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• EGAS00001001311_MalariaGEN_GWAS_summary_statistics_2015

  Summary statistics for Malaria Genomic Epidemiology Network, "A novel locus of resistance to severe malaria in a region of ancient balancing selection", Nature (2015)

  Dataset EGAD00010001081

• Homozygous IL37 mutation leads to infantile inflammatory bowel disease

  Whole-exome sequencing of a trio (parents and offspring) reveals IL37 mutation leads to infantile IBD.

  Study phs002040

• WTCCC2 Schizophrenia study

  A WTCCC2 project genome-wide case-control association study for schizophrenia (SP) in individuals from Ireland.

  Study EGAS00000000118

• WTCCC2 Ischaemic Stroke study

  Genome-wide association study identifies a variant in HDAC9 associated with large vessel ischemic stroke

  Study EGAS00000000103

• CIRCLE-seq of PDAC PDO

  CIRCLE-seq was performed on a PDAC PDO to validate the presence and the structure of ecDNAs

  Study EGAS50000000194

• Maternally-Inherited SPTBN1 Mutation

  The dataset consists of exome sequencing data from a male patient with a maternally inherited SPTBN1 mutation. The clinical presentations include autism spectrum disorder, cognitive delay, feeding difficulties, gastrointestinal manifestations, and musculoskeletal abnormalities.

  Dataset EGAD50000001726

• Observational study on the immune responses acquired by COVID-19 convalescent individuals

  We performed whole exome sequencing and microarray genotyping analysis of rare disease A two patients. .....

  Study JGAS000563

• TSG_knock_out_in_hiPSCs

  We will perform RNAseq to evaluate the effects of the loss of a list of TSGs on the transcriptome.

  Study EGAS00001002262

• Characterizing the tumor immune microenvironment of ependymomas using targeted gene expression profiles and RNA-sequencing the pros and cons

  RNA sequencing data of a collection of 6 pediatric ependymoma cases

  Study EGAS00001006535

• WGS and RNA-Seq data from a GBM patient PT-FB6711

  WGS and RNA-Seq data from a GBM patient PT-FB6711

  Dataset EGAD00001004235

• Melanoma C32 ENU resistance to Combination Therapy

  This study involves mutagenizing C32, a melanoma cell line, with ENU to identify those mutations which engender resistance to a targeted treatment.

  Dataset EGAD00001002234

• Bulk exome sequencing of primary GBM - SF 10282

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10282

  Dataset EGAD00001002275

• Melanoma C32 ENU Resistance to Single Agent Therapy

  This study involves mutagenizing C32, a melanoma cell line, with ENU to identify those mutations which engender resistance to a targeted treatment.

  Dataset EGAD00001003239

• Genome and transcriptome sequence data from a NUT midline carcinoma tumor patient

  Genome and transcriptome sequence data from a NUT midline carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015289

• Genome and transcriptome sequence data from a minimally invasive adenocarcinoma tumor patient

  Genome and transcriptome sequence data from a minimally invasive adenocarcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015297

• Germline DNMT3A mutation in familial acute myeloid leukemia

  Longitudinal and germline exome sequencing analysis of a mother and son pair who both developed adult-onset diploid AML identified a novel germline missense mutation DNMT3A p.P709S.

  Dataset EGAD00001006248

• Genome and transcriptome sequence data from a neurofibromatosis type 1 tumor patient

  Genome and transcriptome sequence data from a neurofibromatosis type 1 patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015301

• Bulk exome sequencing of primary GBM - SF 10345

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10345

  Dataset EGAD00001002273

• Genome and transcriptome sequence data from a metastatic alveolar rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a metastatic alveolar rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015295

• WGS and RNA-Seq data from a GBM patient PT-SO0258

  WGS and RNA-Seq data from a GBM patient PT-SO0258

  Dataset EGAD00001004261

• Severe acne GWAS meta-analysis

  Summary statistics of a GWAS meta-analysis for severe acne. A total of 7,441,713 genotyped and imputed variants were used for 5,602 European severe acne cases and 21,120 matched population controls.

  Dataset EGAD00001004419

• WCDT Hi-C assays performed mCRPC biopsies - Part 2

  13 paired FASTQ files from a Hi-C assay performed on mCRPC tumors. Sequencing was performed using 150nt paired reads generated by a Novaseq 6000 instrument.

