6312 results for "fc coins pc Buyfc26coins.com is FC 26 coins official site..T357"

in 23.35 milliseconds.

• How to request data

  Request Data Access If you're looking to access data from the EGA for your research, you are in the right documentation page! In this page you will find a step by step guide on how to request data archived at the EGA, as well as some frequently asked questions you might find useful. When requesting data, you'll need to provide information about your research project and intended use of the data. Keep in mind that your data access request may require additional approvals or agreements depending on the datasets and data providers involved. Step by step guide Register yourself as an EGA user. Validate your account. A validation link will be sent to your email to activate your EGA user account. Log into the EGA page. Search the dataset of interest from the dataset catalogue or search bar. Click on “Request access” Add a comment requesting these files and send your request Your request is successfully registered, and the DAC will receive a notification about your request In addition to submitting your request, you should also contact the DAC directly via e-mail. You can access the DAC's contact information from the relevant dataset page. Frequently Asked Questions (FAQ) Which is the role of the EGA in the data access process? The European Genome-phenome Archive (EGA) facilitates the secure distribution under controlled access of personally identifiable genetic and phenotypic data. Data Access Committee (DAC) is a body of one or more individuals who are responsible for data release to external requestors, based on participant consent and/or National Research Ethics terms. How do I request access to multiple datasets? To request access for multiple datasets managed by the same Data Access Committee (DAC), please start by visiting the DAC catalogue to locate the DAC of your choice. Once you've found the relevant DAC, proceed to its dedicated page where you'll find a "Request access" button. After logging in to the EGA website, you'll be presented with a comprehensive list of datasets under the chosen DAC. Select the datasets you're interested in, and then compose a message indicating your access request. Click the "Send" button to submit your request, which will include the chosen datasets. Please be sure to review the data usage policies for the requested datasets, as policies can vary among datasets managed by the same DAC. I am a co-applicant. Will I be given a joint access account? Each applicant needs to create an EGA account themselves, with unique login details. User log-in details are for individual use only and should never be shared, under any circumstances. EGA services are only provided to EGA account holders. Therefore, the co-applicant will send a formal request to the DAC. What happens if a co-applicant leaves or a new member needs to be added to an existing DAC application? The appropriate Data Access Committee (DAC) should be contacted and informed about the required changes so that the application can be updated. I have changed my place of work since my EGA account was created. Can I still have access to data? You must contact the relevant Data Access Committee (DAC). The DAC did not reply to my data access request. How should I proceed? There is no estimated time for DAC response. Please allow up to four weeks for a response. In the meantime, please send them a weekly reminder of the status of your request by emailing them directly.If the DAC becomes unresponsive, meaning that they fail to communicate with a requestor within the specified time frame, please contact the EGA Helpdesk team. I have an account with the EGA and would like access to further datasets. How should I proceed? You need to reapply to the relevant Data Access Committee (DAC). Once the DAC has approved your application your account will be updated and an email will be sent to notify you of a change made to your account. How do I download files of the datasets I have been granted access to? The preferred method for data download and decryption is the EGA Secure Download Client. Please carefully review the provided documentation. How do I download metadata? Metadata is retrieved from the EGA webpage; you will not need to use any download client. Be informed that you will only be able to download metadata of your approved datasets. For such download, you should first log in the EGA webpage with your credentials. Then browse the metadata's dataset you have gained access and you will find a metadata download button. You may also want to have a look our metadata schema. I have forgotten or misplaced my user account password; how do I get a new one? Click on “Log in”, located in the top right corner of the EGA homepage. Then click “Forgot password”, type in your registered institutional email address, and instructions for resetting your password will be sent to you. Please check both regular and junk/spam folders. I was sent a link to set a password for my download account, but it seems like the link has expired. What should I do? The procedure is the same as the one for a forgotten password, explained in the previous question.

  Documentation access/request-data/how-to-request-data

• Surveillance, Epidemiology and End Results (SEER) Formalin Fixed Paraffin Embedded (FFPE) Tissue Feasibility Study

  Next Generation Sequencing (NGS) technologies are being used for detection of somatic mutations in tumors and studies of germline variation. However, most NGS studies used DNA isolated either from whole blood or fresh frozen tissue specimens. Meanwhile, the tissue specimens available from most National Cancer Institute (NCI) funded cohorts and the Surveillance, Epidemiology and End Results (SEER) registries (http://seer.cancer.gov/biospecimen) are primarily formalin fixed paraffin embedded (FFPE). There are limited data, on a small number of FFPE tissue samples, which suggest NGS is feasible. Much less is known about the feasibility of these technologies for large scale studies or using older FFPE specimens (e.g. 5-30 years old). The SEER cancer registries cover approximately 28% of the United States population, providing high quality demographic, clinical, pathologic, and survival data. The SEER Residual Tissue Repository (RTR) program was established in 2003. The RTR maintains biospecimens obtained from three of SEER' population-based cancer registries: Iowa, Hawaii, and Los Angeles. Investigators at government, academic, and nonprofit institutions may apply to the program to obtain annotated FFPE tumor tissue specimens to study biomarkers, etiology, and other aspects with a population-based sample of cancer cases. The main objective of this project was to conduct a pilot study to determine whether the DNA obtained from archival FFPE tissue from 3 SEER Registries is of sufficient quality and quantity to conduct NGS. For Exome sequencing, sixty high-grade serous ovarian adenocarcinomas from FFPE tissues which were between 7 and 31 years old were obtained from three SEER registries. DNA was extracted, quantified, quality assessed, and subjected to whole exome sequencing. DNA extraction (yields and quality) and whole exome sequencing (depths of coverage and exome coverage obtained) results from this study will be presented. For RNA-sequencing, sixty-seven high-grade serous ovarian adenocarcinomas from FFPE tissues which were between 7 and 31 years old were obtained from three SEER registries. Total RNA was extracted, quantified, quality assessed, and subjected to whole transcriptome sequencing. Ultimately data derived from this analysis could serve as the basis for determining the utility of archival FFPE biospecimens for characterization and discovery projects utilizing NGS technologies instead of relying on frozen biospecimens.

