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• Open_Targets_020_Epigenomes_of_Cell_Lines

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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 EGAS00001003136

• Open_Targets_020_Epigenomes_of_Cell_Lines

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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 EGAS00001003137

• Open_Targets_020_Epigenomes_of_Cell_Lines

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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 EGAS00001003139

• OMKar

  The whole genome karyotype refers to the sequence of large chromosomal segments that make up an individuals genotype. karyotype analysis, which includes descriptions of aneuploidies and other rearrangements is crucial for understanding genetic risk factors, for diagnosis, treatment decisions, and genetic counseling linked to constitutional disorders. The current karyotyping standard is based on microscopic examination of chromosomes, a complex process that requires high expertise and offers Mb scale resolution. Optical Genome Mapping (OGM) technology can identify large DNA lesions in a cost-effective manner. In this paper, we developed OMKar, a method that uses OGM data to create a virtual karyotype. OMKar processes Structural (SV) and Copy Number (CN) Variants as inputs and encodes them into a compact breakpoint graph. It recomputes copy numbers using Integer Linear Programming to maintain CN balance and then identifies constrained Eulerian paths representing entire donor chromosomes. In tests using 38 whole genome simulations of constitutional disorders, OMKar reconstructed the karyotype with 88% precision and 95% recall on SV concordance and 95% Jaccard score on CN concordance. We applied OMKar to 50 prenatal, 41 postnatal, and 63 parental samples from ten different sites. OMKar reconstructed the correct karyotype in 144 out of 154 samples, covering 25 of 25 aneuploidies, 32 of 32 balanced translocations, and 72 of 82 unbalanced variations. Detected constitutional disorders included Cri-du-chat, Wolf-Hirschhorn, Prader-Willi deletions, Down, and Turner syndromes. Importantly, it identified a plausible genetic mechanism for five cases of constitutional disorder that were not detected by other technologies. Together, these results demonstrate the robustness of OMKar for OGM-based karyotyping.

  Study EGAS00001008245

• 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

• Single-cell Transcriptome Profiling of Treatment-naïve and Post-treatment Colorectal Cancer: Insights into Putative Mechanisms of Chemoresistance

  Drug resistance remains a major clinical challenge in the treatment of colorectal cancer (CRC) with conventional chemotherapy. Investigation of cancer cells and tumor microenvironment (TME) following chemotherapy is critical for unraveling the mechanisms of resistance. In this study, we analyzed scRNA-Seq data from 56 CRCs including treatment-naïve tumors (25 microsatellite stable (MSS) tumors and 7 tumors with microsatellite instability (MSI)); and tumors treated with standard chemotherapy with the known response status (18 responders and 6 progressors). We observed in treatment-naïve MSS CRC that right-sided tumors are more immunogenic with higher numbers of B cells and CD8+ T memory effector cells than left-sided tumors. MSI CRC were even more immunogenic then MSS CRC and were characterized by elevated Tregs in their TME. In the post-treatment CRC there was a high prevalence of dendritic cells (DC) in the TME in the response group. The DC-derived signature was associated with better survival in a large CRC cohort from the TCGA. We also observed two fibroblast subtypes in CRC, one of which was enriched in progressors and was associated with poor survival in a CRC-TCGA cohort. Progressors also showed elevated exhausted CD8+ T memory cells and monocytes suggesting a pro-inflammatory TME. In tumor cells in progressor group we identified specific expression of chemo-protective markers MTRNR2L1 and CDX1; and their co-expression with stemness-related marker CD24. In summary, scRNA-Seq provides a valuable information for the discovery of prognostic markers, and reveals distinct features of CRC based on location, metastasis status, MSI status and treatment response status.

  Study EGAS50000000830

• Paediatric Hepatic International Tumour Trial (JPLT2: PHITT)

