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• Res1_HT29_exp1_MC_02_03_22

  1 sample is pure plasmid DNA and 10 samples are cell pellets for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kozuke primers.

  Study EGAS00001006092

• Prognostic markers of DNA methylation and NGS sequencing in progressive glioblastoma from the EORTC-26101 trial

  These dataset contains NGS data from 380 samples from the EORTC-26101 clinical trial for patients with progressive glioblastoma.

  Study EGAS00001007421

• Genetic Analysis of Metopic Nonsyndromic Craniosynostosis

  Craniosynostosis (CS), the premature fusion of one or more cranial sutures, is a common defect occurring in 1 in 2,500 live births. About 85% of infants with CS present as nonsyndromic (i.e., without unrelated, major birth defects or developmental delay). Nonsyndromic CS (NCS) is a heterogeneous condition with presumed multifactorial etiology; however, its causes remain largely unknown. As such, primary prevention strategies for this defect are limited. Through our International Craniosynostosis Consortium (ICC), we have advanced the understanding of the genetic etiology for the most common NCS subtype, sagittal NCS (sNCS). As a result of our previous funding (R01 DE016866), we successfully conducted the first genome-wide association study (GWAS) for sNCS and identified robust associations to loci near BMP2 (rs1884302; P=1.1x10-39; OR=4.38) and intronic to BBS9 (rs10262453; P=5.6x10-20; OR=0.24), both biologically plausible genes with a role in skeletal development. Building on our work, we investigated case-parent trios with metopic NCS (mNCS) by GWAS. Both sNCS and mNCS affect the midline sutures of the skull, are more likely to occur among non-Hispanic whites, and show a male excess. For each subtype, evidence for multifactorial determinants is supported by increased recurrence risk in families, increased concordance in monozygotic vs. dizygotic twins, and positive associations with variants in selected genes (e.g., FGFR). Given these similarities, we hypothesize that sNCS and mNCS may share common causative variants. This data represents an extension of our current study aimed to perform a comprehensive molecular characterization of sNCS and mNCS.

  Study phs001508

• Family Investigation of Nephropathy and Diabetes (FIND) Study

  The Family Investigation of Nephropathy and Diabetes (FIND) is a multicenter study designed to identify genetic determinants of diabetic kidney disease. Study subjects were recruited from eleven centers and in many ethnic groups throughout the United States. A genome-wide association study (GWAS) was conducted with the Affymetrix 6.0 chip. Subjects (index cases) with diabetes and kidney disease were initially recruited, and their parents and siblings were invited to participate. Genetic material from these participants was used to genotype markers throughout the genome. For association-based testing, a case-control design was implemented with study subjects selected primarily from the index cases of the families. Unrelated controls were selected from families where a case was not already selected. Several study sites also contributed non-FIND subjects, both cases and controls (consent forms for the release of FIND and non-FIND subjects/samples are included in this dbGaP release). Cases were selected if they met study criteria for diabetic nephropathy or met inclusion criteria based on elevated serum creatinine levels and abnormal urine protein excretion. Similarly, controls were long-term diabetics with otherwise normal kidney function. See inclusion/exclusion criteria section for a detailed description for the FIND study as a whole and this GWAS. The goal of the FIND study is to identify genes that influence susceptibility to diabetic kidney disease, leading to a better understanding of how kidney disease develops. In the long run, this may lead to improved treatment and prevention of diabetic kidney disease.

  Study phs000333

• Early Methamphetamine Abstinence: fMRI and Brain Function

  This study included two groups of subjects, methamphetamine-dependent and healthy control participants, with the purpose of characterizing brain structure and cognition during the first month of abstinence from methamphetamine. Participants were able to participate in one or both phases of the study. Methamphetamine abusers were held as inpatients and abstained from methamphetamine use during the entirety of the study. Phase I covered the 1st week of abstinence and Phase II covered the next 3-4 weeks of abstinence. Control subjects participated as outpatients at timeframes which corresponded to the assessments taken of methamphetamine users. The following outlines the procedures in more detail. After initial telephone screening, in-person screening and recruitment procedures took place at the UCLA Neuropsychiatric Institute. Each methamphetamine abuser subject entered the study after completing an interview and questionnaires on drug use history, and providing a positive urine test for methamphetamine. The evaluation included a psychiatric diagnostic interview according to the Structured Clinical Inventory for DSM-IV (SCID-IV), a medical history and physical examination, blood tests [including a complete chemistry panel, hepatic panel, and tests for hepatitis-C and HIV]. Urine samples were also taken for drug screening of illicit drugs, and to test for pregnancy (female subjects). The methamphetamine abusers were then admitted to the General Clinical Research Center (CRC) and participated on a residential basis, where they were administered daily questionnaires about drug craving, withdrawal and mood. The current study makes available phenotype and genotype data, and interested investigators may contact the principal investigator regarding potential sharing of fMRI data.