  Study phs000950

• Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: KARE

  T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples) is a NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a sub study, as it is not consented to be deposited in dbGAP. Table 1. T2D-GENES Whole Exome Sequencing Studies Ancestry Study Countries of Origin # Cases # Controls African American Jackson Heart Study US 502 527 African American Wake Forest School of Medicine Study US 518 532 East Asian Korea Association Research Project Korea 526 561 East Asian Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 486 592 European Ashkenazi US, Israel 506 352 European Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European Malmö-Botnia Study Finland, Sweden 478 443 Hispanic San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 219 Hispanic Starr County, Texas US 749 704 South Asian London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 530 538 South Asian Singapore Indian Eye Study Singapore (Indian Asian) 563 585 The Korea Association Research Project (KARE) studies contributed 526 cases and 561 controls to T2D-GENES Project 1.

  Study phs001096

• Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: Ashkenazi

  T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples) is a NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a sub study, as it is not consented to be deposited in dbGAP. Table 1. T2D-GENES Whole Exome Sequencing Studies Ancestry Study Countries of Origin # Cases # Controls African American Jackson Heart Study US 502 527 African American Wake Forest School of Medicine Study US 518 532 East Asian Korea Association Research Project Korea 526 561 East Asian Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 486 592 European Ashkenazi US, Israel 506 352 European Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European Malmö-Botnia Study Finland, Sweden 478 443 Hispanic San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 219 Hispanic Starr County, Texas US 749 704 South Asian London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 530 538 South Asian Singapore Indian Eye Study Singapore (Indian Asian) 563 585 The Ashkenazi study contributed 506 cases and 352 controls to T2D-GENES Project 1.

  Study phs001095

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (ARIC)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000398 contains the Atherosclerosis Risk in Communities (ARIC) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000398

• GEI Studies - Psoriasis

  The GEI Studies Project was started as an NIH consortium involving 5 disease groups with funding provided through the Genes, Environment, and Health Initiative (GEI). The objective of the project was to optimize strategies for identifying rare variants as a follow up to genome-wide association studies (GWAS) using next-generation sequencing technology. One of the five targeted diseases, Psoriasis, is a multifactorial skin disease characterized by epidermal hyperproliferation and chronic inflammation that affects approximately 2% of Americans. Because only about one-third of all patients with psoriasis have a relative who is also affected with the disorder, psoriasis is not widely recognized as a genetic disease. However, previous research on families and identical twins has shown psoriasis has a strong genetic component, although environmental factors (such as infections, stress, and injuries) are also important. Although no definite psoriasis gene has yet been identified, research during the last ten years has revealed over forty potential gene locations that may contribute to the disease. Large amounts of data generated using next-generation sequencing technology would provide a more detailed characterization of sequence variation which would in turn increase the likelihood of detecting causative loci. With the presumption that rare variants are frequently the cause of a large portion of phenotypic variation, it was necessary to use large sample sets. In the main body of this study, we sequenced 4,966 samples (812 dermatologist-diagnosed cases of purely cutaneous psoriasis (PsC), 1,497 cases of rheumatologist-diagnosed psoriatic arthritis, 665 cases of cutaneous psoriasis with uncertain psoriatic arthritis status (PsV) and 1,992 controls) across 5.7 Mb of sequence containing 100 psoriasis candidate loci and 769 genes. For each candidate locus, we considered sequences within 250 kb of the strongest association signal. Within this window, three strategies were employed. For ten of the strongest psoriasis signals, we used a whole-region approach which included non-coding intergenic and intronic sequence. For four established loci of lesser significance, we targeted all full transcription units within the +/- 250 kb interval. For the remaining signals, we targeted the exons of all transcription units within the +/- 250 kb interval. Due to complexities of high-efficiency targeting of HLA genes we selected 5 specific candidate genes for sequencing near the HLA-C gene.

  Study phs000766

• Foregut Microbiome in Development of Esophageal Adenocarcinoma

  The distal esophagus is an important anatomical area where gastric acid reflux can cause reflux esophagitis (RE), Barrett's esophagus (BE) (intestinal metaplasia), and esophageal adenocarcinoma (EA). The incidence of EA has increased 6-fold in the U.S. since the 1970s, parallel to a significant increase in the prevalence of gastroesophageal reflux diseases (GERD). Although specific host factors might predispose one to disease risk, such a rapid increase in incidence must be predominantly environmental. The cause remains unknown. Our hypothesis is that changes in the foregut microbiome are associated with EA and its precursors, RE and BE in the GERD sequence. We will conduct a case control study to characterize the microbiome in every stage of the GERD sequence as well as analyze the trend in changes in the microbiome along disease progression toward EA. Specific Aim 1. To conduct a comprehensive population survey of the foregut microbiome and demonstrate its association with GERD sequence, by a 16S rRNA gene survey. We will analyze samples of the foregut microbiome at three anatomic loci: mouth, distal esophagus, and gastric corpus. Changes of the microbiota in the distal esophagus will be correlated with the phenotypes. Spatial relationship between the esophageal microbiota and upstream (mouth) and downstream (stomach) foregut microbiotas as well as temporal stability of the microbiome-disease association will also be examined. Specific Aim 2. To define distal esophageal metagenome and demonstrate its association with GERD sequence, by shotgun metagenomic analysis. We will first classify samples of the metagenome into metagenotypes by between-sample k-mer distance and correlate the metagenotypes with the four phenotypes. Subsequent detailed analyses will include pathway-disease and gene-disease associations. DNA viruses and fungi, if identified, also will be correlated with the phenotypes. A significant association between the foregut microbiome composition and GERD sequence, if demonstrated, will be the first step for eventually testing the causal hypothesis that an abnormal microbiome is required for the development of the sequence of phenotypic changes toward EA. If EA and its precursors represent a microbial ecological disease, treating the cause of GERD might become possible, for example, by normalizing the microbiome through use of antibiotics, probiotics, or prebiotics. Causative therapy for GERD could prevent its progression and reverse the current trend of increasing incidence of EA.