  Hepatoblastoma (HBL) is the most common primary liver tumor in children. Despite their diversity in histopathological phenotype and clinical outcome, the underlying molecular aberrations have not been fully understood. Here we describe a comprehensive landscape of genomic, epigenomic, and transcriptomic heterogeneity among the 163 cases of HBLs and transitional liver cell tumors (TLCTs) collected in the multicenter clinical trial JPLT-2. The total numbers of mutational events in HBLs are very few (0.52 SNVs/Mb on exonic regions) but show a positive correlation with the age of onset. While dysregulation of Wnt-pathway related genes was observed (somatic deletion or mutations of CTNNB1 and germline or somatic mutations of APC) in 83.6% of the HBL cases, TERT promoter mutations are mainly in the elderly HBLs (> 8 years old), meeting with the proposed criteria of TLCT. These TLCT cases are clustered in the hypermethylated epigenotype in promoter and enhancer regions. Copy number analyses also revealed recurrent 11p15.5 UPD/LOHs including the IGF2/H19 region (31.6%), focal deletions in 4q35 (15.8%) and focal amplifications in 2q24.3 (7.0%) predominantly in the child and infant HBLs. Motif enrichment analysis of the specific hypomethylated enhancers in these HBL subtypes suggests specific binding of ASCL2, the regulatory transcription factor for definitive endoderm and digestive systems. Transcriptome and histochemical analysis revealed that ASCL2 is upregulated not in HCC and TLCT but in child and infant HBL, suggesting their ?cell of origin? derived from the premature hepatoblast with high proliferative potential such as intestinal epithelial cells. Systematic molecular profiling of HBL will provide a fundamental understanding of hepatoblast carcinogenesis and clues for risk stratification.

  Study JGAS000236

• Systems genetics in human endothelial cells identifies non-coding variants modifying enhancers, expression, and complex disease traits

  Identification of causal variants and mechanisms underlying complex disease traits in humans requires strategies to locate and fine-map functional regulatory variants in disease-relevant cell types. To discover functional regulatory variants in primary aortic endothelial cells (ECs) from humans, we collected genetic, transcriptomic, and four epigenomic phenotypes in a population of 153 human donors representing individuals of both sexes and three major ancestries. We found thousands of EC eQTLs that were not present in GTEx at all ranges of effect sizes, indicating novel functional variants not observable from tissue data. We performed several epigenetic assays across 53 donors' EC to enable molecular QTL mapping, which included chromatin accessibility, histone modification, and transcription factor binding of proteins ERG and NF-kB/p65 in two activation states. We discovered over 3000 regulatory elements where cis-regulatory variants associated to significant differences in epigenetic marks. Co-localization with our eQTLs, TF motif mutations, and 3D confirmation capture data in ECs enabled our discovery of hundreds of high-confidence functional regulatory elements that perturb endothelial molecular phenotypes. Furthermore, this set of variants is enriched at GWAS loci for Coronary Artery disease and other disease traits, with some SNPs demonstrating pleiotropic effects. Together, our dataset and analytical approach provide the genetics and vascular biology communities with specific variants affecting EC biology and serves as a proof-of-principle for how to detect functional regulatory variants in human cells with relevance to complex traits.

  Study phs002057

• The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis

  In this study, we characterized 24 rheumatoid arthritis (RA) synovial tissue chromatin classes (i.e., cell states defined by chromatin accessibility) across 5 cell types (T, B/plasma, myeloid, stromal, and endothelial). We also investigated the transcription factors that may regulate these chromatin classes, their connections to transcriptional cell states in a proposed superstate model, and their interplay with RA pathology through associations with histological parameters and risk variants.As part of the Accelerating Medicines Partnership (AMP) network, we obtained 18 synovial tissue samples from 14 RA and 4 osteoarthritis (OA) patients for this study. Samples were collected from 7 clinical sites. We performed a 10x single cell ATAC-seq experiment on each sample.We further collected synovial tissue samples from 11 RA patients and 1 OA patient from 2 clinical sites; each sample was used for a 10x single cell multimodal ATAC and Gene Expression experiment.For additional support of the proposed superstate model, we also collected peripheral blood mononuclear cells (PBMCs) from 4 RA patients, sorted for 4 populations (CD4+CD127-CD25hi Tregs, CD4+CD127-CD25int Tregs, CD4+CD25-PD1+CXCR5- TPH, CD4+CD25-PD1+CXCR5+ TFH), tagged each population with a hashing antibody, and pooled populations for one multimodal sequencing run.The FASTQ files are available for controlled access via dbGaP. Additional data can be found on Synapse.The presence of pooled subjects inflates the automatically-generated subject count; the actual consented subject count for this data is 34.

