Data Access Committee for Tumor Progression Study at Karolinska Institute

  Dac EGAC00001000778

• DAC for Institute of Human Genetics, Bonn, AGA Project

  Dac EGAC00001000831

• DAC for study Hypothalamic transcriptome in Prader-Willi syndrome

  Dac EGAC00001000869

• DAC for Genomic landscpae of Chordoid Glioma study

  Dac EGAC00001000906

• Data Access Committee for the Medulloblastoma Host Genome Study

  Dac EGAC00001000910

• Data Access Committee for Niigata-NIG collaborative work

  Dac EGAC00001000955

• DAC for study Non-coding RNAs in Breast Cancer

  Dac EGAC00001001090

• DAC for Peritoneal Mesothelioma sequencing study (LAGA-VPC)

  Dac EGAC00001001093

• ASAN Center for Cancer Genome Discovery Data Access Commitee

  Dac EGAC00001001285

• ASAN Center for Cancer Genome Discovery Data Access Commitee

  Dac EGAC00001001391

• DAC for RNA-Seq Transcriptomic CD4+ T data from EGAS00001004152

  Dac EGAC00001001462

• The data usage policy for epigenomic profile of diverse cancer

  Dac EGAC00001001540

• Englander Institute for Precision Medicine - WCM - Yale - Duke DAC

  Dac EGAC00001001777

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

  Dac EGAC00001001880

• DAC for Smart-seq2 kidney glomerular single cell project

  Dac EGAC00001001895

• DAC for de-methylation of the FOXP3-TSDR study

  Dac EGAC00001001902

• Data access Commitee for anti-PD1 in HCC data

  Dac EGAC00001002404

• Data Access Committee for Niigata-NIG collaborative work

  Dac EGAC00001002429

• Data Access Committee for Niigata-NIG collaborative work

  Dac EGAC00001002469

• DAC for tFL with PMBL GE signature Exome samples

  Dac EGAC00001002474

• Center for International Blood and Marrow Transplant Research (CIBMTR)