  Study phs000260

• (Epi)genetic Risk Architectures of Opioid-Dependent Brain

  With nearly 20,000 overdose deaths in 2014 alone, opioid addiction (OA) has emerged as one of the most pressing public health crises in recent US history. One-fifth of individuals who try heroin develop an addiction to opioids. Genetics is a major contributor to OA with an estimated 60% heritability, only somewhat less than schizophrenia (80%) which has recently seen substantial gains in identified underlying genetics. Yet, studies to date have failed to uncover most of the genes that predispose individuals to OA, leaving the overwhelming fraction of OA heritability unexplained. The proposed study takes a novel, integrated "omics-based" strategy to investigate the molecular basis of OA and uncover both genetic and epigenetic factors associated with opioid addiction. The premise for our approach is founded on studies from our labs, and others, implicating regulatory variation in common traits and diseases, including those associated with complex brain phenotypes like addiction. We have collected the largest known cohort of postmortem brains from addicts who overdosed on opioids, along with matched control brains from non-users. From both cases and control specimens, we will isolate cells from 2 regions of the brain closely implicated in the addiction phenotype: the Prefrontal Cortex (PFC) and the Nucleus Accumbens (NAc). In Aim 1, we propose ChIP-seq studies to identify regulatory elements that distinguish cases from controls and define the opioid addiction phenotype. The regulatory differences will be connected to their gene targets through high resolution in situ Hi-C. In Aim 2, we propose QTL-based approaches to identify genetic variants that underlie the regulatory differences (hmQTLs). We also propose eQTL analyses to identify genetic variants that underlie differences in transcript levels between cases and controls. Aim 3 leverages the largest heroin addiction GWAS meta-analysis to date to test the hypothesis that SNPs in regions associated with chromatin and expression differences between cases and controls define novel loci for predisposition to OA. Each Aim has the potential for discovery independent of the others (differential HM, RNAexp, QTLs, and variant-phenotype associations) but their synergy is the most powerful component of the proposed study: identifying regulatory pathways that generate, not only phenotype associations, but hypothesized mechanisms for those associations which can be the focus of new opioid addiction prevention and treatment development.

  Study phs002724

• The genomic complexity of early T-cell progenitor acute lymphoblastic leukemia

  CREST The accurate identification of structural variations using whole-genome DNA sequencing data generated by next-generation sequencing technology is extremely difficult. To address this challenge, we have developed CREST, an algorithm that uses sequencing reads with partial alignments to the reference human genome (so-called soft-clipped reads) to directly map the breakpoints of somatic structural variations. We applied CREST to paired tumor/normal whole genome sequencing data from five cases of T-lineage acute lymphoblastic leukemia (T-ALL). A total of 110 somatic structural variants were identified, >80% of which were validated by genomic PCR and Sanger sequencing. The validated structural variants included 31 inter-chromosomal translocations, 19 intra-chromosomal translocations, one inversion, 22 deletions and 16 insertions. A comparison of the results generated with CREST to those obtained using the traditional paired-end discordant mapping methods demonstrate CREST to have a much higher sensitivity and specificity. In addition, application of CREST to publicly available whole-genome sequencing data from the human melanoma cancer cell line COLO-829 demonstrated the identification of 50 novel structural variations not detected using the standard methods, 20 of which were selected for validation with a 90% success rate. These data demonstrate that direct mapping of soft-clipped reads offers an improved method for detecting structural variants at the nucleotide level of resolution. T-ALL Early T-cell precursor acute lymphoblastic leukaemia (ETP ALL) is an aggressive malignancy of unknown genetic basis. We performed whole-genome sequencing of 12 ETP ALL cases and assessed the frequency of the identified somatic mutations in 94 T-cell acute lymphoblastic leukaemia cases. ETP ALL was characterized by activating mutations in genes regulating cytokine receptor and RAS signalling (67% of cases; NRAS, KRAS, FLT3, IL7R, JAK3, JAK1, SH2B3 and BRAF), inactivating lesions disrupting haematopoietic development (58%; GATA3, ETV6, RUNX1, IKZF1 and EP300) and histone-modifying genes (48%; EZH2, EED, SUZ12, SETD2 and EP300). We also identified new targets of recurrent mutation including DNM2, ECT2L and RELN. The mutational spectrum is similar to myeloid tumours, and moreover, the global transcriptional profile of ETP ALL was similar to that of normal and myeloid leukaemia haematopoietic stem cells. These findings suggest that addition of myeloid-directed therapies might improve the poor outcome of ETP ALL.

  Study phs000340

• Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: Singapore

  T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples) is a NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a sub study, as it is not consented to be deposited in dbGAP. Table 1. T2D-GENES Whole Exome Sequencing Studies Ancestry Study Countries of Origin # Cases # Controls African American Jackson Heart Study US 502 527 African American Wake Forest School of Medicine Study US 518 532 East Asian Korea Association Research Project Korea 526 561 East Asian Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 486 592 European Ashkenazi US, Israel 506 352 European Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European Malmö-Botnia Study Finland, Sweden 478 443 Hispanic San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 219 Hispanic Starr County, Texas US 749 704 South Asian London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 530 538 South Asian Singapore Indian Eye Study Singapore (Indian Asian) 563 585 The Singapore studies contributed 1049 cases and 1177 controls to T2D-GENES Project 1.

