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• Integrated Clinical and Transcriptomic Profiling to Characterize Disease Phenotype

  Personalized medicine requires that we first address the challenge of genetic heterogeneity, prominent in rare cancers to common disease. While current clinical DNA sequence data successfully identify novel genetic variants, the genomic data alone are insufficient biomarkers of clinical phenotype. There is an unmet need for systematic integration of specific functional genomic data with patient genetic data, in order to bridge the knowledge gap between genetic variation and clinical phenotype. This specific study is focused on functional genomic data from platelets as disease-specific cells that are also ideal for proof-of-principle transcriptomic investigation (being anucleate), and highly-relevant to multiple disease processes.

  Study phs002121

• Native American Ancient DNA sequencing

  The morphology of the first humans in the Americas (Paleoamericans) differs from that of Native Americans, and has raised the question of whether or not there are also differences in origin or genetics. A few populations who survived until relatively recently have been suggested to retain Paleoamerican morphology. One of these populations is from La Jolla. Here, we have generated genome sequence data from four La Jolla individuals in order to investigate these questions This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001002144

• Baylor College of Medicine Advancing Sequencing in Childhood Cancer Care (BASIC3) Clinical Exome Sequencing Study - Clinical Sequencing Exploratory Research Consortium

  The BASIC3 (Baylor College of Medicine Advancing Sequencing in Childhood Cancer Care) study is a National Genome Human Research Institute (NHGRI) and National Cancer Institute-funded Clinical Sequencing Exploratory Research (CSER) consortium project that focuses on prospective implementation of clinical whole exome sequencing in the pediatric oncology clinic. The primary study objective are to integrate information from CLIA-certified germline and tumor exome sequencing into the care of newly diagnosed solid tumor patients at Texas Children's Cancer Center, and to perform parallel evaluation of the impact of tumor and germline exomes on families and physicians. Blood and frozen tumor (if available) samples are collected from children undergoing surgery or biopsy of newly diagnosed solid tumors and subjected to exome sequencing in a CLIA-certified laboratory. Germline and tumor (if applicable) exome sequencing reports are generated and submitted into the electronic health record and returned to each patient/family by their primary oncologist. If specific (optional) consent is obtained, research sequencing studies (including transcriptome sequencing) are performed in addition to the clinical exome sequencing.

  Study phs001026

• Whole Genome Sequencing of Skull-Based Chordoma

  Chordoma is a rare bone tumor, which is believed to originate from notochordal remnants. Based on the United States Surveillance Epidemiology and End Results (SEER) data, the incidence of chordoma varies by gender and race; however, little is known about the etiologic factors that predispose to it. Genomic profiling studies of chordoma are limited, particularly in the Chinese population. We therefore conducted a detailed molecular characterization of paired chordoma tumor/normal tissues using fresh frozen tissues and blood collected from skull-based Chinese chordoma patients. These analyses included whole exome sequencing and RNA sequencing analyses.

  Study phs002301

• Genetic mechanisms of resistance to chemotherapy in breast cancer

  Resistance towards chemotherapy is one of the main causes of treatment failure and deathamong breast cancer patients.The main objective of this project is toidentify genetic mechanisms causing some breast cancer patients not torespond to a particluar type of chemotherapy (epirubicin) while otherpatients respond very well to the same treatment. In the project wewill perform genome / exome sequencing of a selection of breast cancerpatients (n=30). These patients are drawn from a cohort where allpatients have recieved treatment with epirubicin monotherapy before surgical removal of alocally advanced breast tumour, and where all patients have beensubjected to objective evaluation of the response to thetherapy. Subsequent to sequencing, we will analyse the data andcompare with the clinical data for each patient (object response totherapy). The main aim being to identify mutations that are associatedwith resistance to epirubicin. Identification of mutations with strongpredictive value, may have a direct impact on cancer treatment sinceit opens the possibility for genetic testing of a tumour, and desicionon which drug is likely to work best, prior to treatment start.

