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• RNA sequencing

  For RNA sequencing: All sample numbers starting with 6717 are tumor samples which has been sequenced using transcriptomics (see BAM files). It concerns biopsies of metastatic lesions from patients with BRAFV600 mutated melanoma, obtained before, during and after the study treatment (see samples metadata). RNA sequencing is performed using the Illumina Novaseq 6000 system.

  Dataset EGAD50000000383

• NICOLA QUB Genetic

  Blood-derived DNA was obtained from samples within the NICOLA cohort. Genetic data was generated using the Illumina Infinium CoreExome-24 array (Illumina, USA) and is available for 2,978 participants (551,839 directly genotyped and 18,148,478 imputed single nucleotide polymorphisms following initial quality control). Genetic .bed .bim and .fam files are available.

  Dataset EGAD00010002762

• Woodcock et al TenMenDeep Study EGA Dataset B

  Woodcock et al TenMenDeep EGA Dataset B. These are Illumina based deep sequencing data based on bait capture sequencing. See Woodcock et al methods for more detail. Note: the Amplicon sequencing data type is selected because the EGA Website currently has no option to select Bait Capture Sequencing or similar.

  Dataset EGAD00001005382

• Woodcock et al TenMenDeep Study EGA Dataset A

  Woodcock et al TenMenDeep EGA Dataset A. These are Illumina based deep sequencing data based on bait capture sequencing. See Woodcock et al methods for more detail. Note: the Amplicon sequencing data type is selected because the EGA Website currently has no option to select Bait Capture Sequencing or similar.

  Dataset EGAD00001005381

• SG10K_Pilot Dataset: Whole genome sequencing data of 4810 individuals from Singapore

  Genomic data obtained from the joint processing and variant calling of 4,810 individuals from Singapore. VCF files are by Chromosome (chr. 1-22 plus X) for all 4,810 individuals. Self-reported ethnicity is found in the "Region" column of metadata file.

  Dataset EGAD00001005337

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

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

  Study phs001026

• Mapping genetic variants underlying gene regulation in healthy intestinal cell types to identify novel IBD drug targets

  Biopsies from the terminal ileum and rectum of healthy individuals are digested on ice to single cells and processed for single-cell RNA-sequencing (10X Genomics and Illumina) 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 EGAD00001006331

• eIMPACT Trial: Modernized Collaborative Care to Reduce the Excess CVD Risk of Older Depressed Patients

  Cardiovascular disease (CVD) is the #1 killer of American men and women, and its economic burden is substantial and on the rise. Adults with depression are at elevated risk of CVD events and poor CVD prognosis. Unfortunately, past clinical trials of depression treatments have not observed the anticipated cardiovascular benefits. A novel explanation for these null results is that the depression interventions in these trials, which all involved patients with preexisting CVD, were delivered too late in the natural history of CVD. Accordingly, the objective of this single-center, parallel-group, assessor-blinded randomized controlled trial was to determine whether successful depression treatment before, versus after, the onset of clinical CVD reduces CVD risk in depression. Primary care patients with depression and elevated CVD risk from a safety net healthcare system (N = 216, Mage = 59 years, 78% female, 50% Black, 46% with income <$10,000/year) were randomized 1:1 to 12 months of the eIMPACT intervention (a modernized collaborative stepped care program involving internet cognitive-behavioral therapy [CBT], telephonic CBT, and/or select antidepressants) or usual primary care for depression (primary care providers supported by embedded behavioral health clinicians and psychiatrists). The primary outcome was endothelial dysfunction (brachial flow-mediated dilation) at 12 months, and the secondary outcomes were self-reported depressive symptoms (Hopkins Symptom Checklist-20), autonomic dysfunction (high-frequency heart rate variability), systemic inflammation (interleukin-6 and high-sensitivity C-reactive protein), and platelet activation (β-thromboglobulin and platelet factor 4) at 12 months. The central hypothesis was that the eIMPACT intervention would improve endothelial dysfunction in depressed adults by decreasing depressive symptoms, autonomic dysfunction, systemic inflammation, and platelet activation. Primary results are posted to ClinicalTrials.gov at NCT02458690. The de-identified limited dataset available on BDC consists of only the individual phenotypic data needed to confirm this trial’s primary results – i.e., randomization status, primary and secondary outcome variables, and participant characteristics utilized in the hypothesis-testing models (age, sex, race, education, income, and systolic blood pressure). We also provide the SAS code to replicate the results of the hypothesis-testing models reported in Table 4 and Supplemental Tables 1-3 in the main outcomes paper (#2 in Selected Publications). Of note, the user will need to specify the file path for the dataset to run the SAS code. Instructions for requesting individual-level data are available on BDC at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BDC. For questions about availability, you may contact the BDC team at https://biodatacatalyst.nhlbi.nih.gov/contact.