  Study phs001097

• Type 2 Diabetes Genetic Exploration by Next-generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: London Life Sciences Population Study (LOLIPOP) UK South Asian

  T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples) is a NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a sub study, as it is not consented to be deposited in dbGAP. Table 1. T2D-GENES Whole Exome Sequencing Studies Ancestry Study Countries of Origin # Cases # Controls African American Jackson Heart Study US 502 527 African American Wake Forest School of Medicine Study US 518 532 East Asian Korea Association Research Project Korea 526 561 East Asian Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 486 592 European Ashkenazi US, Israel 506 352 European Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European Malmö-Botnia Study Finland, Sweden 478 443 Hispanic San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 219 Hispanic Starr County, Texas US 749 704 South Asian London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 530 538 South Asian Singapore Indian Eye Study Singapore (Indian Asian) 563 585 The London Life Sciences Population Study (LOLIPOP) contributed 530 cases and 538 controls to T2D-GENES Project 1.

  Study phs001093

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (FHS)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000401 contains the Framingham Heart Study (FHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000401

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (JHS)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000402 contains the Jackson Heart Study (JHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000402

• NHLBI GO-ESP: Early-Onset Myocardial Infarction Exome Chip (Broad EOMI)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. As part of this initiative, the Broad has performed genotyping on several thousand subjects from 4 different cohorts on Illumina's ExomeChip platform as described below: The Duke Study: The Duke study enrolled cases from the Duke University Medical Center with myocardial infarction or coronary artery stenosis > 50%. Controls were individuals who were > 50 years old without coronary stenosis > 30% and without history of myocardial infarction, coronary artery bypass grafting, percutaneous coronary intervention, or heart transplant. The InterMountain Heart Study: The Intermountain Heart Study is an observational registry of individuals with coronary artery disease and healthy controls who received care at participating Intermountain Healthcare facilities. The Ottawa Heart Study: The Ottawa heart study enrolled cases with angiographically confirmed coronary artery disease (> 1 coronary artery with > 50% stenosis) who did not have type 2 diabetes and were ≤ 50 years old for males and ≤ 50 years old for females. Controls were also enrolled who were asymptomatic males > age 65 and females > age 70. PennCATH: PennCATH is a case-control study that recruited individuals undergoing coronary angiography at the University of Pennsylvania Hospital. Cases had angiographically confirmed coronary artery disease (>1 coronary artery with 50% stenosis) and were ≤ 55 years old if male and ≤ 60 years old if female. Controls were men > 40 years old and women > 45 years old with normal coronary angiography.

  Study phs000936

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (CHS)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000400 contains the Cardiovascular Health Study (CHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000400

• PRE-DETERMINE: Biologic Markers and MRI SCD Cohort Study

  The PRE-DETERMINE Study is a prospective, multi-center study of 5,764 patients with a history of coronary artery disease (CAD) and documentation of either a prior myocardial infarction (MI) or mild to moderate left ventricular dysfunction (LVD) with left ventricular ejection fraction (LVEF) 35-50%. Patients were enrolled at 136 sites where information on baseline demographics, clinical characteristics, pertinent past medical history, lifestyle habits, cardiac test results, and medications were collected via electronic data capture. Electrocardiograms (ECG) along with a blood sample was also collected at baseline, sent to central laboratories, and stored for future analyses. Contrast-enhanced magnetic resonance imaging (CE-MRI) scans were collected on a subset of patients and analyzed. Enrollment closed in November 2013 and patients are now being followed centrally by the Clinical Coordinating Center via mail/phone to document interim non-fatal arrhythmic events and cause-specific mortality. Questionnaires that inquire about intervening implantable cardiac defibrillator (ICD) implantations, ICD therapies, cardiac arrest, and other pertinent cardiovascular endpoints are mailed to participants every six months, and follow-up telephone calls are made to non-responders. Study endpoints are being confirmed through review of medical records, interviews with next-of-kin, and autopsy reports, if available.The primary objective of PRE-DETERMINE is to determine whether biologic markers and ECGs can be utilized to advance sudden cardiac death (SCD) risk prediction in patients with coronary heart disease (CHD) and LVEF >30-35%. The overarching goal of the study is to identify a series of markers that alone or in combination specifically predict risk of arrhythmic death as compared to other causes of mortality among this at risk population of CHD patients with preserved LVEF> 30-35%. If biologic or ECG markers are identified that can specifically predict risk of ventricular arrhythmias, then these markers may serve as relatively inexpensive methods to identify those at risk. The public health impact of identifying markers could be quite substantial, leading to more efficient utilization of ICDs and advances in our understanding of mechanisms underlying SCD.Among the 95% of participants that provided a blood sample at baseline, genome wide genotyping using the Illumina Global Screening Array (GSA) has been performed. A total of 4,335 participants with European ancestry gave consent that allows genetic research and deposition of data into dbGaP.