  Dataset EGAD00001000264

• Nature and Contribution of Noncoding, Regulatory Mutations in Neurodevelopmental Disorders

  This dbGaP study contains variant call files generated from whole-genome sequencing data of families with autism. The variant callers include FreeBayes, GATK, Platypus, and Strelka2. A family-level VCF file, from each caller, is provided for each family in the study. The families included in this study are from the Simons Simplex Collection (SSC), the Study of Autism Genetics Exploration (SAGE), and The Autism Simplex Collection (TASC); sequencing was performed at the New York Genome Center, as part of the Centers for Common Disease Genomics (CCDG) Consortium. The analysis to generate the variant callsets was supported by a K99 Pathway to Independence grant to Dr. Tychele Turner (1K99MH117165-01). *Access to phenotype data at the individual level for Simons Simplex Collection (SSC) subjects can be requested from SFARI Base: https://www.sfari.org/resource/sfari-base/.

  Study phs001874

• NCI-Maryland Prostate Cancer Case-Control Study

  The study seeks to examine the genetic and ancestral basis of prostate cancer-associated inflammation using a genome-wide association approach. The study population are the participants of the NCI Maryland Prostate Cancer Case-Control study. This study recruited both African American and European American men, and investigated the causes for the excessive burden of prostate cancer among African American men in more general terms. We measured 82 blood-based immune-oncology markers, and genotyped the participants using the HumanOmni5-Quad BeadChip, which provides a significant genome coverage for genetically-admixed and diverse populations, to evaluate the genetic basis and evidence for causality of any immune-inflammation marker that is associated with prostate cancer risk. We want to assess how germline genetics influence the abundance levels of these 82 markers in African American and European American men, which may contribute to differences between them.

  Study phs002939

• Molecular Signature of Saudi Thyroid Cancer Using whole exome sequencing

  In Saudi Arabia, thyroid cancer ranked second only to breast cancer among females, eleventh among males and this increased incidence is prevalent in other Gulf Council Countries also. Differentiated thyroid cancer, which includes papillary thyroid cancer (PTC) and follicular subtypes, accounts for 90% of all thyroid malignancies. Currently, there are no clinical or molecular diagnostic tools to predict recurrence and aggressiveness of a subset of PTC. With the goal of better understanding the pathobiology of thyroid carcinogenesis we will use Whole Exome Sequencing to decipher the molecular and genetic signature of Saudi PTC based on International Cancer Genome Consortium (ICGC) Guidelines. The study will provide a better understanding of PTC and should have important clinical implications in the development of new and better strategies for targeted therapeutic intervention for the treatment of Saudi Arabian PTC

  Study EGAS00001000680

• Efficacy of two different FGFR-inhibitors in a patient with extrahepatic cholangiocarcinoma harboring an FGFR2 mutation

  Cholangiocarcinomas (CCAs) is a type of cancer with few effective systemic therapies. Elucidation of the molecular landscape of the disease from genomic studies based on next generation sequencing (NGS) has contributed to the introduction of new targeted therapies. One of these treatments consists of a class of small molecules that target members of the FGFR family of receptor tyrosine kinases. These drugs are effective and have been approved for cholangiocarcinomas with fusions or rearrangements of FGFR genes. In contrast, the role of these inhibitors in cholangiocarcinomas with mutations in FGFR genes is less well defined. We report here a patient with a cholangiocarcinoma bearing a FGFR2 p.Ser252Trp mutation. The patient was treated with two different FGFR inhibitors, as the first caused ocular toxicity. She obtained clinical benefit from both. This case illustrates the efficacy of FGFR inhibitors on cholangiocarcinoma with specific point mutations. This is the first case to report the clinical benefit of these drugs in FGFR2 p.Ser252Trp mutation. Clinical benefit can be sustained, as seen in our patient. Our case also shows that FGFR inhibitors-induced adverse effects, such as ocular toxicities, may not recur after re-challenge with an alternative drug of the same class.

  Study EGAS50000000015

• Genomic Regions Associated with Susceptibility to Barrett's Esophagus and Esophageal Adenocarcinoma in African Americans: The Cross BETRNet Admixture Study

  Differences in rates of diseases between different populations with similar environments are presumed to be secondary to variability in population frequencies of disease causing alleles. Recently admixed populations such as African Americans (AAs) provide a natural opportunity to identify disease-causing variants by examining the ancestry of long chromosomal haplotypes. Admixture mapping approach can be successful in locating genes for diseases such as EAC whose rates varies markedly between the ancestral populations. This is a case only study with 54 African American cases and also on a subset of 28 cases with high genotyping quality. We seek to identify chromosome regions that have excess European ancestry and contrasting it to excess African ancestry.