  Dataset EGAD00001009417

• Genome and transcriptome sequence data from a acute lymphoblastic leukemia tumor patient

  Genome and transcriptome sequence data from a acute lymphoblastic leukemia patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015285

• WGS and RNA-Seq data from a GBM patient PT-BM772

  WGS and RNA-Seq data from a GBM patient PT-BM772

  Dataset EGAD00001004229

• Genome and transcriptome sequence data from a relapsed wilms tumor tumor patient

  Genome and transcriptome sequence data from a relapsed Wilms tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015304

• Genome and transcriptome sequence data from a papillary thyroid carcinoma tumor patient

  Genome and transcriptome sequence data from a papillary thyroid carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015303

• Genome and transcriptome sequence data from a malignant rhabdoid tumour tumor patient

  Genome and transcriptome sequence data from a malignant rhabdoid tumour patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015310

• Genome and transcriptome sequence data from a recurrence nasopharyngeal rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a recurrence nasopharyngeal rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015314

• Genome and transcriptome sequence data from a pineal parenchymal tumor tumor patient

  Genome and transcriptome sequence data from a pineal parenchymal tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015317

• Genome and transcriptome sequence data from a choroid plexus carcinoma tumor patient

  Genome and transcriptome sequence data from a choroid plexus carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015321

• Genome and transcriptome sequence data from a malignant rhabdoid tumor tumor patient

  Genome and transcriptome sequence data from a malignant rhabdoid tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015323

• Genome and transcriptome sequence data from a NUT midline carcinoma tumor patient

  Genome and transcriptome sequence data from a NUT midline carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015325

• WGS and RNA-Seq data from a GBM patient PT-RL5404

  WGS and RNA-Seq data from a GBM patient PT-RL5404

  Dataset EGAD00001004257

• Genome and transcriptome sequence data from a acute myeloid leukemia tumor patient

  Genome and transcriptome sequence data from a acute myeloid leukemia patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015331

• Genome and transcriptome sequence data from a fibrovascular brain tumor tumor patient

  Genome and transcriptome sequence data from a fibrovascular brain tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015271

• Genome and transcriptome sequence data from a papillary thyroid carcinoma tumor patient

  Genome and transcriptome sequence data from a papillary thyroid carcinoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015276

• Genome and transcriptome sequence data from a multifocal glioblastoma multiforme tumor patient

  Genome and transcriptome sequence data from a multifocal glioblastoma multiforme patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015281

• 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

• Exome sequencing of early and late passage Patient Derived Xenogratf Tumoroids with matched Patient Derived Xenogratfs and matched normal liver

  The breadth and depth at which cancer models are interrogated contribute to successful translation of drug discovery efforts to the clinic. In colorectal cancer (CRC), model availability is limited by a dearth of large-scale collections of patient-derived xenografts (PDXs) and paired tumoroids from metastatic disease, the setting where experimental therapies are typically tested. XENTURION is a unique open-science resource that combines a platform of 129 PDX models and a sister platform of 129 matched PDX-derived tumoroids (PDXTs) from patients with metastatic CRC, with accompanying multidimensional molecular and therapeutic characterization. In this specific dataset we focused our attention on early (passage 3) and late (passage 8-12) PDXTs with their matched PDXs and normal liver

  Dataset EGAD50000000266

• Large Scale Meta-analysis Characterizes Genetic Architecture for Common Psoriasis-associated Variants

  The genotypes obtained from the Affymetrix Biobank Plus array constituted one of eight Caucasian datasets used in a large genome-wide meta-analysis of the association of psoriasis cases versus unaffected controls. With a combined effective sample size of > 39,000 individuals, this study identified 16 new psoriasis loci achieving genome-wide significance, increasing the total number of identified psoriasis loci for European-ancestry populations to 63.

  Study phs001306

• Clinical and Genetic Analysis of Retinopathy of Prematurity (ROP)

  Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide and is treated based on the presence of symptoms of "plus disease", a dilation and tortuosity of retinal vessels. This project aims to identify the genetic and clinical underpinnings of the disease by comparing the germline variants of ~1,400 premature babies. 100 samples have been selected for WES and all have been genotyped.

  Study phs002047

• Cellular Heterogeneity in Early Human Development at Stage CS16

  In this study, we applied 10x Genomics Multiome assays for single-nucleus profiling of gene expression and chromatin accessibility simultaneously to a Carnegie stage 16 (37-42 days) specimen. These data can be used to identify and characterize diverse human cell types and annotate them with respect to marker genes, expression, and regulatory modules. These data comprise a rich resource for the exploration of human biology.

  Study phs003532

• Single-Cell DNA Methylation Profiling with sciMETv2

  In this study we developed a high-throughput single-cell DNA methylation analysis technology, sciMETv2. This technique is rapid, cost-effective, and robust, enabling large-scale single-cell methylome dataset generation. We demonstrate this technology on human middle frontal gyrus, where we identified major cell types. We additionally performed target enrichment using sciMET-cap to enable a reduction in sequencing costs per cell while achieving comparable cell type identification.

  Study phs003091

• Single Cell Analysis of Healthy and Diseased Temporomandibular Joint Synovial Fluid

  Temporomandibular joint disorders (TMJDs) are a set of complex, poorly understood painful conditions that negatively affect many children and adults in the US. In this study, we establish a protocol to utilize irrigation fluid from TMJ arthrocentesis to perform single-cell RNA sequencing on cells contained in TMJ synovial fluid. Our results should help investigators better understand these conditions and identify novel therapeutic options.