  Study phs003283

• Identification of RNA biomarkers in Parkinson's disease iPSC-derived neuronal cells

  Parkinson?s disease (PD) is an age-related, chronic and progressive neurodegenerative disorder characterized by a loss of multifocal neurons and subsequent motor symptoms. These overt motor symptoms are often preceded by prodromal non-motor symptoms. Though a number of genetic and environmental factors have been identified to play a role in PD, more exact methods for both diagnosing and assessing prognosis are yet to be discovered. Probing the transcriptomes of control and PD cells can give some interesting insight into changes caused by the disease (in both coding and non-coding gene expression), highlighting potential RNA biomarkers that may be used for PD diagnosis and as new drug targets. The study consists of two main sources of data: matched neural stem cell (NSC) and fully differentiated dopaminergic neurons derived from iPS cells. Both sets of data are made up of three samples from a control cell line, and five samples carrying a mutation in one of several genes known to be linked to heritable PD: PARK2, PARK22 or PARK9. All transcriptome libraries were synthesized and sequenced using no-amplification non-tagging cap analysis of gene expression (nAnT-iCAGE) on the Illumina HiSeq 2500 platform. Resulting data was mapped to the human genome annotation (hg38) and processed CAGE tags were clustered ready for differential expression analyses. The 16 samples here described were sequenced across two lanes.

  Study JGAS000142

• Identification of RNA biomarkers in Parkinson's disease iPSC-derived neuronal cells

  Parkinson���s disease (PD) is an age-related, chronic and progressive neurodegenerative disorder characterized by a loss of multifocal neurons and subsequent motor symptoms. These overt motor symptoms are often preceded by prodromal non-motor symptoms. Though a number of genetic and environmental factors have been identified to play a role in PD, more exact methods for both diagnosing and assessing prognosis are yet to be discovered. Probing the transcriptomes of control and PD cells can give some interesting insight into changes caused by the disease (in both coding and non-coding gene expression), highlighting potential RNA biomarkers that may be used for PD diagnosis and as new drug targets. The study consists of two main sources of data: matched neural stem cell (NSC) and fully differentiated dopaminergic neurons derived from iPS cells. Both sets of data are made up of three samples from a control cell line, and five samples carrying a mutation in one of several genes known to be linked to heritable PD: PARK2, PARK22 or PARK9. All transcriptome libraries were synthesized and sequenced using no-amplification non-tagging cap analysis of gene expression (nAnT-iCAGE) on the Illumina HiSeq 2500 platform. Resulting data was mapped to the human genome annotation (hg38) and processed CAGE tags were clustered ready for differential expression analyses. The 16 samples here described were sequenced across two lanes.

  Study JGAS000318

• Aberrant (pro)renin receptor expression induces genomic instability by chromatin remodeler SMARCA5 disruption during the pancreatic ductal adenocarcinoma

  The aim of the present study is to elucidate whether aberrant (P)RR expression induces genomic instability in human pancreatic ductal epithelial (HPDE) cells, which are transforming into pancreatic ductal adenocarcinoma (PDAC).

  Study JGAS000143

• An exome sequencing approach to defining the genetic risk factors for Achilles tendinopathy

  Musculoskeletal soft tissue injuries are complex phenotypes. Case control association studies using the candidate gene approach have predominantly been used to identify risk loci for these injuries. However, the ability to identify all risk conferring variants using this approach alone is unlikely. Therefore, this study aimed to define the genetic profile of these injuries using whole exome sequencing and a customized analysis pipeline. The exomes of ten exemplar asymptomatic controls and ten exemplar cases with Achilles tendinopathy were individually sequenced using a platform that included the coverage of the untranslated regions and miRBase miRNA genes. These results provide a proof of concept for the use of a customized pipeline for the exploration of a larger genomic dataset. This approach, using previous research to guide a targeted analysis of the data has generated new genetic signatures in the biology of musculoskeletal soft tissue injuries.