  Study phs001454

• Everything you need to know about Federated EGA Affiliates: Q&A

  Addressing common questions about Federated EGA (FEGA) Affiliates and providing answers. FEGA Affiliates have recently been defined as the third tier within the newly approved “Federated EGA Structure and Organisation” document, alongside Central EGA (CEGA) and the FEGA Nodes. In this blog post, we aim to answer the questions that may arise on this topic. For more general information about FEGA Affiliates, you can refer to this blog post. Let's now start with the questions and answers! What is the difference between a FEGA Affiliate and a FEGA Node? FEGA Nodes A FEGA Node is a national-level service that accepts submissions and provides archiving and access services within a single country's jurisdiction. Nodes provide end-to-end services for submitters in that jurisdiction, including submission support, processing, permissions management, and distribution. FEGA Affiliates A FEGA Affiliate is not a national submission service. Instead, it archives data from its own legal entity and/or selected partner institutions (for example, consortium partners). Affiliates are designed for organisations and consortia that need to keep data stewardship and access decisions within their own governance model, while still enabling discovery through the broader FEGA ecosystem. What do Affiliates commit to? Here is a practical checklist of the core expectations for a FEGA Affiliate. FEGA Affiliate checklist Discovery and metadata Submit non-personal metadata to CEGA to obtain EGA accessions and enable discovery (with metadata validation handled by the CEGA Helpdesk). Operations and resilience Maintain a data storage system and a defined backup/recovery approach. Ensure operational capacity (personnel and infrastructure) to deliver Affiliate services. Maintain systems and practices that support local data security and align with EGA best-practices. Access and user support Provide data distribution or access (e.g in a trusted research environment) to authorised users to datasets hosted at the Affiliate. Provide permissions management for datasets archived by the Affiliate (the CEGA DAC (Data Access Committee) Portal is always at your disposal to use). Provide a minimal helpdesk with sufficient capacity to support relevant DACs and approved users. Membership term Commit to a minimum membership term of four years. Governance and participation (lightweight by design) Affiliates integrate into the FEGA network operationally, but without the committee obligations associated with Nodes. When is becoming an Affiliate the right fit? Consider the Affiliate tier if: You host (or plan to host) controlled-access datasets that must be managed under your organisation’s or consortium’s governance, you want studies to be discoverable through EGA, but need access control and/or distribution to remain local, and you are not aiming to operate a national submission service tier.. What if a FEGA Node already exists in my jurisdiction? We encourage any potential Affiliate to reach out to their national FEGA Node to explore collaboration at the national level. Why? Federated models within a country already exist in FEGA, where a national Node operates like a Central EGA for their country. FEGA Nodes can also represent the interests of any Affiliates within their jurisdiction at the FEGA Committees. FEGA Nodes have experience and can support you on your FEGA journey. Ready to join as a FEGA Affiliate? We’re excited to open this formally defined pathway for organisations and consortia to participate in the federation. If you think the FEGA Affiliate tier fits your needs, start by assessing: Your scope (organisation/consortium-held data rather than public external submissions), Your ability to provide the core services (permissions, distribution/access, helpdesk, monitoring), and Your readiness to submit non-personal metadata to CEGA for accessioning and discovery. To express interest, please contact us here, and we'll help you understand the onboarding steps and how Affiliates integrate into the FEGA network.