  Study phs003417

• Next Generation Mendelian Genetics: Familial Hemophagocytic Lymphohistiocytosis

  The NHGRI Next Generation Mendelian Genetics project uses exome resequencing to identify variants in unsolved Mendelian diseases. Familial hemophagocytic lymphohistiocytosis (fHLH) is a serious immune disorder that results from defective cytotoxic lymphocyte function. Autosomal recessive mutations in PFP1, UNC13D, STX11, STBP2, or RAB27, and hemizygous mutations in SH2D1A or BIRC4, account for known causes of the disease, but 30-70% of patients in North America lack a known genetic etiology. This project was designed to identify additional genetic abnormalities from HLH patients. The exome sequences of four unrelated individuals with a diagnosis of HLH, but without mutations in genes known to cause disease, were obtained by massively parallel DNA sequencing.

  Study phs000537

• Genomics of Relapsed Small Cell Lung Cancer Progression

  Small cell lung cancer (SCLC) accounts for nearly 15% of all patients with lung cancer. Though the response to initial therapy is favorable in many patients, a majority of patients go on to develop recurrent disease which is very difficult to treat. The response rates to chemotherapy are very low and most patients succumb to relapsed SCLC within a few months. Virtually no progress has been made in the treatment of SCLC in the last three decades. In order to better understand the molecular alterations in relapsed SCLC, we have generated exome and RNA sequence from normal, primary tumor and relapse tissues of SCLC patients.

  Study phs001049

• Whole genome sequencing data of pediatric hypodiploid acute lymphoblastic leukemia

  Hypodiploid acute lymphoblastic leukemia (ALL) is a rare subtype of B-cell ALL characterized by chromosome number < 45 , encompassing near-haploid (24–29 chromosomes) and low-hypodiploid (30–39 chromosomes) subgroups. These subgroups display distinct genetic landscapes, including Ras and receptor tyrosine kinase pathway alterations in near-haploid ALL, and frequent IKZF2, RB1, and germline TP53 alterations in low-hypodiploid ALL. Clinically, hypodiploid ALL is associated with dismal prognosis, with 5-year overall survival rates often between 50-70% in children and markedly worse in adults. Despite advances in risk stratification and MRD-guided therapy, allogeneic stem cell transplantation remains the current standard recommendation for affected patients.

  Study EGAS50000001305

• Transcriptome analysis of a novel human iPSC-derived 3D cortical tissue model – 2D versus 3D co-culture comparison

  Single-cell RNA-seq analysis of human iPSC-derived microglia/astrocytes/neurons in a novel, human in vitro 3D cortical tissue model, as well as 2D co-cultures for comparison. Samples include distinct conditions (each as biological triplicates): - wild-type cells from 2D or 3D co-cultures after 3 months of culturing (2D_WT, 3D_WT) - knock-in cells from 2D or 3D co-cultures carrying three familial AD mutations in the APP gene (Swedish, Iberian, Arctic; introduced by CRISPR/Cas9-mediated knock-in) after 3 months of culturing (2D_KI, 3D_KI) - 2D and 3D KI cultures treated with Bumetanide (KI_bum) or BACE IV (KI_bace) inhibitor

  Study EGAS50000001392

• Exome-sequencing of two UFM individuals and their Fragile X family members.

  Fragile X syndrome (FXS) is a monogenic neurodevelopmental disease often caused by a CGG triplet expansion in the 5’UTR of the FMR1 gene, which results in DNA methylation of the FMR1 promoter and its transcriptional silencing. Exceptional healthy individuals named "unmethylated full mutation (UFM)" have been identified in the families of FX patients. They carry an expanded CGG repeat, but show normal FMR1 epigenetic configuration and expression. In this study we performed exome-sequencing of two UFM individuals and their family members to identify possible genetic mutations responsible for the escape of silencing in the unmethylated full mutation (UFM) phenotype.

  Study EGAS00001001737

• Cancer sequencing for somatic variant calling

  This dataset includes WES and RNAseq for 11 patients with metastatic melanoma, lung, kidney, and stomach cancers, enrolled in phase I clinical trials of TIL ACT (NCT03475134 &amp; NCT04643574). WES was performed on matched cancer and healthy tissues, whereas RNAseq was performed on cancer tissues, using Illumina HiSeq 2500/4000 and Illumina NextSeq 550 systems.