  Study phs002940

• Type 1 Diabetes Genetics Consortium (T1DGC): Multi-Ethnic ImmunoChip Study

  Type 1 diabetes (T1D) is characterized by an autoimmune attack that destroys the insulin-producing pancreatic beta cells and is driven by diverse genetic and environmental factors. Between 8-100 chromosome regions are known to contain variants that alter T1D risk, substantially fewer than many other common diseases. Less is known about the contribution of T1D risk alleles in non-European populations, despite recent increases in T1D diagnoses in multiple non-European ancestry groups. To address these gaps in T1D genetics, we doubled the sample size from the previous largest T1D association study, genotyped ancestrally diverse T1D cases, controls, and affected families with the Illumina ImmunoChip array, and imputed additional variants using a large haplotype reference panel. After quality filtering, a total of 61,427 participants and 140,333 genotyped ImmunoChip variants were included in analysis, providing dense coverage in 188 autosomal regions ("ImmunoChip regions") and sparse genotyping in other regions of the genome. Each participant was assigned to one of five ancestry groups using k-means clustering of ImmunoChip genotype principal components: European (EUR, N = 47,319), African Admixed (AFR, N = 4,290), Finnish (FIN, N = 6,991), East Asian (EAS, N = 588) and Other Admixed (AMR, N = 2,239). In total, 16,159 T1D cases, 25,386 controls (unrelated) and 6,143 trio families (i.e., an affected child and both parents) were genotyped and included in association analyses. Imputation with the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) multi-ethnic reference panel was used to improve discovery power and fine-mapping resolution. After imputation, the number of variants in ImmunoChip regions with imputation R-squared > 0.8 and MAF > 0.005 in each ancestry group was 322,084 (AFR), 166,274 (EUR), 163,612 (FIN), 137,730 (EAS) and 188,550 (AMR). Imputed genotypes were compared in the same participants who have whole genome sequencing data, resulting in high concordance. Unrelated cases and controls (N = 41,545) were analyzed initially, assuming an additive inheritance model. T1D trio families (N = 6,143 trios, some trio families were multiplex and analyzed as multiple trios) were analyzed separately, with meta-analysis of case-control and trio results used for discovery of regions associated with T1D (p < 5×10-8). Summary-level data at each SNP (genotype and imputed) for type 1 diabetes (outcome) are provided in dbGaP.

  Study phs002468

• Study of Environment, Lifestyle and Fibroids SNP Data

  Uterine fibroids are hormonally-dependent benign tumors of the uterine muscle that develop in premenopausal women. Currently, the primary symptoms (pain and bleeding) are treated, but when those treatments fail, major procedures to remove or shrink the fibroids are frequently the only options for women. Fibroids are the leading indication for hysterectomy in the United States. African-American women develop fibroids an average of 10 years earlier than white women in the U.S., and they are approximately three times more likely to have a hysterectomy for fibroids. The known risk factors for fibroids do not explain this disparity.The goal of the Study of Environment, Lifestyle & Fibroids (SELF) is to identify risk factors for uterine fibroid development. It is the first study to identify incident cases based on ultrasound screening. We enrolled a cohort of 1693 women who self-identified as Black or African American, ages 23-35, from the Detroit, Michigan area. Women with a prior diagnosis of fibroids were not eligible. Participants were screened for fibroids with ultrasound at enrollment, and follow-up ultrasounds occurred approximately every 20 months to identify new fibroids. Fibroids that were detected at enrollment and those that arose during follow up were monitored at subsequent visits for fibroid growth. We collected risk factor and symptom data, physical measurements, as well as blood, urine, and vaginal swab specimens at enrollment and follow-up visits.The study was designed to test three primary hypotheses:Vitamin D deficiency is a risk factor for fibroid incidence and/or growth.Reproductive tract infections can increase risk of fibroid development.Genotypic variation in African ancestry may influence fibroid development directly, or through interaction with life-course risk factors.In addition, we collected extensive information to examine other exposures of interest, and our extra specimens can be used to test new hypotheses in the future.With this first prospective study of fibroid development, we aim to identify new preventative factors that could directly benefit women. We anticipate that the detailed data on fibroid development can be used to help design new interval treatment strategies to limit fibroid growth and thus reduce the need for the invasive treatments that remain the standard of care when first-line treatments fail.

  Study phs002513

• Acute Respiratory Distress Network (ARDSNet) Studies 06 and 08 Prospective, Randomized, Multicenter Trial of Aerosolized Albuterol Versus Placebo for the Treatment of Acute Lung Injury (ALTA) (ARDSNet-ALTA-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. Biospecimens Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-ALTA include Plasma, DNA, Urine, and BAL. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives This clinical trial was designed to test the hypothesis that an aerosolized beta-2-agonist, albuterol, would improve clinical outcomes in participants with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). Background In participants with acute lung injury and acute respiratory distress syndrome (ALI/ARDS), inflammation of the pulmonary circulation increases vascular permeability. Fluid leaks from blood vessels into the pulmonary interstitium and alveoli. Recovery from this form of acute respiratory failure requires that the pulmonary edema resolve. The resolution of alveolar edema is driven by active transport of sodium and chloride ions from the luminal space across both type I and type II alveolar epithelial cells, creating an osmotic gradient for the reabsorption of water. In the ex vivo human lung, the rate of alveolar fluid clearance can be doubled by treatment with a cyclic AMP beta-2 adrenergic receptor agonist. On the basis of the preclinical observations that treatment with beta-2-agonists could reduce pulmonary edema and accelerate the rate of alveolar fluid clearance, the ALTA study was designed and undertaken with the hypothesis that treatment of participants with ALI/ARDS with beta-agonist therapy would accelerate the resolution of alveolar edema and improve clinical outcomes. Participants There were 282 participants. Design Study staff conducted a multicenter, randomized, placebo-controlled clinical trial in which participants were randomized to receive aerosolized albuterol (5 mg) or saline placebo every 4 hours for up to 10 days. The primary outcome variable for the trial was ventilator-free days. Conclusions Ventilator-free days were not significantly different between the albuterol and placebo groups. The results suggest that aerosolized albuterol does not improve clinical outcomes in participants with ALI. Routine use of beta-2 agonist therapy in mechanically ventilated participants with ALI cannot be recommended (Matthay, et al., 2011, PMID: 21562125).