  Blog fega-affiliates-q&a

• NHLBI TOPMed: Genetics of Cardiometabolic Health in the Amish

  The Amish Complex Disease Research Program includes a set of large community-based studies focused largely on cardiometabolic health carried out in the Old Order Amish (OOA) community of Lancaster, Pennsylvania (http://medschool.umaryland.edu/endocrinology/amish/research-program.asp). The OOA population of Lancaster County, PA immigrated to the Colonies from Western Europe in the early 1700's. There are now over 30,000 OOA individuals in the Lancaster area, nearly all of whom can trace their ancestry back 12-14 generations to approximately 700 founders. Investigators at the University of Maryland School of Medicine have been studying the genetic determinants of cardiometabolic health in this population since 1993. To date, over 7,000 Amish adults have participated in one or more of our studies. Due to their ancestral history, the OOA may be enriched for rare variants that arose in the population from a single founder (or small number of founders) and propagated through genetic drift. Many of these variants have large effect sizes and identifying them can lead to new biological insights about health and disease. The parent study for this WGS project provides one (of multiple) examples. In our parent study, we identified through a genome-wide association analysis a haplotype that was highly enriched in the OOA that is associated with very high LDL-cholesterol levels. At the present time, the identity of the causative SNP - and even the implicated gene - is not known because the associated haplotype contains numerous genes, none of which are obvious lipid candidate genes. A major goal of the WGS that will be obtained through the NHLBI TOPMed Consortium will be to identify functional variants that underlie some of the large effect associations observed in this unique population.

  Study phs000956

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Epilepsy: Epi25 Consortium

  Epilepsy genetics research is at an exciting stage where it is now feasible, with the power of a large cohort, to understand the more complex genetic components of epilepsy. The driving principle behind the Epi25 Consortium is collaboration and synergy - it is only possible to achieve this type of research by working together. The Epi25 Consortium was formed by the unification of various consortia, including Epi4K, EPIGEN, EuroEPINOMICS, the Epilepsy Phenome/Genome Project, EpiPGX, SANAD, and EpiCURE, and individual epilepsy investigators. The consortium's sample collection is the best resource in the world for this disease, both in terms of numbers of patients and quality of phenotypic information. As part of the NHGRI Centers for Common Disease Genomics (2016-2020), we aggregated a global sample collection from the various repositories for whole genome genotyping and whole exome sequencing (WES) at the Broad Institute (Cambridge, MA), initiating the largest and most ethnically diverse genetic study of epilepsy to date. The primary epilepsy phenotypes for Epi25 are based on strict standards agreed upon by the epilepsy community. The epilepsy cases contributed by Epi25 sites can be broadly defined as genetic generalized epilepsy (GGE), non-acquired focal epilepsy (NAFE), epileptic encephalopathies (EE), and lesional focal epilepsies. More information about eligibility criteria and phenotyping forms for Epi25, as well as the contributing centers, can be found here: epi-25.org The genomic data will be analyzed iteratively to identify genes and variants that explain these types of epilepsy. Summary clinical data compiled in the Epi25 clinical database will allow retrospective phenotypic analyses of groups of subjects with common genomic variant(s).

  Study phs001489

• DIME study: Safety, dose-response and efficacy of treatment with Anaerobutyricum soehgenii on glucose metabolism in human subjects with metabolic syndrome

  The intestinal microbiota has been implicated in insulin resistance, although evidence regarding causality in humans is scarce. We herefore performed a phase I/II dose-finding and safety study on the effect of oral intake of the anaerobic butyrogenic Anaerobutyricum soehgenii on glucose metabolism in subjects with metabolic syndrome. We found that treatment with A. soehgenii was safe and observed an overall significant and dose-dependent increase in insulin sensitivity after 4 weeks in all treated subjects. This was accompanied by an altered microbiota composition and a change in bile acid metabolism. Finally, we show that metabolic response upon administration of A. soehgenii (defined as improved insulin sensitivity 4 weeks after A. soehgenii intake) is dependent on microbiota composition at baseline. These data in humans are promising and additional studies are needed to study long-term effects as well as modes of delivery.