  Study EGAS00001007101

• Submitter Portal

  Submitter Portal The Submitter Portal does not support array submissions! Please refer to the array documentationAny new objects registered in the Submitter Portal will not be available for use in an array submission For further information please check our Submission FAQs, submission quickguide as well as submission terms! The metadata submission process can be difficult and time-consuming. For this reason, the EGA has developed the Submitter Portal, a tool that was created to offer a simplified and user-friendly method of registering metadata. Our portal provides features that are intended to make the input of metadata easier, ensuring that your data is registered correctly and effectively. Our page is divided into logical sections and includes a helpful video instruction to further assist you as you complete the submission process. With the Submitter Portal, you can rest assured that the submission of your data is in good hands. Submitter Portal Index Previous steps Access to Submitter Portal Start a Submission Take The Tour Tutorial Previous steps Create your EGA account To submit data, you first need to create your EGA user. Then, once your account has been verified by the Help Desk team, you will be able to request a submitter role and send the EGA Data Processing Agreement (DPA). In the case you already have an EGA account, or an ega-box (submission account), you can skip this step. Upload your files Please note that all your files must be encrypted using the Crypt4GH tool before upload them.As soon as you are assigned with a submitter role and added your public key to your profile, you will be able to connect to the EGA inbox and upload your files. Understand the EGA metadata schema It's crucial to comprehend the EGA metadata schema, a set of rules that specify how data is organised, described, and shared inside the EGA, in order to get the most out of this resource. Learn all about EGA metadata schema! Register your DAC and policy There are two objects in the EGA metadata schema that are registered in a separate portal. All DACs and policy objects are registered using the DAC Portal, a tool developed by EGA to help data controllers manage their data stored at the EGA. You can find relevant information in the DAC Portal Guide. Access to Submitter Portal 1. Request Submitter Role Once you have created your EGA user, request a Submitter Role and complete relevant information such as submission type and size. 2. Signature of the Data Processing Agreement The Data Processing Agreement (DPA) signed by CRG and EMBL-EBI (Joint Data Processors for the EGA) can be downloaded to the submitter for its signature. Further information related to the DPA can be in the Privacy Notice section. The DPA should be signed by a legal representative of the submitter with power of attorney/appointment duly authorised to sign contracts on behalf of the institution. The submitter will return a fully-executed copy of the DPA to us. Please note that due to the high volume of submissions to EGA the DPA is non-negotiable. Once you have completed all the information and attached the DPA signed, send your Submitter request and the EGA Helpdesk Team will validate it and send a confirmation to start submitting your metadata. Start a Submission The steps below will show you how to start a submission and are accompanied with a tutorial and the Take the tour of Submitter Portal. 1. Login Go to the Submitter Portal interface and log in using your EGA account credentials. 2. Create a submission The Submitter Portal interface will show you any already existing open submission. To start a new submission click on “Create a Submission”.In this phase you have the option to add any collaborator(s) as well as their permissions (“Read only” or “Read & Write”). If you want to invite all the collaborators from a previous submission, you can add them by selecting said submission.In the event that the submission has been closed, you will need to reopen it. To do this, you will need to modify one of the objects in the submission, for example, copy and paste the title. Once the submission is open, you can add a collaborator. Further information can be found in the Submission Tour 3. Create Study Click on add Study and complete the form with the relevant information. The fields with an asterisk (*) are mandatory. Further information can be found in the Submission Tour4. Create Sample Sample registration can be done either individually or in batch by using a template. Batch upload: download the template and complete it with information about the sequencing samples. Upload the samples.csv and the sample will be created.Add single sample: complete the mandatory fields with the metadata information of your sample.  Further information can be found in the Submission Tour5. Create Experiment Register an experiment with ​information about the sequencing methods, protocols and machines. Experiments generate the connection between samples and study. Further information can be found in the Submission Tour6. Create Run Samples, experiments and files are linked through runs. To register a run, you will be asked to select the appropriate experiment and the file format. Run registration can be done either individually or in batch by using a template. Batch upload: download the template and complete it with the sample - file linkage. Upload the run.csv and the runs will register.As the INBOX is a directory, bear in mind to include the file path (/). Example: /filename.c4gh. Add single run: select the file format, sample and experiment from the drop box. For re-using submitted samples, please use the EGA accession ID (EGANXXX). Please note that files must be uploaded in your inbox before linking your files and samples. Further information can be found in the Submission Tour7. Create Analysis Analysis should be only used for BAM/BAI or CRAM/CRAI pair, VCF and phenotype linkage to samples. The analysis is an EGA specific metadata object that links samples to files. This object also stores some metadata about your experiments, such as the experiment type, genome reference, or the platform used. **If only BAM or CRAM alignment files are submitted but not the original unaligned FASTQ files, then please make sure that the BAM or CRAM files also contain the unaligned reads. This is critical to enable primary re-analysis and re-alignment of the dataset using new tools or future genome assemblies.** Start by selecting the samples to be linked to the file, and then populate the required attribute fields. Please be aware of the existence of mandatory fields that must be populated.When populating the chromosome field (mandatory), please select the chromosomes from the checkbox. Please take in consideration that EGA allows for the re-use of any registered metadata. Therefore, a previously registered study or samples can be referenced for the analysis in the current data submission.Further information can be found in the Submission Tour 8. Create Dataset Dataset contains the collection of runs/analysis data files subjected to controlled access by being associated with a Policy. Complete the mandatory fields such as title, description, type and policy. Please, take in consideration that DAC and Policy must be registered in advance in the DAC Portal. Similar to other metadata objects, you can re-use previous runs or analyses, using their EGA accessions IDs (runs - EGAR, analyses - EGAZ). Further information can be found in the Submission Tour 9. Finalise submission Once the files are ingested please delete them from your SFTP INBOX before finalising your submission. This will prevent the files from reappearing in your Submitter Portal Inbox. Once you have completed your submission, click on the Finalise button, and schedule an estimated release date. Afterwards, your submission will be sent to Helpdesk for approval. Please note that once the Helpdesk has approved your submission, you will receive the identifiers for your data. See the Frequently Asked Questions (FAQ) for more information. 10. Update closed submission If you want to append more file to a closed submission, you will need to re-open the submission where the dataset was registered. Find the Submission: go to the Submitter Portal Menu -> Datasets section and find the submission id (EGA0XXX).  Reopen the submission where the dataset is located: to reopen a submission, you must edit any object within the submission. For example, you can copy and paste the title. Take The Tour The Submitter Portal Take The Tour is a visual guidance of all the steps described previously about how to start a submission. Tutorial In this tutorial we will show you how to use the Submitter Portal to register your metadata. Please note the video focuses on the run-based submission (for raw files - fastq - and aligned data - BAM/CRAM) and analysis-based submission (for your BAM/BAI pairs, variation -VCF - and phenotype files).