  Study phs003743

• Idiopathic Pulmonary Fibrosis Network (IPFnet) Prednisone, Azathioprine, and N-Acetylcysteine: A Study That Evaluates Response in Idiopathic Pulmonary Fibrosis (IPFNet-Panther-IPF-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: The initial objective of the PANTHER-IPF study was to evaluate the effectiveness of a drug combination of prednisone, azathioprine, and N-acetylcysteine in the treatment of mild-to-moderate idiopathic pulmonary fibrosis (IPF) compared to N-acetylcysteine alone or placebo. After interim analysis presented safety concerns regarding the three drug regimen, the protocol was modified to evaluate only N-acetylcysteine effectiveness. Background: IPF is a chronic, progressive lung disease of unknown cause that is characterized by the histopathological or radiologic patterns of usual interstitial pneumonia in a typical clinical setting. The median survival of participants with idiopathic pulmonary fibrosis after diagnosis is 2 to 5 years. To date, no pharmacologic therapies have been shown to improve survival. Acetylcysteine has been suggested as a beneficial treatment for idiopathic pulmonary fibrosis, although data from placebo-controlled studies are lacking.Design: Patients with mild-to-moderate impairment in pulmonary function were randomly assigned to receive a three-drug regimen (prednisone, azathioprine, and acetylcysteine), acetylcysteine alone (plus matched placebos for prednisone and azathioprine), or matched placebos for each of the active therapies. After the planned midpoint interim analysis, the data and safety monitoring board recommended discontinuation of the three-drug regimen because of an excess in the number of deaths, hospitalizations, and serious adverse events among patients in the combination-therapy group, as compared with the placebo group. After NHLBI accepted this recommendation on October 14, 2011, the three-drug regimen was discontinued and patients were recruited for only the acetylcysteine group and the placebo group. Patients were seen at the clinical centers for screening, at baseline, and at 4, 15, 30, 45, and 60 weeks. The primary outcome measure was change in FVC over 60 weeks.Conclusions: As compared with placebo, acetylcysteine offered no significant benefit with respect to the preservation of FVC in patients with idiopathic pulmonary fibrosis with mild-to-moderate impairment in lung function. In addition, there were no significant differences between the acetylcysteine group and the placebo group in the rates of death or acute exacerbation.

  Study phs004071

• dbGaP Collection: Compilation of Individual-Level Genomic Data for General Research Use

  This dbGaP Collection contains all authorized individual-level genomic datasets currently in dbGaP that are approved for General Research Use (GRU) and have no further limitations beyond those outlined in the model Data Use Certification Agreement. Access to this study will include any additional authorized individual-level GRU datasets that become available. Renewal of this study is required annually. Data Included in this Study Individual-level genomic data designated for general research use with no further use limitations or restrictions, that is, Data use does not require approval by an Institutional Review Board for secondary analyses Data have no publication embargo Data have no other use limitations (e.g., requirement for collaboration or publication; restricted for use by academic or not-for-profit organizations; restricted to health, medical, and/or biomedical research) In response to requests from the scientific community, the NIH implemented a change in the procedures for accessing individual-level GRU genomic data. Under the modified procedures, interested investigators can request GRU individual-level genomic datasets with a single application. However, please note that these data have not been harmonized. Additionally, to help expedite the processing of requests for individual-level GRU genomic datasets, the requests will be reviewed by a single, central Data Access Committee. The process for requesting these datasets is identical to the request process for non-GRU individual-level, controlled-access data, such as the expectation that investigators will abide by the NIH Policy for Sharing of Data Obtained in NIH Supported or Conducted Genome-Wide Association Studies and Data Use Certification Agreement. Effective April 24, 2018, the Data Use Limitations (DUL) for the Genes and Blood Clotting Study (GABC) (phs000304) was updated to Health/Medical/Biomedical, Not-for-profit Use Only (HMB-NPU). Additionally, the submitting institutions have requested the removal of the National Heart, Lung, and Blood Institute (NHLBI) "Grand Opportunity" Exome Sequencing Project (GO-ESP) Lung Cohorts Exome Sequencing Project: Genetic modifiers of Pseudomonas aeruginosa (Pa) lung infection acquisition in cystic fibrosis (phs000254) from the dbGaP Compilation of Individual-Level Genomic Data for General Research Use (dbGaP Compilation) (phs000688). As such, data from studies phs000304 and phs000254 are no longer available as part of the dbGaP Compilation (phs000688). Investigators must submit separate Data Access Requests (DARs) for the two studies and be approved by the NHLBI Data Access Committee.

  Study phs000688

• Multi-omics data of 1000 Inflammatory Bowel Disease patients

  Portal available at https://1000ibd.org Inflammatory bowel disease (IBD) is a chronic complex disease of the gastrointestinal (GI) tract. Patients with IBD can experience a wide range of symptoms, but the pathophysiological mechanisms that cause these individual differences in clinical presentation remain largely unknown. In consequence, IBD is currently classified into subtypes using clinical characteristics. If we are to develop a more targeted treatment approach, molecular subtypes of IBD need to be discovered that can be used as new drug targets. To achieve this, we need multiple layers of molecular data are generated from the same IBD patients.We initiated the 1000IBD project to prospectively follow more than 1000 IBD patients from the Northern provinces of the Netherlands. For these patients, we have collected a uniquely large number of phenotypes and generated multi-omics profiles. To date, 1,215 participants have been enrolled in the project and enrolment is on-going, with 609 patients being present in the first data release. Phenotype data collected for these participants includes information on dietary and environmental factors, drug responses, and adverse drug events. Genome information has been generated using genotyping (ImmunoChip, Global Screening Array and HumanExomeChip) and sequencing (whole exome sequencing and targeted resequencing of IBD susceptibility loci), transcriptome information generated using RNA-sequencing of intestinal biopsies and microbiome information generated using both sequencing of the 16S rRNA gene and whole genome shotgun metagenomic sequencing.All molecular data generated within the 1000IBD project will be shared in multiple data on the European Genome-Phenome Archive (www.ega-archive.org). The first data release, will contain basic phenotypes for 609 participants, genotypes of 314 participants, gut microbiome data generated by tag sequencing the 16S gene of feces from 315 participants and intestinal biopsies from 107 participants, and gut microbiome metagenomic sequencing of feces of 355 participants . Future releases will comprise many more additional phenotypes and -omics data layers. 1000IBD data can be used by other researchers as a replication cohort, a dataset to test new software tools, or a dataset for applying new statistical models.