  Study phs003645

• ScRNA sequencing and snp-array genotyping of peripheral immune cells in Type 1 diabetes mellitus (T1DM)

  Type 1 diabetes mellitus (T1DM) is a prototypic endocrine autoimmune disease resulting from an immune-mediated destruction of pancreatic insulin-secreting beta-cells. A comprehensive immune cell phenotype evaluation in T1DM has not been performed thus far at the single. In this cross-sectional analysis, we generated a single-cell transcriptomic dataset of peripheral blood mononuclear cells (PBMCs) from 46 manifest T1DM (Stage 3) cases and 31 matched controls.Our study reveals a surprisingly strong systemic dimension at the level of immune cell network in T1DM, defines disease-relevant molecular subtypes and has the potential to guide non-invasive test development and patient stratification.

  Dataset EGAD50000000345

• Brazilian Thyroid WES

  Medullary thyroid cancer (MTC) is a rare malignant tumor that arises from parafollicular cells. Approximately 8% of thyroid cancer cases are MTC, and about 25% of these have a hereditary component. Incorporating molecular parameters into tumor classification is important. Besides, the presence of pathogenic germline variants can impact directly on cancer prevention. Thus, the aim of this study was to perform whole exome sequencing (WES) on a consecutive series of hereditary RET wild-type MTC patients to identify genetic variants that may be involved in the carcinogenesis of this tumor. WES was performed on 28 patients negative for germline RET pathogenic variants using the NovaSeq 6000 platform. Variant classification followed American College of Medical Genetics and Genomics guidelines.Our study represents a significant advancement in gene discovery for MTC genetics.

  Dataset EGAD50000000086

• cfDNA methylation profiling on longitudinally collected blood plasma of patients with esophageal adenocarcinoma

  Esophageal adenocarcinoma (EAC) is an aggressive cancer characterized by a high risk of relapse post-surgery. Analyzing cell-free DNA (cfDNA) from blood plasma emerges as a promising avenue for therapy response monitoring. This study aims to evaluate the cost-effective and genome-wide cell-free reduced representation bisulfite sequencing (cfRRBS) method combined with computational deconvolution for effective disease monitoring in EAC patients.

  Study EGAS50000000514

• RNASeq from PPGL-derived PC12 cell lines cultivated in normoxia and hypoxia conditions.

  PC12 cells derived from rat PPGL were then either continued cultivated in the same normoxia condition (37˚C, 5% CO2 and 21% O2 balanced with N2) or were placed in a hypoxic incubator, that maintained a constant hypoxic environment (37˚C, 5% CO2 and 1% O2 balanced with N2), for different short (12h, 24h, and 48h) or prolonged time (36 days, approximately 860h).

  Study EGAS50000000814

• ChIP-seq data in MSC_Pat and EWIma1 (FLI1 & H3K27ac)

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic and epigenetic hallmarks of EwS.

  Study EGAS50000001172

• RNA-seq data in hMPC, MSC_Pat and EWIma

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic and epigenetic hallmarks of EwS.

  Study EGAS50000001173

• Viral evasion Strategy for Generating Hypoimmunogenic hiPSC Lines

  Mismatches in HLA haplotypes between donors and recipients significantly increase the risk of graft failure due to immune rejection. To address these limitations, we introduced a cytomegalovirus-derived US2 encoding sequence into the AAVS1 safe-harbor locus of a human induced pluripotent stem cell (hiPSC) line. US2 expression in iPSC abolished HLA-A2 alloreactive T-cell activation without increasing NK cell degranulation, indicating preserved inhibitory signaling.

  Study EGAS50000001618

• Meta-analysis of Genome-Wide-Association Sudies for plasma Factor XI

  Coagulation factor XI (FXI) has become increasingly interesting for its role in pathogenesis of thrombosis. We performed a genome-wide association study (GWAS) for plasma FXI levels, using novel data imputed to the 1000 Genomes reference panel. Individual GWAS analyses, including a total of 16,169 European individuals from the ARIC, GHS, MARTHA and PROCARDIS studies, were meta-analyzed, and results are presented here.

  Study EGAS00001002123

• Novel manifestations of immune dysregulation and granule defects in gray platelet syndrome

  Gray Platelet Syndrome (GPS) is a rare recessive bleeding disorder resulting from biallelic variants in NBEAL2. As part of a comprehensive evaluation of the phenotype and genotype in 47 patients with GPS, four different blood cell-types (platelets, neutrophils, monocytes, and CD4-lymphocytes) were evaluated using bulk RNA-seq in five patients and five controls. These data are deposited in this archive in FASTQ format.