  Study EGAS00001003498

• Genetic Basis of Early Onset Bicuspid Aortic Valve Disease

  The study protocol was approved by the Committee for the Protection of Human Subjects at the University of Texas Health Science Center at Houston (HSC-MS-11-0185). Study recruitment began on July 1, 2017, and concluded on March 30, 2022. After written informed consent, we enrolled probands with early onset BAV disease (EBAV), which we defined as individuals with BAV who were under the age of 30 at the time of first clinical event. Clinical events were defined as aortic replacement, aortic valve surgery, aortic dissection, moderate or severe aortic stenosis or aortic regurgitation, large aneurysm (Z > 4.5), or intervention for BAV-related conditions. Those with hypoplastic left heart, known genetic mutations, genetic syndromes, or complex congenital heart disease were excluded. Samples were collected and genotyped as previously reported. For comparison, we analyzed a cohort of older individuals of European ancestry with sporadic BAV disease selected from the International BAV Consortium (BAVGWAS). Phenotypes were derived from record review with confirmation of image data whenever possible [25-26]. The computational pipeline for CNV analysis of Illumina single nucleotide polymorphism (SNP) array data included three independent CNV detection algorithms.GenomeStudio was used to exclude samples with indeterminate sex or more than 5% missing genotypes, and single nucleotide polymorphisms (SNPs) with GenTrain = 0. Principal component analysis was used to remove outliers that did not cluster with European ancestry. Prior to CNV analysis, each dataset was trimmed by selecting a common set of 650,000 SNPs that were genotyped on each of the microarrays used in this study.Three independent algorithms (PennCNV, cnvPartition, and QuantiSNP) were used to generate CNV calls and sample-level quality statistics from SNP intensity data. PennCNV and QuantiSNP were run on Unix clusters and cnvPartition data were exported from GenomeStudio. The analysis was run using default configurations. PennCNV was used to generate QC data and remove CNV calls that intersect with polymorphic genomic regions. Samples that met any of the following criteria were excluded, standard deviation of the LogR ratio (obtained from PennCNV) > 0.35 or number of CNVs > 2 standard deviations above the mean for each data set. CNV calls less than 20 Kilobases in length and/or spanned by fewer than 6 probes were excluded. The overlap function for rare CNVs in PLINK was used to construct CNV regions (CNVRs) after adjacent regions were merged using PennCNV. LogR ratio (LRR) and B allele frequency (BAF) data at CNVRs and calls of interest were visualized in GenomeStudio for validation. For segregation analysis, GenomeStudio was used to determine the presence of CNVs in relatives.A total of 22,014 unselected control Illumina Genotypes obtained from the Database of Genotypes and Phenotypes were analyzed using identical methods (S1 Table). The Wisconsin Longitudinal Study (WLS) includes data on a cohort of 10,300 individuals who graduated from Wisconsin high schools in 1957. The Health and Retirement Study (HRS) includes data on 37,000 individuals aged 50 above from 23,000 households across the United States. Principal component analysis was used to select European ancestry genotypes from these datasets for analysis. Datasets were paired for case-control analysis based on the concordance of log-transformed sample-level quality control statistics (number of CNV calls and standard deviation of logR ratios). Chi-squared or Fisher exact tests were used to compare CNV frequencies in cases and controls.Rare CNV functions in PLINK (v1.7) were used to perform permutation-based burden tests or gene set-based enrichment tests. Case control burden tests were restricted to CNVs that were longer than 110 Kb and less than 0.1% in frequency. CNV overlap functions in PLINK were used to identify rare CNVs that intersect between datasets or involve specific BAV or CHD genes . The list of candidate genes included 190 CHD genes that have strong cumulative evidence to cause BAV or related congenital malformations from human or animal model data. Genome Reference Consortium Human Build 37 was used for CNV annotation [34].

  Study phs003705

• The Precision Medicine in Liver Cancer across an Asia-pacific NETwork (PLANET)

  Hepatocellular carcinoma (HCC) is the 2nd most important cause of cancer deaths in the world. The outcomes of treatment in HCC are poor compared to other common cancers because there are no good systemic therapy drugs. We designed a prospective study that will involve 5 different sites within the established Asia-Pacific Hepatocellular Carcinoma Trials Group to study both the genetics as well as immune profiles of HCC in different ethnicities. In this study, patients will be followed-up and at recurrence the tissues to understand the evolution of disease progression. Here, we presented both the genomic (DNA) and phenotypic (RNA) evolution for the first batch of 56 patients. The detailed findings will be listed in the corresponding publication soon.

  Study EGAS00001003813

• UCSF Pediatric Bithalamic Glioma Genome Project

  Brain tumors are the most common solid tumors of childhood, and the genetic drivers and optimal therapeutic strategies for many of the different subtypes remain unknown. We performed targeted next-generation sequencing of approximately 500 cancer-associated genes on a cohort of 13 pediatric bithalamic diffuse gliomas, a lethal brain tumor of childhood for which the genetic basis is largely unknown. We identified that bithalamic diffuse gliomas harbor frequent mutations in the EGFR oncogene in the absence of accompanying gene amplification and only rare histone H3 mutation. These EGFR mutations were either small in-frame insertions within exon 20 (intracellular tyrosine kinase domain) or missense mutations within exon 7 (extracellular ligand-binding domain). Accompanying alterations included frequent TP53 mutation, CDK6 amplification or CDKN2C mutation, and BCOR and BCORL1 mutation or deletion.