  Study EGAS00001002702

• UK10K RARE COLOBOMA

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. Ocular coloboma is the most common significant developmental eye defect with an incidence of ~1 in 5,000 live births. It results from failure of optic fissure closure during embryogenesis. The position and extent of the fusion failure dictates the clinical appearance and functional effect. ~30% of coloboma cases are associated with other systemic malformations. These UK10K samples will mostly comprise isolated coloboma cases without systemic involvement (aka non-syndromal coloboma). There is strong evidence from family studies that coloboma has a major genetic component with autosomal dominance being the most common pattern of inheritance. However, many cases are isolated or show complex patterns of familial clustering. The genes responsible for isolated coloboma are largely unknown, but in a small number of families mutations in SHH, CHX10, and PAX6 have been identified indicating marked genetic heterogeneity. Thus in addition to the clinical benefits of achieving a molecular diagnosis there are also major scientific advantages to identifying coloboma genes, as these are likely to provide insights into the complex process of optic fissure closure, that is critical to normal eye development. In the longer term, understanding the molecular basis of the disease may provide clues to therapeutic strategies.For further information with regard to this cohort please contact David Fitzpatrick (david.fitzpatrick@ed.ac.uk).

  Study EGAS00001000127

• Wellcome Trust Sanger Institute

  Access to individual-level genotype data is available by application to the MalariaGEN Independent Data Access Committee. Access to data will be granted to qualified investigators for appropriate use. For further information information on data release policy and data access application form, please follow the link below.

  Dac EGAC00000000002

• Mutational Profile in Newly Diagnosed Diffuse Large B-Cell Lymphoma: Insights from the GAINED Study

  The GAINED study (NCT01659099) is a randomized phase 3 trial comparing obinutuzumab (G) to rituximab (R) in combination with ACVBP or CHOP14 induction, followed by PET-guided consolidation. This post-hoc analysis focuses on primary mediastinal B-cell lymphoma (PMBL) patients, confirmed through expert pathological review and characterized using gene-expression profiling (GEP) and Next-Generation Sequencing (NGS).

  Dac EGAC50000000540

• Cancer Research UK Manchester Institute/ Cancer Research UK National Biomarker Centre Data Access Committee

  Cancer Research UK Manchester Institute/Cancer Research UK National Biomarker Centre Data Access Committee is created to • Review and approve data access requests. • Ensure data security and compliance with institutional and legal obligations. • Maintain accurate records of access decisions For questions or further information, please contact: Chair of the Data Access Committee: Caroline Wilkinson Email: dac@cruk.manchester.ac.uk

  Dac EGAC50000000795

• DCIS_FF_RNAseq

  This RNAseq dataset contains full transcriptome data on n=77 pure DCIS samples. The RNA is derived from fresh-frozen DCIS samples, obtained from two hospital based cohorts (NKI cohort and Oslo cohort). The libraries were sequenced with 54 bp paired end reads using a Novaseq instrument (Illumina). We share fastq data files of paired end sequencing (two files per sample).

  Dataset EGAD50000002123

• Aligned Low pass whole genbome sequencing of cell free and tumour DNA from 5 patients with high grade serous ovarian cancer. Samples have been aligned to hg19 and bam files uploaded

  This is the aligned bam files of 5 patients, with sequential sampltes from patients comprising cfDNA and FFPE extracted tumour DNA

  Dataset EGAD50000001632

• Tumor Profiler Project - OV cell-free DNA data

  The dataset contains amplicon sequencing data from 48 samples from 35 different patients with ovarian cancers. Cell free DNA was collected from plasma. Sequencing was performed on an Ion Torrent platform and the sequencing data is provided in bam format.

  Dataset EGAD50000001410

• Highly complex single-cell mixture of 5 individuals of high cell number

  Mixture of 5 unrelated individuals sequenced by 10x as a scATAC-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile using the De-goulash pipeline. The separation file is submitted as the processed file. The bam are submitted as unprocessed files.

  Dataset EGAD50000000480

• Fecal metagenomics and plasma metabolomics

  This dataset contains all fecal shotgun metagenomics and metabolomics of the study which investigated the effects of the probiotic strain Anaerobutyricum soehngenii. Shotgun data is from three different time points, baseline and two follow up. Metabolomics sets are pre and post intervention, both fasted and post prandially. Data on randomization and metformin use can be found in the analysis.

  Dataset EGAD50000000608

• Methylation Array data for: Three-dimensional patient-derived models of glioblastoma retain intra-tumoral heterogeneity

  3 sets of matched patient-derived-organoids (PDOs),  -neurospheres (PDNs), and parent glioblastoma tissue (9 samples total) underwent methylation array analysis. 200ng of each sample DNA extracted via a commercial kit (Qiagen) and loaded onto the Illumina EPIC v2.0 array. Data is provided as raw red and green .idat files.

  Dataset EGAD00010002745

• SNP Array data for: Three-dimensional patient-derived models of glioblastoma retain intra-tumoral heterogeneity

  4 sets of matched patient-derived-organoids (PDOs),  -neurospheres (PDNs), and parent glioblastoma tissue (12 samples total) underwent SNP array analysis. 200ng of each sample DNA extracted via a commercial kit (Qiagen) and loaded onto the Global Screening Array v2.0 array. Data is provided as raw red and green .idat files.