  Study EGAS00001003234

• Pediatric Papillary Thyroid Carcinoma Whole Exome Sequencing

  BACKGROUND: Pediatric papillary thyroid carcinoma (PPTC) is distinct from adult-onset disease. Despite higher rates of regional and distal metastases and more frequent recurrence, there is, paradoxically, a highly favourable prognosis. Historically, only 40-50% of childhood PTC are driven by genomic variants common to adult PTC, while the oncogenic drivers in the remainder are unknown. METHODS: Fifty-two PPTCs were genotyped by candidate gene testing, followed, in a subset (n=32), by whole exome (WES) and transcriptome sequencing (RNASeq) to identify oncogenic variants in driver-unknown tumors and to explore gene expression patterns. FINDINGS: Thirty-one tumors (60%) carried variants identified by candidate gene testing, specifically: BRAFV600E(22%), NRASQ61R(2%), RET-CCDC6(19%), RET-NCOA4(15%) and PAX8-PPARG. Among the 21 remaining tumors with negative first-line genotyping, oncogenic variants were identified in 19 (90%). These were enriched with oncogenic fusions, with 11 non-recurrent fusion transcripts identified, including two that had not been previously described: STRN-RET and TG-PBF. Most fusions were associated with 3’ receptor tyrosine kinase (RTK) moieties: RET, MET, ALK and NTRK3. Gene expression analysis defined three distinct clusters, which demonstrated differing expression of genes involved in thyroid differentiation and MAPK signaling. INTERPRETATION: Exome and transcriptome-wide sequencing identify genomic drivers of PPTC in 98% of tumors, whereas conventional genotyping leaves many tumors genetically unexplained. PPTC is driven, in the majority of cases, by oncogenic fusion transcripts involving one of a limited number of RTKs. These observations have broad implications for diagnostic testing and for therapeutic options in children with advanced disease.

  Study EGAS00001005187

• SINGLE_CELL_ANALYSIS_OF_IN_VITRO_ERYTHROPOIESIS

  We are developing a protocol to differentiate mouse and human induced pluripotent stem (IPS) and embryonic stem (ES) cells towards the haematopoietic pathway to generate erythrocytes in vitro. This system has many applications such as the study of the role of specific genes and human polymorphisms in infectious diseases such as malaria, as well as haematological diseases such as myelodysplastic syndrome. The nature of the in vitro differentiation process means that a heterogeneous population of cells is generated. In order to understand the types of cells produced with our protocol, we have performed a single cell analysis, which has the power to reveal the different populations of cells and their characteristics. For this, a cDNA library has been made that needs to be sequenced to obtain the gene expression profiles of the different cells. With this information we will be able to assess the quality of the differentiation protocol and improve it in order to produce better cells for the downstream applications.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 EGAS00001000764

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas (2019-04-03)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004893

• Enhanced cortical neural stem cell identity through SMAD/WNT inhibition in human cerebral organoids facilitates emergence of outer radial glial cells

  Cerebral organoids exhibit broad regional heterogeneity accompanied by limited cortical cellular diversity despite the tremendous upsurge in derivation methods, suggesting inadequate patterning of early neural stem cells (NSCs). Here we show that a short and early dual-SMAD/WNT inhibition course is necessary and sufficient for establishing robust and lasting cortical organoid NSC identity, efficiently suppressing of non-cortical NSC fates, while other widely used methods are inconsistent in their cortical NSC specification capacity. Accordingly, this method selectively enriches for outer radial glia (oRG) NSCs, which cytoarchitecturally demarcate well-defined outer sub-ventricular (oSVZ)-like regions propagating from superiorly radially organized, apical cortical rosette NSCs. Finally, this method culminates in the emergence of molecularly distinct deep and upper cortical layer neurons, and reliably uncovers cortex-specific microcephaly defects. Thus, a short SMAD/WNT inhibition is critical for establishing a rich cortical cell repertoire that enables mirroring fundamental molecular and cytoarchitectural features of cortical development and meaningful disease modeling.

  Study EGAS00001006063

• Kids First: Whole Genome Sequencing of Nonsyndromic Craniosynostosis

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Nonsyndromic craniosynostosis (NCS) is a common, major structural birth defect - due to the premature fusion of one or more cranial sutures - that requires extensive surgical correction and is associated with considerable ongoing medical problems and health care costs. Because little is known about the causes of NCS, whole genome sequencing will help advance knowledge of genetic factors contributing to the etiology of NCS. Data from this project will lead to a better understanding of biological processes involved in the etiology of NCS and provide critical insights for development of early diagnostic tools and therapeutic strategies.