  Documentation submission/metadata/submission/sequencing-phenotype/submitter-portal

• Genome-Wide Association Study of Lung Cancer Susceptibility in Never-Smoking Women in Asia

  To learn about the etiology of lung cancer among never-smoking women in Asia, we formed the Female Lung Cancer Consortium in Asia (FLCCA), which includes studies of lung cancer in Eastern Asia and conducted a GWAS. We analyzed a total of 5510 lung cancer cases and 4544 controls and identified 3 novel loci (Lan et al., 2012). Of these study subjects, 4922 lung cancer cases and 3959 controls are available for posting. Lan et al.., Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia. Nat Genet. 2012 Dec;44(12):1330-5. doi: 10.1038/ng.2456. Epub 2012 Nov 11. PubMed PMID: 23143601.

  Study phs000716

• Study on the Genetics of Alcoholism (COGA): African American Family GWAS

  COGA is a family study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This project has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and after securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through an alcoholic proband. Assessment involved a detailed personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results are included on a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3. As part of COGA, a set of informative African American families were selected to have Genome-Wide Association data obtained within families. Genotyping was performed using the Illumina Omni2.5_080814_1 chip to genotype 3,438 subjects selected from densely affected families. Genotyping was performed at CIDR. This sample complements a set of densely affected European American families previously made available under dbGaP study accession phs000763. In addition, exome sequencing data on a subset of individuals with GWAS were added in version 2.For version 3, a subset had 30X Whole Genome Sequencing (WGS) as part of the NIDA Sequencing Initiative. The subset contained two distinct sets: Sibling pairs where one sibling had at least two dependence diagnoses in the set (alcohol, cannabis, cocaine, and opioid), and the other had none, and non-related Case-Control pairs matched for age and ethnicity where the cases had alcohol and at least 2 other dependence diagnoses and controls had none. After sequencing, some sibling pairs are re-classified as half siblings, Three VCF files (small variants, structural variants, and copy number variations) are provided. Additional substance abuse variables are made available in version 3. We note that the full sample data are deposited in four dbGaP submissions and the sequenced samples are split across all four: CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study (phs000125). GWAS data on cases (primarily probands) and controls drawn from the families. Families with highest density of alcohol dependence and/or extreme event-related oscillation data (phs000763). GWAS data on 119 extended families of European descent are available here, along with extensive documentation. Study on the Genetics of Alcoholism (COGA): African American Family GWAS (phs000976). GWAS data on all available COGA families of African descent are available. COGA: Smokescreen GWAS (phs001208). GWAS data on all remaining COGA DNA samples, primarily of other racial background, were genotyped on the Smoke Screen array. A listing of all sequenced pairs is provided in the documentation to facilitate the merging of these samples.