  Study EGAS00001004216

• RNAseq_of_ribosomal_footprints

  Cancer genes can affect ribosomal RNA processing and this can underlie their essentiality to cells, making them cell-essential in the same way as ribosomal genes themselves. We want to confirm this, in order to understand the results of our CRISPR drop-out screens.NOTE FROM BESPOKE TEAM: Run a single read 1 (forward read) of 30 bases, then an index 1 read as normal. This would fit a 50cycle kit

  Study EGAS00001001591

• Mutational profiling of LUAD in young never-smokers

  NSCLC has been recognized as a highly heterogeneous disease with phenotypic and genotypic diversity in each subgroup. In this study, we conducted whole genome sequencing (WGS) to characterize the genomic alterations of 36 never-smoker Chinese patients with lung adenocarcinomas (LUADs). Our study provides a detailed mutational portrait of LUADs occurring in young never-smokers and gives insights into the molecular pathogenesis of this NSCLC subgroup

  Study EGAS00001002773

• Study_to_investigate_the_prevalence__of_leukaemic_mutations_in_whole_blood_DNA_in_a_cohort_of_blood_donors

  The aim of this study is to ascertain whether leukaemic mutations exist within the blood of people with otherwise normal haematopoeisis. To satisfy this aim we plan to look for 7 known leukaemic mutations in the whole blood DNA of a large cohort of blood donors who have normal haematopoesis. Genomic regions around mutational sites have been amplified using a 2 step PCR process which involves barcoding of individual patients

  Study EGAS00001000814

• Genetic characterization patients affected by Cancer of Unknown Primary

  The genetic changes sustaining the development of human Cancers of Unknown Primary (CUP) remain elusive. Here we report the genomic profiling of 14 rigorously selected CUP samples. Although no specific recurring mutation in known driver genes was found, a comparison of the mutational landscape of CUPs with that of most other human tumor types revealed a consistent change in diverse genes belonging to the axon guidance KEGG pathway.

  Study EGAS00001006621

• ATAC_SEQ_MAIN___PHASE_1

  This is a study to test ATAC-seq protocols. CD4+ and CD8+ cells have been obtained from three different anatomical compartments. We aim to assay open-chromatin regions across these cells and perform comparative analyses.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 EGAS00001000947

• QSEA – modelling of genome-wide DNA methylation from sequencing enrichment experiments

  We describe a new method, QSEA, for analyzing methylation enrichment data. We generated a benchmark experiment consisting of MeDIP-seq enrichment data, targeted BS-seq validation data, and RNA-seq data on five pairs of tumor and adjacent normal samples of non-small cell lung cancer patients. Details of the method and its performance on the data have been described in Lienhard et al. (2016).

  Study EGAS00001001822

• Prospective high-throughput genome profiling in advanced cancers:

  Genomics-based tumor profiling in advanced cancers (aC) was recently demonstrated as feasible in clinical practice. After the prospective pilot PANDORA study done on advanced breast cancers, we conducted a prospective monocenter clinical trial called PERMED01 to evaluate the number patients with locally advanced or metastatic cancer for whom identification of molecular alterations in tumor samples could lead to the delivery of a targeted therapy

  Study EGAS00001004554

• 46 patients primary malignant glioma cohort in Chinese population

  We recruited 46 Chinese patients with primary malignant glioma. All the patients were analyzed with whole-exome sequencing (WES) and 27 of them were analyzed with RNA-seq. We compared the molecular features between patients in different WHO grades. We used six-month progression-free survival (PFS6) status to group glioblastoma (GBM) patients to a good and a poor survival compared two groups genomic profiles.

  Study EGAS00001005583

• Genomic abnormalities of TP53 define distinct risk groups of paediatric B-cell non-Hodgkin lymphoma

  TP53 alterations are associated with adverse outcome in many malignancies; however, whilst common in paediatric B-NHL, their utility as a risk classifier in this setting is unknown. We evaluated the clinical significance of TP53 abnormalities (mutations, deletion and/or copy number neutral loss of heterozygosity) in a large UK paediatric B-NHL cohort (n=95) and determined their impact on survival.

  Study EGAS00001005617

• Multiomics Characterization of Low-grade Serous Ovarian Carcinoma

  Low-grade serous ovarian carcinoma (LGSOC) is a rare tumor subtype with high case fatality rates. There is a pressing need to develop effective treatments using newly available preclinical models for therapeutic discovery and drug evaluation. In this study, we use multiomics integration of whole exome sequencing, RNA sequencing, and mass spectrometry-based proteomics on fourteen LGSOC patient derived cell lines to elucidate novel biomarkers and therapeutic vulnerabilities.