  Study phs001806

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Kidney (1)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Dataset EGAD00001006427

• National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC) Study

  Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. Phenotype data will be stored at dbGaP, while molecular and sequence data will be stored at BioData Catalyst. The PCGC Cohort is utilized in the following dbGaP substudies. Please click on the following substudies below or in the "Substudies" section of this top-level study page phs001194 PCGC Cohort. phs000571 PCGC: whole exome sequences, whole genome sequences, targeted sequences, MIP sequences, and SNP array data phs001843 PCGC-CMG Collaboration: whole genome sequences The Gabriella Miller Kids First Pediatric Research Program (Kids First) subset of the PCGC project (phs001194) is now accessible through a separate dbGaP study accession: phs001138. To access this dataset, please submit a Data Access Request (DAR) for phs001138. Approval of this DAR will be expedited for approved users of phs001194. To learn about other Kids First datasets visit https://kidsfirstdrc.org/.NHLBI's TOPMed program has provided additional Whole Genome Sequencing for PCGC participants - that data is accessible through a separate dbGaP sudy accession: phs001735. Access to this data set should be requested through a Data Access Request (DAR) for phs001735.

  Study phs001194

• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Gene Discovery in Autosomal Dominant Focal Segmental Glomerulosclerosis (FSGS)

  Focal segmental glomerulosclerosis (FSGS) is a frequent cause of end-stage renal disease. The pathogenesis of FSGS has not been precisely defined and there are no consistently effective treatments. Recent studies identifying causal genes in rare, inherited FSGS, including our own study, have associated mutations in at least six genes with familial FSGS, and each discovery has clarified molecular mechanisms of glomerular injury. To build on this productive line of inquiry, we have ascertained and carefully characterized 118 families with familial FSGS. We have screened the remainder of our families for mutations in genes known to cause FSGS and identified the causal mutations in an additional 6 kindreds; the genetic basis of disease in the remaining 111 families is unknown. The objective of this proposal is to use this valuable and unique family resource to systematically identify causal genes for familial FSGS. Limitations of current conventional linkage and positional cloning approaches include their requirement for large, multiplex families. In addition, narrowing candidate areas in traditional linkage analysis can be difficult due to large regions that lack recombination events and hence these regions have required cumbersome and lengthy screening for causative mutations. Powerful new genetic tools can facilitate this screening process and improve variant discovery in smaller families. In particular, efficient whole-exome sequencing, the targeted capture of protein-coding gene sequences, should be particularly useful in our studies since most Mendelian disorders are caused by mutations affecting exomes of the target gene. Thus, by combining genome-wide linkage analysis (GWLS) and whole-exome sequencing, we can maximize impact of our family data and accelerate identification of novel mutations in FSGS. In preliminary studies, we have used this combination to identify a novel variant in the WT1 (Wilms' Tumor-1) gene in one FSGS family, and we have evidence suggesting it is the causal mutation. This success provides proof-of-concept and provides a roadmap of how genes will be identified and evaluated in the proposed studies. Our hypothesis is that causes of inherited FSGS in our cohort of families will be sequence variants in the coding region of genes not previously associated with familial FSGS. We aim to: 1) Use GWLS and whole-exome sequencing to identify genetic variants associated with familial FSGS. 2) Characterize functional consequences of candidate causative mutations and 3) Determine the prevalence in the Duke FSGS dataset of these new causative mutations identified in Aim 2. Any genes found to have causative mutations will be sequenced in the remaining families and take full advantage of our family resource. By combining genome-wide linkage analysis (GWLS), whole-exome sequencing, and characterization of variants' functional consequences, we will significantly improve understanding of normal glomerular biology and of the pathogenesis of FSGS and related glomerular diseases. Moreover, our discoveries are likely to reveal new opportunities to improve therapy for a disease that currently has few effective treatments.

