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• Acute myeloid leukemia bulk RNA-seq (Diagnosis and Relapse)

  To gain insight into the clonal heterogeneity of diagnosis (Dx) and relapse (Re) pairs, we employed RNA-seq to longitudinally profile two t(8;21) (AML1-ETO = RUNX1-RUNX1T1), and four FLT3-ITD AML cases. All the samples are bone marrow aspirates.

  Dataset EGAD00001008374

• Metagenome for FINRISK2002

  The dataset contains data for n=7211 FINRISK 2002 participants who underwent fecal sampling. Demultiplexed shallow shotgun metagenomic sequences were quality filtered and adapter trimmed using Atropos (Didion et al., 2017), and human filtered using Bowtie2 (Langmead and Salzberg, 2012). The files are in FASTQ format.

  Dataset EGAD00001007035

• ChIP-seq bulk

  This dataset gather ChIP-seq data produced by immunoprecipitating CTCF factor in own laboratory in MM.1S cell line in EtOH and Dex conditions. It also gather ChIP-seq dataset produced by external laboratory (Active Motif) for H3K27ac mark and GR transcription factor in same cell line and conditions ( MM.1S ETOH/Dex)

  Dataset EGAD00001011136

• Longitudinal Study of Immune Mediated Disorders After Allogenic Hematopoietic Cell Transplantation (HCT)

  Allogeneic hematopoietic cell transplantation (HCT) is the only known curative option for many hematologic disorders. After transplantation, many patients develop immune mediated disorders that may be life-threatening. Post-HCT immune mediated disorders are rare relative to other diseases but the prototype of graft versus host disease (GVHD) develops in 30-70% of patients. The morbidity and mortality associated with these HCT-associated immune mediated disorders are major barriers to successful use of transplantation to cure rare hematologic malignancies such as leukemia, lymphoma, multiple myeloma, myelodysplastic/myeloproliferative syndromes amongst other diseases. The purpose of this study is to characterize and more completely define the onset and course of immune mediated disorders after allogeneic HCT, focusing on participants who develop cutaneous sclerosis, bronchiolitis obliterans syndrome (BOS), late acute graft-vs.-host disease (GVHD), and chronic GVHD. Of the participants undergoing allogeneic hematopoietic cell transplantation (HCT), can we, the researchers better identify who will develop immune-mediated disorders, what types of disorders participants will have, and whether these disorders will be severe or respond to currently available therapies? This is a longitudinal study of 1118 individuals (1081 adults and 100 children). Those participating in this study will be evaluated over a 3 year period at 9 study sites. Participants will be enrolled pre-transplant, or up to day 121 post transplantation. This wide enrollment window will allow sites to use recruitment methods that are most efficient at their institutions. At least 2 years of follow-up will ensure an adequate sample size, and sufficient time for observation of the full spectrum of immune mediated disorders. The data of 1023 individuals have been submitted to dbGaP.

  Study phs001331

• Exome Sequencing to Identify Medically Relevant Associations in Finnish Sub-Isolate Samples from the FINRISK Cohort

  We propose to undertake, at the McDonnell Genome Institute of Washington University, a collaborative exome sequencing project of ~10,000 samples from a large Finnish population cohort, FINRISK, a participating component of the Sequencing Initiative Suomi (SISu) consortium. Together these sequenced samples will provide a unique resource for identification of infrequent or rare variants with a large impact on cardiovascular and metabolic disorders as well as on a wide range of heritable, disease-related quantitative phenotypes. Our collaborative group has already shown, in exome sequencing studies of smaller Finnish samples, that numerous loss of function variants are dramatically more frequent in Finland compared to other European populations, and that such variants demonstrate strong associations to several disease-related traits. Finland is the largest population isolate in Europe and the enrichment of these variants reflects its rapid growth from a severe population bottleneck about 100 generations ago. Northern and Eastern parts of Finland experienced additional, more recent bottlenecks, and therefore the enrichment of particular high-impact variants in these regions is even more extreme (Stoll et al., 2013, PMID: 23912948). We therefore propose to focus exome sequencing efforts on about 10,000 members of FINRISK who are specifically drawn from these sub-isolate regions. As a very wide range of phenotypes are available from this cohort (including cardiovascular and metabolic disease outcomes obtained from national registries) we hypothesize that the proposed exome sequencing will identify numerous new disease-related associations. Within the National Biobanks of Finland (www.nationalbiobanks.fi) we have DNA and tissue samples from over 200,000 individuals of whom 50,000 have GWAS data; these samples provide an exceptional resource for both imputation from the sequencing studies proposed here, as well as for replication of associations.