  Study phs001198

• Genetic Modifiers of Syndromic Orofacial Clefts

  Reduced penetrance and variable expressivity are common, but poorly understood, features of most monogenic diseases. Genetic modifiers are possible factors to contribute to this phenotypic variability and blur the traditional distinction between monogenic and complex disease. This study focuses on the most common orofacial cleft syndrome (Van der Woude syndrome, VWS) and nonsyndromic orofacial clefts (OFCs), which intersect both in phenotype and in genetic etiology, as a model to understand reduced penetrance and variable expressivity. VWS occurs in 1 in 35,000 individuals and accounts for 2% of all OFCs. The features of VWS include an OFC and/or lower lip pits, but 15% of VWS patients present with an isolated OFC, making them indistinguishable from nonsyndromic OFC patients. Mutations in the genes IRF6 or GRHL3 cause VWS, but approximately 20% of VWS patients currently lack a molecular diagnosis. Furthermore, there are few genotype-phenotype correlations for known mutations and patient phenotypes. By contrast, GWAS of nonsyndromic OFCs have identified a number of risk factors, some of which we have shown increase risk for specific types of OFCs or act as modifiers of OFC subtypes. Whole genome sequencing will be used to identify the remaining genetic mutations for VWS, determine the relationship between those genes/regions with nonsyndromic OFCs, and identify rare and common modifiers of VWS and OFC phenotypes. These analyses will provide further insight into the genetic architecture of VWS and OFCs and will serve as a model for exploring links between other Mendelian disorders that share phenotypes with complex traits.

  Study phs002221

• Melbourne Collaborative Cohort Study DNA Methylation Studies

  This dataset contains raw Illumina 450K blood DNA methylation data from a subset of participants in the Melbourne Cohort Study (MCCS), a prospective study of 41,513 healthy adult volunteers (24,469 women) aged between 27 and 76 years when recruited between 1990 and 1994. Nested case-control studies: DNA methylation data were generated as part of cancer case-control studies nested in the MCCS. Participants were cancer-free at blood draw; blood samples were taken at baseline (1990-1994) for 97% of participants; and for 3% of participants at the second wave of follow-up (2003-2007). Eight separate studies were conducted of breast, prostate, colorectal, lung, kidney, urothelial and gastric cancer and B-cell lymphoma, for a total of > 3,500 cancer cases. Controls were individually matched to cases on age, sex, and country of birth using incidence density sampling. Additional matching on smoking history was made for the study of lung cancer. Longitudinal study: For a subset of 1,100 participants with baseline DNA methylation measures (from dried blood spots) who were selected as controls in the nested case-control studies, repeated methylation measures were made using wave 2 follow-up samples (also from dried blood spots) to study longitudinal DNA methylation changes. Project aims: 1. Nested case-control studies: To assess prospective associations between peripheral blood DNA methylation and risk of eight cancer types (breast, prostate, colorectal, lung, kidney, urothelial cell and gastric cancer, and mature B-cell neoplasms). 2. Longitudinal study: To assess associations between lifestyle changes and changes in peripheral blood DNA methylation.

  Study phs003213

• Study on the Genetics of Alcoholism (COGA): Smoke Screen and Exome Sequencing

  This is a family study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This project has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and after securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through an alcoholic proband. Assessment involved a detailed personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results are included on a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3.

  Study phs001208

• CINECA_synthetic_cohort_EUROPE_UK1 referencing fake samples

  Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

  Dataset EGAD00001006673

• Differential Presence of Exons in Cell-Free DNA Reveals Different Patterns in Colorectal Cancer Between Metastatic and Non-Metastatic Patients

  Tumor genotyping during disease follow-up is gaining an increasing interest for monitoring and clinical management in colorectal cancer (CRC). Growing evidences suggest that single biopsies are inefficient for molecular profiling, due to clonal evolution and intratumoral heterogeneity of primary tumors and/or metastasis. Circulating free DNA (cfDNA) has emerged as an alternative source of genetic material that seems to be representative of the continuously changing tumor molecular features. Thus, the so-called 'liquid biopsy' also offers the additional advantages of accessibility and non-invasiveness for the patient. Novel strategies based on next-generation sequencing (NGS) of cfDNA are being currently developed, with most studies focusing on targeted deep sequencing panels of potential clinically actionable genes. Here we describe an alternative approach, consisting of exome-sequencing in cfDNA at a relatively shallower depth to provide a more general overview of the circulating genome. In this study, two groups of colorectal cancer patients, with either disseminated (M) or localized disease (N), were compared using whole-exome sequencing and a RNA-seq bioinformatics analysis pipeline. Thus, a set of 379 exons present at different levels in cfDNA from both groups were identified, giving rise to a completely new concept in this field, termed as 'Differential Presence of Exons'. Differentially present exons (DPEs) were subsequently used for M and N patients clustering and classification, allowing for the design of a predictive algorithm with encouraging preliminary results in a small subset of patients that could not be initially classified attending to the selection criteria (U group, unassignable).

  Study EGAS00001002687