  Study phs000777

• Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants and parents), NIDDK

  Genetics of Kidneys in Diabetes (GoKinD) study is an initiative aimed at identifying susceptibility genes for diabetic nephropathy in type 1 diabetes. A large number of individuals with type 1 diabetes were screened to identify two subsets, one with clear-cut kidney disease and another with normal renal status despite long-term diabetes. Those who met additional entry criteria and consented to participate were enrolled. When possible, both parents were also enrolled to form family trios. Altogether, GoKinD includes 3043 participants comprising 931 cases, 944 singletons, 268 pairs of parents of cases, and 316 pairs of parents of control. Accessible as a GAIN database are 905 of the cases, 890 of the controls, 10 pairs of parents of cases and 10 pairs of parents of controls (dbGaP phs000018 Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants), GAIN). The other parents and the remaining cases and controls are available by a separate application process through NIDDK. Interested investigators may request the DNA collection and corresponding clinical data for GoKinD participants using the instructions and application form available at http://www.niddkrepository.org or by contacting the Juvenile Diabetes Research Foundation.

  Study phs000088

• Endothelium-derived stromal cells contribute to bone marrow niche formation

  Comprehensive transcriptional characterization of bone marrow stromal cells by RNA sequencing was performed to determine the molecular properties/signatures of endothelium during niche formation.Here, we identify a rare subset of cells in the human fetal BM that co-express endothelial and stromal markers, including low-affinity nerve growth factor receptor (LNGFR/CD271). They display transcriptional reprogramming consistent with endothelial-to-mesenchymal transition (EndoMT), reflected in their potential to generate stromal cells with in vivo BM niche forming capacity.

  Study EGAS00001004946

• Interactions between the tumor and the systemic response of breast cancer patients

  Breast cancer (BC) research has largely focused on the molecular properties of the tumor proper. However, to understand how cancer progresses and ultimately modulates patient outcome, we also require an understanding of the molecular changes in the patient systemic response (SR). Toward this end, we generated and analyzed RNA profiles from tumor and matched blood samples in 173 BC patients. We designed a system (MIxT) to explore and link tightly co-expressed gene sets (modules) across matched tissues. The gene composition of modules, and their expression, largely vary across tissues. Distinct patterns of expression in the SR are predominantly detected in highly immunogenic BC subtypes. We also find that the expression pattern of a module in one tissue is correlated to the expression pattern of a module in the other tissue in a fashion that depends on subtype. For example, systemic immunosuppression is detected in basalL patients in a fashion that is proportional to the level of expression of several tumor modules highlighting immune evasion mechanisms active in these particular cancers.

  Study EGAS00001001804

• Analysis of error profiles in deep next-generation sequencing data

  BackgroundSequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.ResultsBy evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target enrichment PCR led to aprox 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1% - 0.01% frequency with the current NGS technology by applying in-silico error suppression.ConclusionsWe present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

  Study EGAS00001003444

• CRC Promoter capture Hi-C

  Genome organisation determines chromosome interactions between regulatory elements, such as promoters and enhancers, influencing gene expression. Despite the fact that it is possible to assess whether a gene is actively transcribed, it has been challenging to point out the genomic regions that are involved in the regulation of a particular gene. We are interested in better understanding the interactions between promoters and their regulatory elements in colorectal cancer in order to unveil novel non-coding regions which might have a role in tumour development. To do so, we utilise the HiC method complemented with promoter capture in combination with NGS to map promoter interactions in two CRC cell lines, representing two distinct CRC subtypes.

  Study EGAS00001001946

• Bruno et al.: Interferon gamma rebalances immunopathological signatures in Chronic Granulomatous Disease through metabolic rewiring

  Chronic granulomatous disease (CGD) is a primary immunodeficiency characterized by recurrent life-threatening infections and hyperinflammatory complications. It is caused by mutations in the NADPH oxidase complex and the consequent loss of reactive oxygen species (ROS) production. Recombinant human interferon gamma (rIFN-γ) prophylaxis reduces the risk of severe infections, but the mechanisms behind its efficacy in CGD are still an open question, as it does not restore NADPH oxidase-dependent ROS production. Here, we show that myeloid innate immune cells of CGD patients are transcriptionally and functionally reprogrammed to a hyperactive inflammatory status, displaying an impaired in vitro induction of trained immunity. CGD monocytes have reduced intracellular amino acids concentrations and profound functional metabolic defects, both at the level of glycolysis and mitochondrial respiration. Ex vivo and in vivo treatment with IFN-γ restored these metabolic defects and reduced excessive IL-1β and IL-6 production in response to fungal stimuli in CGD monocytes. These data suggest that prophylactic rIFNγ modulates the metabolic status of innate immune cells in CGD. These data shed light on the effects of NADPH-derived ROS deficiency to the metabolic programs of immune cells and pose the basis for targeting this immunometabolic axis, potentially beyond CGD, with IFN-γ immunotherapy.