  Study phs000976

• Genome-Wide Approach to Measure Variant-Based Heritability of Drug Outcome Phenotypes

  Current pharmacogenetic approaches often use a few large-effect alleles to predict drug outcomes. However, many drug outcome phenotypes are determined by complex pathways that may be influenced by common single-nucleotide variants (SNVs) across the genome. We ascertained how much variation in drug response is explained by common SNVs for pharmacokinetic (drug levels) and pharmacodynamic phenotypes (highest creatinine) for 4 drugs: vancomycin, gentamicin, cyclosporine and tacrolimus.

  Study phs002506

• Non_Hodgkin_lymphoma_project___mutational_burden_of_chemotherapy_in_normal_blood

  his study aims to further investigate the mutational burden induced by chemotherapy in the normal stem and progenitor cell of individuals treated for Non -hodgkins lymphoma. Single cell derived progenitor colonies have been grown and DNA extracted. 5-10 colonies from a number of individuals exposed to chemotherapeutic regimens for lymphoma will undergo whole genome sequencing to address the question of the extent of mutational impact of these different regimens.

  Study EGAS00001006733

• Project for Development of Innovative Research on Cancer Therapeutics;Shuttle system between petient-derived xenograft and ex vivo culture for innovative platform of evaluating drug sensitivity.

  We developed CTOS (cancer tissue-originated spheroid) panel covering diversity among patients for colorectal cancer, lung cancer and cervical small cell carcinoma. We then carried out exome sequence analysis of tumor tissues, cell lines and CTOS derived from patients to validate qualitative changes in preparation, culture, cell line, transplantation and passage of CTOS pathologically, biochemically, molecular biologically.

  Study JGAS000089

• High-depth whole genome sequencing of paired ductal carcinoma in-situ (DCIS) and germline control samples from 51 individuals.

  Deposited here are whole-genome sequencing data for 51 paired breast cancer DCIS and matched-normal samples taken from the same individual. Average sequence depth is 110x for DCIS samples and 39x for matched-normals. Matched-normals are from blood (n=14) or adjacent normal breast (n=37). Sequencing was performed on Illumina HIseqX (n=70) or Illumina Novoseq (n=32). They are a part of a broader project that uses high-depth WGS to investigate the somatic mutation genomic landscape of DCIS in order to uncover biological insights into breast cancer progression as well as possible methods to stratify DCIS patients for individualised therapy or disease monitoring.

  Dataset EGAD50000002071

• Genomewide detection of cytosine methylation by single molecule real-time sequencing

  5-methylcytosine (5mC) is an important type of epigenetic modification. In this study, we enhanced 5mC detection using SMRT sequencing by holistically analyzing kinetic signals of a DNA polymerase and sequence context for every base within a measurement window. We employed a convolutional neural network to train a methylation classification model. This methodology has provided a system for simultaneous genome-wide genetic and epigenetic analyses. 

  Study EGAS00001004642

• Exome and Whole-Genome Sequencing of Central African Hunter-Gatherers and Agriculturalists

  To investigate how human populations have adapted to the equatorial rainforest, we generated 266 high-coverage exomes, analyzed in combination with 300 published exomes, from 14 populations of African rainforest hunter-gatherers and farmers, together with 40 newly-generated, low-coverage genomes. Genome scans for positive selection and signatures of polygenic selection provide evidence for local adaptation of hunter-gatherers to the African rainforest.

  Study EGAS00001003722

• The Causes of Clonal Blood Cell Disorders Study - SCOR (2018-04-19)

  We will take a bone marrow aspirate and peripheral blood samples from a healthy patient aged around 60, and use flow cytometry to isolate 100 HSCs, 50 MEPs, and 50 GMPs. We will grow these up into colonies, then whole genome sequence each colony. Somatic mutations will act as a unique barcode for each clone. We will then design a panel for targeted resequencing of the mutations that we find. It will then be possible to look for these mutations in the peripheral blood over several years, to see the dynamics of how HSCs contribute to the peripheral blood in health. This dataset contains all the data available for this study on 2018-04-19.

  Dataset EGAD00001004086