  Study EGAS00001004724

• 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

• Identifying autosomal recessive mutations causing neurological disorders

  The objective of this study is to resequence of targeted intervals containing autosomal recessive variants causing neurological disorders in consanguineous pedigrees. Using homozygosity mapping, three intervals of very different sizes have previously been unambiguously mapped for three different neurological diseases: 2.4Mb, 8Mb and 14.3Mb in size, for Microlissencephaly, Severe Mental Retardation and Complicated hereditary spastic paraplegia respectively. This study is a pilot to assess how well custom targeted resequencing performs across a broad size range of intervals. The study design is to use a different custom capture probe set for each interval, pulldown from a single patient from each family, and sequence 1 lane using Illumina paired-reads for each sample. Candidate variants will be followed up in the families themselves, and in patients with similar phenotypes from outbred populations

  Dataset EGAD00001000340

• Acute Respiratory Distress Network (ARDSNet) Study 04 Assessment of Low Tidal Volume and Elevated End-Expiratory Volume to Obviate Lung Injury (ALVEOLI-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. BiospecimensAccess to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-ALVEOLI include Plasma and DNA. Please note that use of biospecimens in genetic research is subject to a tiered consent. Available Data Outcome data regarding organ failure free days are not available. Objectives The ARDS Network is a consortium of clinical centers and a coordinating center to design and test novel therapies for the treatment of Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS). The ARDS Network 01/03 trials included an investigation of the efficacy and safety of Ketoconazole and Respiratory Management in the treatment of ALI and ARDS (KARMA). The Ketoconazole arm of the KARMA study was later stopped due to an inability to show efficacy. Participants continued to be randomized to the respiratory management arms of the study (ARMA), which compared two ventilator strategies: a tidal volume of 6 mL/kg versus 12 mL/kg. The LARMA phase of the study investigated the efficacy of Lisofylline and Respiratory Management. The objective of the ALVEOLI study was to compare clinical outcomes of participants with ALI and ARDS treated with a higher end-expiratory lung volume/lower FiO2 versus a lower end-expiratory lung volume/higher FiO2 ventilation strategy. The ALVEOLI study tested the hypothesis that mortality from ALI and ARDS would be reduced with a mechanical ventilation strategy designed to prevent lung injury from repeated collapse of bronchioles and alveoli at end-expiration. Background Most participants requiring mechanical ventilation for ALI and ARDS receive positive end-expiratory pressure (PEEP) of 5 to 12 cm of water. Higher PEEP levels may improve oxygenation and reduce ventilator-induced lung injury but may also cause circulatory depression and lung injury from overdistention. PEEP levels higher than traditional levels may reduce ventilator-induced lung injury by decreasing the proportion of nonaerated lung and higher PEEP levels may allow arterial-oxygenation goals to be met at a lower level of inspired oxygen (FiO2). Participants A total of 550 participants were randomized to receive mechanical ventilation with either lower or higher PEEP levels, which were set according to different tables of predetermined combinations of PEEP and fraction of inspired oxygen. Conclusions Participants with acute lung injury and ARDS who receive mechanical ventilation with a tidal-volume goal of 6 ml per kilogram of predicted body weight and an end-inspiratory plateau-pressure limit of 30 cm of water, clinical outcomes were statistically similar whether lower or higher PEEP levels are used. (Brower, et al., 1004; PMID: 15269312).

  Study phs003714

• The University of Tasmania MS Stem Data Access Committee

  Data access committee for data related to the Multiple Sclerosis Stem (MS Stem) biobank. A biobank of human induced pluripotent stem cell (iPSC) lines. MS Stem is a biobank of human induced pluripotent stem cell (iPSC) lines, derived from people living with and without multiple sclerosis. The biobank provides researchers with fully characterised iPSC lines from well phenotyped and genotyped individuals. This provides a unique opportunity to research the pathophysiology of MS in human cell models or conduct preclinical screening of putative therapeutics.

  Dac EGAC50000000120

• A fast, affordable and minimally-invasive diagnostic test for Cancer of Unknown Primary (CUP) using DNA methylation profiling

  CUP diagnosis on FFPE tissue and liquid biopsies (blood, pleural and peritoneal effusions) using cfRRBS (cell-free reduced representation bisulfite sequencing), a technique that allows for identification of the methylation profile starting from minimal amounts of highly fragmented DNA.

  Study EGAS50000000257

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from Cardiff, UK (O'Donovan)

  This research project was a collaboration between Cardiff University, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of Bipolar case/control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina HiSeqX machines producing CRAM files.

  Dataset EGAD50000000887

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from the Netherlands (Ophoff)

  This research project was a collaboration between UCLA and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 1,965 Bipolar case/control samples from collaborators in the Netherlands and UCLA. Genomic DNA from each sample was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina HiSeqX machines producing CRAM files.

  Dataset EGAD50000000983

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from London, UK

  This research project was a collaboration between University College London, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 4,627 Bipolar case/control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina HiSeqX machines producing CRAM files.