  Study EGAS00001005463

• South Asia Rheumatic Heart Disease Genetics Network

  Rheumatic heart disease (RHD) is a major cause of cardiovascular death and disability amongst young adults. Building on a sample collection established for and genotyped in several earlier successful candidate gene studies, this case-control study investigated host genetic susceptibility to RHD using a genome-wide approach. The current dataset comprises over 850 individuals recruited in Uttar Pradesh, India, including cases of RHD based on echocardiographic diagnosis and controls recruited on the basis of normal echocardiograms. For this analysis all available samples were genotyped using the Illumina HumanCore-24 BeadChip platform. Efforts are now underway to establish new sample collections in other areas of India as well as Pakistan and later other neighbouring countries.

  Study EGAS00001003565

• BARIA baseline first 100 individuals transcriptomes

  Prevalence of obesity and associated diseases, including type 2 diabetes mellitus, dyslipidaemia and non-alcoholic fatty liver disease (NAFLD), are increasing. Underlying mechanisms, especially in humans, are unclear. Bariatric surgery provides the unique opportunity to obtain biopsies and portal vein blood-samples. Methods The BARIA Study aims to assess how microbiota and their metabolites affect transcription in key tissues and clinical outcome in obese subjects and how baseline anthropometric and metabolic characteristics determine weight loss and glucose homeostasis after bariatric surgery. We phenotype patients undergoing bariatric surgery (predominantly laparoscopic Roux-en-Y gastric bypass), before weight loss, with biometrics, dietary and psychological questionnaires, mixed meal test (MMT) and collect fecal-samples and intra-operative biopsies from liver, adipose tissues and jejunum. We aim to include 1500 patients. A subset (approximately 25%) will undergo intra-operative portal vein blood-sampling. Fecal-samples are analyzed with shotgun metagenomics and targeted metabolomics, fasted and postprandial plasma-samples are subjected to metabolomics, and RNA is extracted from the tissues for RNAseq-analyses. Data will be integrated using state-of-the-art neuronal networks and metabolic modeling. Patient follow-up will be ten years.

  Study EGAS00001005704

• Genetics of Human Developmental Brain Disorders

  Developmental brain malformations are at the core of significant neurological diseases affecting many families in the United States and around the world. It is known that epilepsy, specific learning deficits and intellectual disability, cerebral palsy, and abnormalities of brain volume can be attributed in many cases to pathological malformations of the cerebral cortex. Although these consequences, such as epilepsy and intellectual disability, might appear broadly in the population as due to complex traits, this study's focus on those associated with cortical malformations highlights individual developmental pathways likely represented by innumerable and rare Mendelian alleles. Research has thus far uncovered dozens of genes responsible for these conditions and dissected the mechanisms underlying early cortical development in animals. However, this progress represents only the dawn of understanding the complex genetic network and neuronal architecture of the uniquely human cerebral cortex. The overall goal of this study is to define the genetic bases of human cerebral cortical development. This is accomplished through (1) the ascertainment of families with disorders of human brain development and malformation, (2) categorizing these using medical, physical and neuroimaging data, and (3) mapping and identifying the gene causing the disorder of cortical development, which can then be investigated for its normal expression and function, and role in human disease.

  Study phs000492

• Colorectal adenomas, carcinomas and adjacent normal NKI-AvL TGO series NGS-ProToCol

  Cancer is caused by changes in the genome of cells, resulting in aberrant transcripts and proteins. In order to understand why normal cells become cancer cells and how we can identify and destroy them, the CTMM-NGS-ProToCol project aimed to understand prostate and colorectal cancer through DNA and RNA molecular profiling, to further improve diagnosis, prognosis and treatment.The state-of-the-art within the field of genome sequencing makes it possible to identify all the modifications in our genome that encode for RNA and of the transcripts themselves. The latest development in RNA sequencing is that if one does not select for polyA RNA, but first removes rRNA from the total RNA and then performs ‘random’ RNA sequencing, 30-60% of the reads are intronic. Since about 40% of the genome consists of genes (and only 1.6% is exonic), deep RNA sequencing will cover not only the exons, but also a large portion of the introns and therefore much of the genome. The power of the combined sequencing of genome and transcriptome is the full view of copy number aberrations (CNA), exon mutations and the consequence and relevance of the mutations at the RNA level in the form of differential gene expression, alternative splicing, alternative promoter usage, novel transcripts, fusion transcripts, read-through transcripts and mutations. For the colorectal (tumor) tissue dataset, we applied molecular profiling to 30 colorectal adenomas, 30 colorectal carcinomas and 18 normal adjacent colon tissues.