  Dataset EGAD00010002744

• Helleday_HRAS Project

  This experiment is looking at the mutational signatures generated by engineered HRAS mutations by using whole genome sequence generated on massively parallel next generation sequencers.

  Dataset EGAD00001000302

• Isotype-resolved sequencing of B cell receptor in measles virus infection (2017-09-13)

  Isotype-resolved sequencing of B cell receptor in measles virus infection 1) 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 please see http://www.sanger.ac.uk/datasharing/ This dataset contains all the data available for this study on 2017-09-13.

  Dataset EGAD00001003749

• RRBS sequencing data of ovarian cancer, breast cancer, control tissues, and white blood cell DNA.

  The dataset comprises 8 breast cancer, 11 ovarian cancer, 1 benign tumour, 18 normal tissue, 2 endometrium, and 23 white blood cell samples. Genome wide methylation analysis was performed by Reduced Representation Bisulfite Sequencing (RRBS) on Illumina HiSeq 2500. Data is provided as FASTQ files

  Dataset EGAD00001003822

• Whole exome profiling of spatial biopsies of high grade serous epithelial ovarian cancer patients

  This data set is comprised of data from seven distinct high grade serous epithelial ovarian cancer (HGS-EOC) partients, from whom multiple biopsies were taken at the time of surgery, from the ovary and from different locations in the peritoneal cavity. This data set contains 28 samples, sequenced with a whole exome sequencing approach.

  Dataset EGAD00001004154

• RNA-seq data from hypothalamic tissue from individuals with Prader-Willi syndrome and age-matched controls.

  RNA-seq data (bam files) from the hypothalamus of 4 individuals with Prader-Willi syndrome and 4 age-matched control individuals. Detailed information about the study design, case-control matching and RNA-seq data processing is provided in the accompanying publication [Bochukova et al (2018) Cell Reports].

  Dataset EGAD00001004034

• ENGAGE - Amendment "500 genes exon sequencing"

  The ENGAGE project is a FP7 funded EU project aiming to combine genetic and phenotype information from European population based cohorts. In this sub-project we aim to do whole exome sequencing of individuals selected from Health 2000 and FINRISK cohorts. Individuals have been selected based on their metabolic trait phenotypes

  Dataset EGAD00001000403

• Nimblegen

  The aim of this project is to identify rare variants in the 1q region associated with type 2 diabetes. To this end 651 case samples and 651 control samples from six populations have been pooled (pool sizes range from 27-33 individuals), and are being sequenced. The hybridization solution being used captures the exons and UTRs of genes in the 1q region.

  Dataset EGAD00001000424

• Whole Genome Sequencing of hiPS cells

  Human induced pluripotent stem (hiPS) cells hold great promise for regenerative medicine. Safety issues of use of hiPS cells however remain to be addressed. One of such issues is mutations derived from somatic donor cells and introduced during genome manipulation. We sequence whole genomes of hiPS cells and analyzed mutations. Our study brings hiPS cell technology one step closer to application to regenerative medicine.

  Dataset EGAD00001000362

• Whole genome sequencing

  The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC) is not well understood. We performed whole genome sequencing on primary and metastatic sites from highly clinically annotated HGSC samples. Samples were obtained pre-treatment based on a laparoscopic triage algorithm from patients who underwent R0 tumor debulking, or received neoadjuvant chemotherapy (NACT) with excellent or poor response.

  Dataset EGAD00001005240

• IBD Whole Genome Sequencing (2019-08-14)

  Whole genome sequences at 15X depth of patients with Inflammatory Bowel Disease. 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/ . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005254

• Predictor_ChemoNEAR_TNBC (2019-08-14)

  In this study a collection of core biopsies from breast cancer patients receiving neoadjuvant chemotherapy as part of the ChemoNEAR trial will be investigated. The study is intended to detect early acquired resistance in women with diagnosed breast carcinoma. Samples will undergo whole genome sequencing and analysis, including use of HR Predict. . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005255

• Sequencing data for personalized therapy design and endotype identification

  Whole exome sequencing of 15 DNA samples, and whole genome sequencing of 2 matched DNA samples. Whole exome sequencing is of RMS samples (both alveolar and embryonal) and from cell lines as well as patient samples. Patient samples are of pediatric RMS patients.

  Dataset EGAD00001005458

• Whole genome sequencing of glioblastoma reveals enrichment of non-coding constraint mutations in known and novel genes

  The dataset comprises of an aggregate level VCF (version 4.1), containing the somatic point and indel mutations found across the glioblastoma cohort (SweGBM-1, n=38 samples). The VCF file is in accordance with the HTS format specifications (https://samtools.github.io/hts-specs/).

  Dataset EGAD00001006084

• 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

• Whole exome sequencing of patient derived cell lines

  Whole exome sequencing of 3 patients derived cell lines and patient blood (N = 6 samples), performed using Agillent SureSelect All Exon V5 and Illumina HiSeq 4000. Data is in raw fastq format (N = 10 fastq pairs, 20 files total), as some samples were split between two lanes.

  Dataset EGAD00001007738

• Mucosal RNAseq data

  This is the RNAseq data from mucosal biopsies.

  Dataset EGAD00001008214

• Multiple Myeloma ChipSeq data on six histone modifications

  The data contained in this dataset is ChipSeq BAM files aligned to reference genome hg38. The ChipSeq was based on a combination of six histone modifications as follows: H3K4me1, H3K4me3, H3K9me3, H3K27me3, H3K27Ac and H3K36me3. The samples are patient-derived xenografts generated by passaging primary patient CD138+ selected cells through the SCID-rab myeloma mouse model.

  Dataset EGAD00001008353