  Study EGAS00001004033

• MP2PRT-MNG: Identifying Novel Molecular Markers of Response to Radiotherapy in Meningiomas Using Samples from the RTOG-0539 (NCT00895622)

  The Molecular Profiling to Predict Response to Treatment (MP2PRT) program is part of the NCI's Cancer Moonshot Initiative. The aim of this program is the retrospective characterization and analysis of biospecimens collected from completed NCI-sponsored trials of the National Clinical Trials Network and the NCI Community Oncology Research Program. NRG RTOG (Radiation Therapy Oncology Group)-0539, which was a nonrandomized phase II cooperative group trial in 2009, was selected for inclusion in this program. NRG RTOG-0539 assigned patients with histologically confirmed diagnosis of meningioma to 1 of 3 risk groups based on 2007 WHO grade, resection extent, and recurrence status, and radiotherapy was given per protocol to the intermediate- and high-risk cases. Under the MP2PRT program, DNA methylation profiling, RNA sequencing, and whole exome sequencing were performed on clinical trial cases with available tissue for molecular analyte extraction and subsequent sequencing. Raw molecular data with metadata are available for this study.

  Study phs003707

• Single_cell_analysis_T_cell_activation

  We isolated naïve and memory T cells from healthy donors and cultured them in resting and stimulated conditions. We performed scRNA sequencing to assess T cell actiavtaion and perform sceQTL analysis. Major challenges for translating GWAS variants to function include identification of the disease relevant cell types in which the associated variants function. We have shown that immune-disease variants are functional in CD4+ T cell activation, and understanding how GWAS variants affect the activation efficiency is critical for development of new therapies. To perform sceQTL analysis of naïve and memory T cell activation, here we stimulated T cells and profiled single cell transcriptome at different time points following stimulation. We mapped sceQTLs affecting cell activation. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001003479

• EGA synthetic data

  Synthetic Data One of the limitations in genomics research is that human genomics data is not openly available; access must be controlled according to participant consent agreements and data protection regulations such as GDPR. Obtaining authorization to access such data can sometimes take a long time, resulting in delays to important research work. In this context, synthetic genomic and phenotype data can be useful resources for researchers to avoid these delays. Synthetic data are artificially generated datasets, often created with algorithms, which can be used without the need for authorization to test new products and tools, build technical demonstrators, validate data models, and train AI models. The EGA provides access to synthetic cohort datasets augmented with rich synthetic metadata that overcomes these real data usage restrictions. Whilst synthetic datasets are not included in the general EGA mandate and services, we can consider such submissions and evaluate their acceptance on the basis of their unique use cases not already covered by existing synthetic datasets. Access to synthetic data studies is managed by the EGA Helpdesk Data Access Committee. Study ID Title Located in EGAS00001002472 CINECA synthetic cohort EUROPE UK1 referencing fake samples Central EGA EGAS00001005591 Synthetic data - Genome in a Bottle Central EGA EGAS00001005042 Test Study for EGA using data from 1000 Genomes Project - Phase 3 Central EGA EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Central EGA EGAS50000000190 EOSC4Cancer Synthetic Colorectal Cancer Genomic data Central EGA EGAS50000000086 Synthetic - FEGA Sweden Heilsa synthetic dataset December 2023 Federated EGA Sweden EGAS50000000678 Synthetic - GDI synthetic data Federated EGA Spain