  Study EGAS00001002854

• Development of CMT Peds Scale for Children with CMT

  Information about how different forms of CMT affect children is not readily available because there are not good methods to measure impairment of children with CMT. The purpose of this project is to develop and test such a method and to then test this scale to ensure that it is an effective measurement of impairment of CMT in children, that the children tolerate it well, that different investigators using this method obtain similar results and that changes over time with the scale allow measurement of progression of CMT in the children. Primary Objective: To develop and test the CMT Peds scale (CMTPedS) in children with CMT in order to refine the scoring for future natural history and therapeutic trials. Secondary Objective: We propose to test the sensitivity of the CMT Peds Scale in a longitudinal study and compare the CMT Peds Scale with the Children's Quality of Life scale CHQ-PF50. 2000 patients <21 years of age with various forms of CMT will be evaluated at baseline and at subsequent annual follow up visits when possible. This first study release makes available data of n=208 study participants.

  Study phs001553

• The National Heart, Lung, and Blood Institute (NHLBI)-funded Next Generation Genetic Association Studies (NextGen) Consortium: Phenotyping Lipid traits in iPS derived hepatocytes Study (PhLiPS Study)

  The goal of the PhLiPS study is to create a library of induced pluripotent stem cell (iPSC) lines and iPSC-derived hepatocytes of diverse genotypes for use in metabolic profiling and interrogating lipid phenotypes. These cell lines were created as a part of the Next Generation Genetic Association Studies (Next Gen) Program, which was a five-year, $80 million program to investigate functional genetic variation in humans by assessing cellular profiles that are surrogates for disease phenotypes. To achieve this, researchers from multiple institutions across the U.S. were awarded grants to derive iPSC lines from more than 1,500 individuals representing various conditions as well as healthy controls for use in functional genomic ("disease in a dish") research. This extensive panel includes a diverse set of age, gender, and ethnic backgrounds, and therefore will be an invaluable tool for evaluations across demographics. Further enhancing the utility of these cell lines are data sets such as phenotyping, GWAS, genome sequencing, gene expression and -omics analyses (e.g., lipidomic, proteomic, methylomic) that can be matched to the cell lines. The PhLiPS Study focuses on individuals free of cardiovascular disease or with lipoprotein metabolism disorders in the community served by the Hospital of the University of Pennsylvania.

  Study phs001341

• Single cell sequencing of endoscopic biopsies from Barrett's oesophagus and proximal tissue from the normal GI tract

  Barrett’s oesophagus is a precursor of oesophageal adenocarcinoma. In this common condition, squamous epithelium in the oesophagus is replaced by columnar epithelium in response to acid reflux. Barrett’s oesophagus is highly heterogeneous and its relationships to normal tissues are unclear. We investigated the cellular complexity of Barrett’s oesophagus and the upper gastrointestinal tract using RNA-sequencing of single cells from multiple biopsies from six patients with Barrett’s oesophagus and two patients without oesophageal pathology.

  Study EGAS00001003144

• A developmental cell atlas of the human thyroid gland

  Thyroid hormones are essential for health, but human thyroid development and cellular heterogeneity are poorly understood. We generated a high-resolution, spatiotemporal transcriptional atlas of human fetal thyroid, and examined its perturbations in trisomy 21 (T21), where aberrant thyroid development is associated with congenital hypothyroidism, and in papillary thyroid carcinoma (PTC). Normal tissue revealed two functional follicular cell states (fTFC1, fTFC2) with divergent PAX8 expression levels, persisting into adulthood. Additionally, the rare C-cell population was comprehensively profiled at single-cell resolution for the first time. T21 fetal thyroid was hypoplastic, with disrupted follicular morphology and altered expression of genes mediating cellular topology and extracellular matrix interactions. Finally, the transcriptional signals of both fetal follicular cell states were found to be perturbed in PTC. Overall, we defined a reference atlas for normal human fetal thyrocyte heterogeneity and provided novel insights into thyroid disorders.