  Dataset EGAD50000000950

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from Stockholm, Sweden (Pedersen)

  This research project was a collaboration between the Karolinska Institute BioBank and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 4,765 control samples from collaborators in Sweden. Genomic DNA from each samples was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina HiSeqX machines producing CRAM files.

  Dataset EGAD50000001026

• CRISPRi/a of GATA2/NR4A2/SOX17 upon spontaneous iPSC differentiation

  Arrayed CRISPR screens, modulating the expression of key lineage TFs GATA2 (mesoderm), SOX17 (endoderm), and NR4A2 (neuroectoderm) in hiPSCs via CRISPR interference or activation over a time-course of spontaneous differentiation (days cultured in vitro: 0, 4, 12, and 18).

  Study EGAS50000000819

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from Cardiff, UK (Owen)

  This research project was a collaboration between Cardiff University, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 1,105 Bipolar case/control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina HiSeqX machines producing CRAM files.

  Dataset EGAD50000001212

• A living biobank of patient-derived ductal carcinoma in situ Mouse-INtraDuctal xenografts identifies factors associated with risk of invasive progression

  Create a living biobank of patient-derived ductal carcinoma in situ (DCIS) Mouse-INtraDuctal (MIND) xenografts to find factors explaining invasive growth. Samples exist of both primary and pdx samples. Invasive growth was scored in the pdx.

  Study EGAS00001006554

• DNA-seq FASTQ files from 16 carriers of the BMPR2 p.Arg491Gln mutation in a family affected by HPAH

  Paired-end DNA-seq FASTQ files from 16 carriers of the BMPR2 p.Arg491Gln mutation in a family affected by hereditary pulmonary arterial hypertension (HPAH). Whole genome sequencing of these samples was performed in an Illumina HiSeq 4000 instrument. Libraries were prepared using the Fisher PE Kit (Kapa Biosystems). Each sample was multiplexed across flowcells and lanes, leading to a total number of 86 FASTQ files.

  Dataset EGAD00001005756

• Spatial RNA-sequencing of metastatic melanoma

  We performed RNA sequencing of 48 different regions sub-sampled from a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor. RNAseq was performed on samples with a minimum RNA integrity number (RIN) of 5.5 except for two cases (6A10 and 8A3) with RINs greater than 3. A minimum of 700ng of RNA were required for all samples undergoing RNAseq. Paired-end transcriptome reads were aligned using TopHat2, to the UCSC hg19 reference genome.

  Dataset EGAD00001005820

• De novo mutations in cell-free foetal DNA (cffDNA)

  This project is to develop and validate a method to detect de novo mutations in a foetal genome through deep sequencing of cell-free DNA from the plasma of pregnant women. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000596

• Study to investigate the prevalence of leukaemic mutations in whole blood DNA in a cohort of blood donors

  The aim of this study is to ascertain whether leukaemic mutations exist within the blood of people with otherwise normal haematopoeisis. To satisfy this aim we plan to look for 7 known leukaemic mutations in the whole blood DNA of a large cohort of blood donors who have normal haematopoesis. Genomic regions around mutational sites have been amplified using a 2 step PCR process which involves barcoding of individual patients

  Dataset EGAD00001001319

• Whole genome sequencing of a Grem1 mutant human tumour

  The BMP antagonist Grem1 has been shown to be associated with a rare human polyposis syndrome (HMPS). We have shown that there is a 40KB duplication on chrom 15 found in some patients with HMPS. Traditional serrated adenomas (rare sporadic polyps) share some morphological features with HMPS polyps and it has long been hypothesised that they are the sporadic version of HMPS polyps. We have obtained of one of these lesions and in this project we aim to characterise this tumour.

  Dataset EGAD00001002182

• 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

• Prematurity and Respiratory Outcome Program: Clinical Research Center Study of Functional and Lymphocytic Markers of Respiratory Morbidity in Hyperoxic Preemies