  Documentation synthetic-data

• Genomic Studies of Bipolar Disorder in a Large Cohort from The Netherlands

  The transcriptomes of whole blood samples of a large cohort of individuals from the Netherlands were assayed using RNA-seq. These whole blood samples included patients diagnosed with schizophrenia or bipolar disorder, family members of patients, and healthy controls. Within the whole blood dataset, about 600 of the samples were sequenced to an average of 13.9 million mapped reads per sample, while about 2,000 were sequenced to an average of 5.9 million mapped reads per sample, in order to assess changes in power to detect eQTLs based on sample size. We find that expression, defined as the log transcripts per million reads (TPMs), is highly correlated when comparing the moderate (13.9M) and lower (5.9M) coverage datasets. Additionally, a subset of about 150 individuals provided fibroblast cell lines which were assessed for the levels of gene expression using RNA-seq at an average of 50 million mapped reads per sample. We use downsampling techniques to generate synthetic datasets derived from this real fibroblast RNA-Seq data to explore the relationship between coverage and number individuals in an eQTL analysis. Corresponding individual-level genotypes for the samples included in the expression matrix are also made available. The genotypes were derived from multiple other project cohorts, each using different genotyping platforms including OmniExpress Exome, Global Screening Array, Illumina550, and PsychChip. A Plink file set of these cohorts is provided here after merging the separate project file sets and extracting only the individuals who have expression data also provided here; quality control for SNP-missingness is recommended. We demonstrate in this study that given a fixed budget, eQTL discovery power can be increased by lowering the sequencing depth per sample to allow for an a greater number of individuals sequenced. 

  Study phs002856

• Evaluating gene expression in aggressive B-cell lymphoma using a quantitative nuclease protection assay

  Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma (NHL), comprising 25-30% of all NHL in developed countries with an annual incidence in the USA of 7 cases/100000 persons/year. Collectively, DLBCL is classified based on a common morphological appearance of diffuse growth of large transformed B-cells, immunophenotype, high proliferation rate and aggressive behaviour. Despite these similarities, DLBCLs are a heterogeneous collection of malignancies with distinct clinical and molecular characteristics that do not always correlate with immunohistological features. This gene expression dataset includes transcriptomes of ABC-DLBCLs and of GCB-DLBCLs where cell of origin is determined by the HTG-EdgeSeq quantitative nuclease protection assay. Also included are clonality results from BCR profiling from high-grade B-cell lymphomas sequenced using a NOVA sequencer

  Dataset EGAD00001011309

• Gene-Environment Interactions in COCCaINE Use Disorder: Collaborative Case-Control Initiative in Cocaine Addiction

  Drug addiction is a phenotype that has high heritability estimates. In recent years, association studies of candidate genes and some genome-wide association studies (GWAS) have identified a large number of SNPs associated with substance use, abuse or dependence, particularly in phenotypes related to alcohol and nicotine use. Regarding snorted or smoked cocaine dependency, only one GWAS has been conducted so far. In addition, genetic association studies that specifically evaluated smoked cocaine dependence (e.g. crack) are rare, because of characteristics related to the route of administration and duration of the effect of the drug. Thus, the main aim of this GWAS was to identify genetic variations that modulate the risk for the cocaine dependence.

  Study phs001810

• Epigenetic Analysis of Malnutrition

  The PROVIDE study (Dhaka, Bangladesh) is a randomized clinical trial platform which evaluated the efficacy of delayed-dose oral rotavirus vaccine as well as the benefit of an injectable polio vaccine replacing one dose of oral polio vaccine. This rigorous infrastructure supported the additional examination of hypotheses of vaccine underperformance. Primary and secondary efficacy and immunogenicity measures for rotavirus and polio vaccines were measured, as well as the impact of maternal and childhood malnutrition, environmental enteropathy, and additional exploratory variables. This study has been conducted to test the role of epigenetics in malnutrition, specifically the genome-wide role of histone modifications, which are known to provide a precise signature of metabolic state and immune system function.

  Study phs001073

• Comprehensive molecular and clinicopathological profiling of glioma

  Various molecular profiles are needed to classify malignant brain tumors, including gliomas, based on the latest classification criteria of the World Health Organization, and their poor prognosis necessitates new therapeutic targets. The Todai OncoPanel 2 RNA Panel (TOP2-RNA) is a custom-target RNA-sequencing (RNA-seq) using the junction capture method to maximize the sensitivity of detecting 455 fusion gene transcripts and analyze the expression profiles of 1,390 genes. This study aimed to classify gliomas and identify their molecular targets using TOP2-RNA. A total of 124 frozen samples of malignant gliomas were subjected to TOP2-RNA for classification based on their molecular profiles and the identification of molecular targets.

  Study JGAS000671