  Dataset EGAD00001015783

• Kids First: Genetics of Pediatric Germ Cell Tumors

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the genomic and phenotypic data from this study are accessible through dbGaP. The data is also available at the Kids First Portal, where other Kids First datasets can also be accessed in the cloud for data analysis, data visualization, collaboration and interoperability, open to all researchers and developers.Pediatric malignant germ cell tumors (GCTs) represent approximately 6% of childhood cancers, including 3% of tumors in children aged 0-14 years and 15% of tumors in adolescents. GCTs are heterogeneous and grouped together due to the presumed common cell of origin, the primordial germ cell (PGC). GCTs typically occur in the testes or ovaries; however, extragonadal GCTs can occur and are likely a result of abnormal germ cell migration during development. Evidence suggests that GCTs, including those diagnosed in adults, are initiated in utero. Thus, alterations in normal embryonic development are likely to be especially relevant to GCT etiology. Germline susceptibility has not been evaluated in an agnostic fashion in pediatric GCT, mainly due to a lack of an adequate number of samples; however, emerging evidence supports a genetic etiology.In the two Kids First GCT projects, we will evaluate genetic susceptibility to intracranial and extracranial GCT by sequencing probands and their unaffected parents. The goals of the project are to: 1) evaluate the contribution of rare genetic variants in GCT through the use of aggregate burden tests, focusing on genes and established regulatory regions; 2) identify de novo SNVs and CNVs in pediatric GCT using a case-parent triad design; and 3) identify molecular signatures in GCT tumor specimens, overall and by age group and tumor characteristics. Whole Genome Sequencing (WGS) data generated through the Gabriella Miller Kids First Pediatric Research Program will provide an opportunity to investigate the genetic origins of GCT in a diverse set of samples. Given the limited knowledge of GCT etiology and biology, the results of the proposed analyses are likely to have a big impact on the field.

  Study phs002322

• BIONi010-C-8 / SAMEA4454011 WGS data

  The iPSC line BIONi010-C-8 / SAMEA4454011 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-8 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001028

• SIGi001-A-13 / SAMEA104386250 WGS data

  The iPSC line SIGi001-A-13 / SAMEA104386250 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-13 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001031

• BIONi010-C-3 / SAMEA4342740 WGS data

  The iPSC line BIONi010-C-3 / SAMEA4342740 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-3 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001034

• BIONi010-C-7 / SAMEA4454010 WGS data

  The iPSC line BIONi010-C-7 / SAMEA4454010 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-7 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001035

• BIONi010-C-6 / SAMEA4454009 WGS data

  The iPSC line BIONi010-C-6 / SAMEA4454009 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-6 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001037

• BIONi010-C-9 / SAMEA4454012 WGS data

  The iPSC line BIONi010-C-9 / SAMEA4454012 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-9 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001040

• SIGi001-A-3 / SAMEA4448571 WGS data

  The iPSC line SIGi001-A-3 / SAMEA4448571 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-3 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001041

• BIONi010-C-4 / SAMEA4452060 WGS data

  The iPSC line BIONi010-C-4 / SAMEA4452060 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-4 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001043

• EDi014-A / SAMEA4459369 WGS data

  The iPSC line EDi014-A / SAMEA4459369 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001051

• EDi014-B / SAMEA4459371 WGS data

  The iPSC line EDi014-B / SAMEA4459371 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001053

• SIGi001-A-9 / SAMEA4447499 WGS data

  The iPSC line SIGi001-A-9 / SAMEA4447499 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-9 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001095

• SIGi001-A-8 / SAMEA4448777 WGS data

  The iPSC line SIGi001-A-8 / SAMEA4448777 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-8 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001093

• SIGi001-A-5 / SAMEA4448708 WGS data

  The iPSC line SIGi001-A-5 / SAMEA4448708 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-5 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001092

• SIGi001-A-4 / SAMEA4448632 WGS data

  The iPSC line SIGi001-A-4 / SAMEA4448632 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-4 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001088

• SIGi001-A-6 / SAMEA4447426 WGS data

  The iPSC line SIGi001-A-6 / SAMEA4447426 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-6 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001078