  Dac EGAC00001002536

• Single cell multi-omics (scNOVA) group for Skin fibroblast

  Dac EGAC00001002833

• AmsterdamUMC Data Access Committee for the EPIC-CD study

  Dac EGAC00001003480

• Genomic and transcriptome analysis for intrahepatic cholangiocarcinoma

  Study EGAS00001006007

• DAC for RNAseq data in B cell malignancies

  Dac EGAC50000000399

• Test GWAS Data for Training and Computational Benchmarking

  Study EGAS00001007914

• Data Access Committee for Triple Negative Breast Cancer dataset

  Dac EGAC00001003584

• The EMC-HEMA-SCN DAC for severe congenital neutropenia data

  Dac EGAC00001003590

• DAC for GWAS of Phenytoin-Induced SJS/TEN in Thailand

  Dac EGAC00001003602

• Brain Arteriovenous Malformation Genetics Study

  The Predictors of Spontaneous Cerebral AVM Hemorrhage study was designed to identify genetic markers that predict adverse outcomes in brain arteriovenous malformation (BAVM) patients, examine race-ethnicity influences on BAVM hemorrhage risk, and use genome-wide association analysis to identify novel genetic predictors of AVM and hemorrhage using the Affymetrix GeneChip. We performed the first genome-wide association study (GWAS) (PMID: 26818729) of sporadic BAVM to investigate association of common single nucleotide polymorphisms (SNPs) with risk of sporadic BAVM in the international, multicenter Genetics of Arteriovenous Malformation (GEN-AVM) consortium. The study included a Caucasian discovery cohort of 515 BAVM cases and 1,191 controls genotyped using Affymetrix genome-wide SNP arrays. The Phase 1 discovery cohort comprised of 338 BAVM cases (154 male) and 504 controls genotyped using the Affymetrix Genome-Wide Human SNP Array 6.0. The molecular data (individual genetic data) for the Phase 1 discovery cohort 338 BAVM cases (self-reported Caucasian) recruited at University of California, San Francisco, or Kaiser Permanente of Northern California (KPNC) are included in the dbGaP Study Report: Brain Arteriovenous Malformation Genetics Study, with the additional BAVM case phenotypic and sample attribute characteristics: sex, race, age at BAVM diagnosis, hemorrhagic presentation, BAVM size. Written informed consent was obtained from all participants and the study was approved by the respective Institutional Review Boards. The molecular dataset for this study in dbGaP is based on the genotypes obtained for the initial set of 906,600 SNPs for cases and controls called together using Birdseed v2 algorithm in Affymetrix Genotyping Console Software. The final QC'd dataset includes 717,335 markers as SNPs with MAF<0.01 or deviating from Hardy-Weinberg equilibrium (P<0.00001) in controls were excluded. After QC, the average genotyping call rate was 99%. The discovery phase GWAS identified 57 top BAVM-associated SNPs which were tested in a replication cohort including 608 BAVM cases and 744 controls. The molecular dataset for these 338 BAVM cases was also included in a report investigating common and rare genome-wide copy number variation for association with BAVM (PMID: 24098321), which included a total sample size of 371 sporadic Caucasian BAVM cases and 563 Caucasian controls. This study identified a CNV region on 1p36.13 (NBPF1 locus) that was significantly enriched with duplications in BAVM cases compared to controls, although this association did not replicate in an independent cohort of 184 sporadic BAVM cases and 182 controls. This resource will help researchers to better understand the genetic risk factors for BAVM and/or hemorrhage. These data may be applied to examine the genetic contributions to arteriovenous malformation, stroke, and related vascular disorders and may help generate hypotheses regarding the genetics of cerebrovascular disease.

  Study phs002069

• Kids First: Genomic Etiologies of CHARGE Syndrome, Related Conditions and Structural Anomalies

  Developmental disorders with structural birth defects account for the majority of morbidity and mortality in children's hospitals, and the genetic bases of many clinical phenotypes remain unknown. Genetic testing for individuals with structural malformations has uncovered the basis of many such birth defects; however, many more cases remain unsolved, posing challenges for diagnosis, treatment, and prevention. Multiple anomaly conditions are particularly challenging to diagnose, since they often present with unique combinations of clinical features that vary widely between affected individuals, even in the same family. CHARGE Syndrome (Coloboma of the eye, Heart Defects, Atresia of the choanae, Retardation of growth and development, Genital abnormalities including pubertal delay and infertility, Ear abnormalities with deafness and vestibular disorders) is a multiple anomaly condition that affects a wide variety of organ systems. CHARGE Syndrome is caused in most cases by monoallelic pathogenic variants in CHD7, the gene encoding ATP-dependent helicase chromodomain DNA binding protein 7. Both de novo and inherited variants in CHD7 have been reported in CHARGE, and a growing number of families present with individuals who test positive for a pathogenic CHD7 variant yet exhibit only mild features. Similarly, individuals with CHARGE Syndrome often exhibit broad variability and reduced penetrance of clinical features, consistent with pleiotropic roles for CHD7 during development and/or additional genetic contributors or modifying alleles. Recent work has also implicated RERE, KMT2D, EP300, and PUF60 in having a role in CHARGE Syndrome.We hypothesize that (1) some cases of CHARGE are due to other genetic etiologies including oligogenicity, and (2) genetic modifiers contribute to the broad clinical variability and reduced penetrance of CHARGE features. To address these hypotheses, we have generated a cohort of 223 deeply clinically phenotyped individuals with CHARGE Syndrome and related disorders and structural anomalies who tested negative by chromosomal microarray, single gene sequencing, next generation panel sequencing, or exome sequencing. These individuals exhibit clinical CHARGE-like features including structural birth defects affecting craniofacial, ocular, neurosensory, brain, heart, mediastinal, renal, genitourinary, and skeletal organs. Our cohort includes these 223 individuals as well as affected and unaffected family members who consented to clinical and research genetic testing and donated blood samples for DNA and RNA isolation and sequencing. Building on this valuable cohort, we propose to use exome and genome sequencing to identify novel genetic etiologies of CHARGE and related developmental disorders for which alternative genetic tests have been inconclusive. Identification of novel pathogenic genetic variants and contributing modifier alleles within the coding and non-coding portion of the genome of these individuals will improve genetic diagnosis and provide important insights toward understanding the developmental mechanisms of structural birth defects.

  Study phs002592