  Approximately 550,000 babies born prematurely each year in the United States suffer from birth at a time in development when the respiratory tract and immune system would normally be protected and maintained in a naïve state. This project is a component of the NIH Prematurity and Respiratory Outcomes Program (PROP) whose goals are the identification of disease mechanisms and biomarkers to stratify premature infants, at the time of discharge, for their risk of subsequent pulmonary morbidity. This Clinical Research Center (CRC) project will investigate prematurity-dependent alterations in cellular innate and adaptive immune systems resulting in increased susceptibility to respiratory infections and environmental irritants, and leading to respiratory morbidity in the first year of life. Prior studies have established developmental (maturity) and disease-related changes in circulating and pulmonary lymphocyte populations, but a comprehensive assessment of their relationship to disease risk/outcome has not been undertaken. We hypothesize that cellular and molecular immuno-maturity is altered due to intrinsic and extrinsic factors presented by premature birth in such a way as to reduce resistance to viral infections and to promote cytotoxic damage to the lung. We will evaluate immunologic maturity by comprehensively phenotyping lymphocyte populations in peripheral blood sampled at premature delivery, at the time of discharge from the hospital and at twelve months corrected age. The lymphocytic phenotype will be analyzed particularly in the context of gestational age and maternal-fetal stressors capable of modulating oxidative stress (oxygen exposure, infection and environmental tobacco smoke exposure). Additionally, we will assess changes in the molecular phenotype of isolated CD8 lymphocytes, a cell type preferentially recruited to the lungs of premature infants and capable of contributing to disease pathogenesis, by genome-wide expression profiling, in order to uncover novel disease pathways and define a gene expression signature associated with disease risk. We propose to build a statistical model, using cellular and molecular phenotypes and additional clinical variables, for stratifying risk of lung morbidity within the first year of life. Finally, we will assess the development of the gut microbiome in the preterm subjects to correlate with the observation of development of the adaptive immune system.

  Study phs001297

• International Consortium to Identify Genes and Interactions Controlling Oral Clefts

  Oral clefts represent the most common group of craniofacial birth defects in humans, and include cleft lip with or without cleft palate (CL/P) and cleft palate (CP). Oral clefts have a complex and heterogeneous etiology, with strong evidence for both genetic and environmental causal factors. Candidate gene studies and genome wide linkage studies have yielded compelling but inconsistent evidence that multiple genes control risk, and several studies have shown evidence for interaction between genes and environmental exposures, especially maternal smoking and nutrient intake. This consortium pulls together a very large collection of cases and their parents from multiple populations, and offers a unique opportunity to expand the search for genes controlling risk to the genome wide level. The specific aims are: To conduct a genome wide analysis on 2000+ case-parent trios ascertained through a case with isolated, non-syndromic CL/P or CP to test for linkage and disequilibrium. Initial analysis will consist of individual tests for gene effects while simultaneously testing for GxE interaction with common maternal exposures including vitamin supplementation, cigarette smoking and alcohol consumption (which have all been implicated as environmental risk factors for oral clefts). To use haplotypes in tests for GxE interaction incorporating population specific estimates. Since haplotype frequencies vary among populations, trios will be assigned haplotypes in a stratified estimation and then a pooled test statistic will be constructed. To test for interaction between SNPs in different genes showing evidence of influencing risk in a test for GxG interaction. To test for interaction between genes and maternal biomarkers using trios from Utah where measures of plasma folate, vitamin B-6, homocysteine and zinc in mothers are available. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org), which was developed through the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to oral clefts through large-scale genome-wide association studies of well-characterized cases and their parents from multiple populations. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). The study was supported by the National Institute of Dental and Craniofacial Research (NIDCR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000094

• 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

• Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses

  Background Single-cell RNA sequencing (scRNAseq) is a powerful tool for studying complex biological systems, such as tumour heterogeneity and tissue microenvironments. However, the sources of technical and biological variation in primary solid tumour tissues and patient-derived mouse xenografts for scRNAseq, are not well understood. Here, we used low temperature (6°C) protease and collagenase (37°C) to identify the transcriptional signatures associated with tissue dissociation across a diverse scRNAseq dataset comprising 128,481 cells from patient cancer tissues, patient-derived breast cancer xenografts and cancer cell lines.Results We observe substantial variation in standard quality control (QC) metrics of cell viability across conditions and tissues. From FACS sorted populations gated for cell viability, we identify a sub-population of dead cells that would pass standard data filtering practices, and quantify the extent to which their transcriptomes differ from live cells. We identify a further subpopulation of transcriptomically “dying” cells that exhibit up-regulation of MHC class I transcripts, in contrast with live and fully dead cells. From the contrast between tissue protease dissociation at 37°C or 6°C, we observe that collagenase digestion results in a stress response. We derive a core gene set of 512 heat shock and stress response genes, including FOS and JUN, induced by collagenase (37°C), which are minimized by dissociation with a cold active protease (6°C). While induction of these genes was highly conserved across all cell types, cell type-specific responses to collagenase digestion were observed in patient tissues. We observe that the yield of cancer and non-cancer cell types varies between tissues and dissociation methods.Conclusions The method and conditions of tumour dissociation influence cell yield and transcriptome state and are both tissue and cell type dependent. Interpretation of stress pathway expression differences in cancer single cell studies, including components of surface immune recognition such as MHC class I, may be especially confounded. We define a core set of 512 genes that can assist with identification of such effects in dissociated scRNA-seq experiments.

  Study EGAS00001003753

• Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Despite druggable events in 80% of neuroblastoma patients within the Princess Máxima Center precision medicine program 'iTHER', clinical uptake of treatment recommendations has been low, and the clinical impact for individual patients remains hard to predict. This stresses the need for a method integrating genomics and transcriptomics with functional approaches into therapeutic decision making. We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake. Cell lines, NBL-PDOs and their parental tumors were characterized utilizing (lc)WGS, WES and RNAseq. Cells were exposed to a ~200 compound library, and viability was assessed using CellTiterGlo or MTT. Molecular and HTS results were transferred to the R2 platform (http://r2platform.com/pmc_nb_drugs/), in which a comprehensive suite of visualizations and analysis options were implemented. As a result, a powerful reference set of cell lines is available, reflecting distinct known pharmacologic vulnerabilities, including resistance of TP53-inactivated lines to MDM2 inhibitor idasanutlin; ALK-inhibitor sensitivity in ALK-activated lines, and sensitivity of an ATM-deleted cell line to PARP- and CHEK1-inhibitors. Novel established NBL-PDOs retained molecular features of their parental tumor and again reflected established drug sensitivities. However, HTS also identified additional therapeutic vulnerabilities in vitro, such as a striking correlation between a positive mesenchymal signature and sensitivity to BCL2-inhibitor venetoclax. Finally, we explored personalized drug sensitivities within iTHER, demonstrating HTS can support genomic and transcriptomic results, thereby strengthening the rationale for clinical uptake. Furthermore, in vitro insensitivity may avoid ineffective treatments. Lastly, novel treatment options may be identified, as indicated by sensitivity to ponatinib correlating with overexpression of RET or KIT. In conclusion, we established a dynamic publicly available dataset with detailed genomic, transcriptomic, and pharmacological annotation of classical neuroblastoma cell lines as well as NBL-PDOs, representing the heterogeneous landscape of neuroblastoma. We anticipate that in vitro drug screening will be complementary to genomic-guided precision medicine by supporting clinical decision making, thereby improving prognosis for all neuroblastoma patients in the future.

  Study EGAS00001007160

• WTCCC2 Pharmacogenomic Response to Statins study

  A WTCCC2 project genome-wide study for pharmacogenomic response to statins (PR) in individuals from Scotland.

  Study EGAS00000000121

• Sequencing data (BAM files) from - A mutation in VPS15 (PIK3R4) causes a ciliopathy and affects IFT20 release from the cis-Golgi. The Data Access Committee (DAC) is responsible for sequencing data release to external requestors based on consent and/or National Research Ethics terms.

  Dac EGAC00001000552

• Structural variants

  Structural variants assessed in 6 patient samples with varying phenotypes, through the use of sniffles2 with a support parameter of 1 and at a length of 30 bp

  Dataset EGAD50000000741

• McQuillin_Global_WES_Schizophrenia

  Whole Exome Sequencing of Schizophrenia cases and matched controls performed at the Broad Institute on a cohort from UCL, London, UK

  Study EGAS50000000901

• Metagenome shotgun sequencing of the Inflammatory Bowel Disease

  We performed a comprehensive metagenome-wide association study for inflammatory bowel disease by utilizing whole-genome shotgun sequencing.

  Study JGAS000530

• KIT-dependent and -independent genomic heterogeneity of resistance in gastrointestinal stromal tumors - TORC1/2 inhibition as salvage strategy

  The mutational status of GIST analyzed with a broad sequencing approach (WES, RNAseq)

  Study EGAS00001003405

• ICGC Breast Cancer Project

  A comprehensive characterisation and analysis of human breast cancers through genome-wide approaches including genomics, transcriptomics and epigenomics.

  Study EGAS00001001195

• Kidney_tumour_DNA

  This is a bulk DNA and RNA sequencing study of human renal tumours

  Study EGAS00001002486

• WTCCC2 BO (Barretts oesophagus) samples

  A WTCCC2 project genome-wide case-control association study for Barretts oesophagus in individuals from the UK.

  Study EGAS00001000628

• Metastatic_breast_cancer_targeted_gene_screen

  The samples will be sequenced for a targeted panel of cancer relevant genes (n ~ 370) and analysed for somatic mutations.

  Study EGAS00001000704

• GermCellTumour

  DNA and RNA sequencing across a number of different germ cell tumours, included mixed components within the same tumour.

  Study EGAS00001003457

• checup

  Sequencing data from a phase II study of nivolumab and ipilimumab in recurrent or refractory cancer of unknown primary (CheCUP trial)

  Study EGAS00001007403

• WGS and RNA-Seq data from a GBM patient PT-HO0394

  WGS and RNA-Seq data from a GBM patient PT-HO0394

  Dataset EGAD00001004243

• Melanoma Germlines subset for BAP1

  These samples comprise both melanoma cases and controls sequenced for a selection of loci linked to disease susceptibility. These bams are a subset of the sequencing restricted specifically to the GRCh37 coding areas of the BAP1 gene.

  Dataset EGAD00001002743