  Study phs000756

• Genetic Analysis of Parkinson's Disease

  A portion of the sample includes multiplex PD families recruited as part of a previously funded study (R01NS037167; PI: Tatiana Foroud). Families were ascertained initially through a living affected sibling pair. Subsequently, ascertainment was loosened to include PD probands having a positive family history of PD in a first degree relative, who was not required to be part of the study. All individuals completed an in-person evaluation at one of the > 65 Parkinson Study Group sites participating in this study. Individuals completed a detailed evaluation that included the Unified Parkinson Disease Rating Scale (UPDRS), Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS) and a diagnostic checklist that implemented the UK PD Brain Bank inclusion and exclusion criteria. An autopsy program was established in this study and brain tissue for confirmation of diagnosis and further experimental study are available from over 100 participants. Autopsy confirmation of the PD diagnosis was nearly 100% for those who met UK PD Brain Bank criteria. In addition, because this was a cross sectional study and family members were often seen very early in disease course, among those who did not meet UK PD Brain Bank criteria but had a subsequent autopsy, a significant subset (>1/3) had autopsy confirmation of PD. The second source of samples is from the NINDS Human Genetics DNA and Cell Line Repository located at the Coriell Institute. Currently DNA from 4,509 PD patients is available from the Coriell Institute. We restricted the selected sample to include only Caucasians and ensured there was no overlap with samples contributed by the PROGENI Study.

  Study phs001004

• Binding of Epstein Barr Virus EBNA2 Unifies Multiple Sclerosis Genetic Mechanisms

  This study is focused on multiple sclerosis (MS). MS is likely caused by a combination of genetic and environmental factors; however, the mechanisms contributing to these factors remain poorly understood. Epstein-Barr virus (EBV) in particular is a well-established environmental risk factor for MS. We have created a computational algorithm that systematically searches for common molecular mechanisms that might be impacted at multiple MS-associated loci. Using this algorithm, we have discovered that over 40% of MS-associated loci contain MS genetic variants that fall within regions of the human genome occupied by the EBV-encoded EBNA2 protein. The same MS-associated variants also impact gene expression levels of MS-associated genes in EBV-infected B cell lines. Our hypothesis is that allele-dependent binding of EBNA2 and its co-factors explains the allele-dependent risk at many MS genetic loci. Importantly, this hypothesis links the genetic associations of MS to the known molecular roles played by EBV and Notch signaling in disease processes.Subjects with and without MS were recruited into an Institutional Review Board (IRB)-approved protocol through the Cincinnati Autoimmune Registry and Repository. From each subject, DNA from peripheral blood was isolated for whole genome sequencing (WGS). These data will be used to identify genotype-dependent transcriptional regulation in cells assessed from patients and controls. This WGS data was deposited before the full integration of sequence data with other functional genomic data types.From each subject, 90 mL of blood is drawn for isolation of peripheral blood mononuclear cells from which primary B and T cells will be isolated. For each B cell isolation, an EBV-transformed B cell line will be derived.

  Study phs003240

• Genomic Studies in Charcot-Marie-Tooth Disease

  The various forms of Charcot-Marie-Tooth disease (CMT) comprise a genetically heterogeneous set of peripheral neuropathies. Currently, >90 different CMT genes have been identified; yet, for the axonal CMT2 subtype these genes explain only 30-40% of the genetic effect. In particular, the application of exome sequencing has led to an unprecedented pace in identifying about half of those genes in the past five years. We have been at the forefront of this development with 22+ published new gene identifications in the past seven years. This success was only possible through broad national and international collaborations, data sharing, and the development of advanced analysis tools and methods. We also learned that despite an accumulation of exome sequencing data, over 50% of axonal CMT patients remain undiagnosed, suggesting even more genes are involved; additionally, our preliminary data also support the existence of non-coding variations as Mendelian allele contributors. In this study, we will continue our highly impactful work in CMT family recruitment, exome sequencing and traditional gene identification. In addition, we will expand the genetic studies to whole genome sequencing with a focus on families already explored unsuccessfully in whole exome studies. We further plan to perform the first large rare variant burden analysis in the rare disorder CMT2. This is only possible through the exceptional clinical resources we have built over the past decade. Finally, with many CMT genes available, we will perform statistical network analyses on a CMT-ome to identify gene modules and pathways that will be the starting point of polypharmacology, and provide insight into pathophysiology of peripheral nerve degeneration. All data will be available in real-time to an existing network of CMT investigators worldwide, and deposited in dbGaP annually.

  Study phs003389

• Genomic Profiling of Pediatric B-cell Acute Lymphoblastic Leukemia

  Pediatric leukemia is the most common type of childhood cancer and, despite tremendous progress in treatment, remains the second leading cause of cancer deaths in children. B-cell acute lymphoblastic leukemia (B-ALL) is the most common type of pediatric leukemia. Recent studies using transcriptional profiling of large cohorts of pediatric B-ALL have shown that patients can be grouped into transcriptional subtypes that are often defined by specific driver mutations. Interestingly, many of these mutational subtypes are defined by gene fusions or rearrangements that drive altered expression of transcription factors (ETV6-RUNX1, PAX5, DUX4, TCF3-PBX1, ZNF384) or in chromatin regulatory machinery (KMT2A), suggesting that transcriptional dysregulation is a major driver of B-ALL. While the transcriptional distinctions are clear, the relationship between patients in terms of their chromatin regulatory landscape remains unclear. To address this, we profiled gene expression, open chromatin, and 3D genome folding in patient derived B-ALL samples. We identified that at the level of 3D genome organization, many chromatin interactions and looping events are shared across mutational subtypes, suggesting that shared transcriptional programs, in addition to group specific driver mutations, possibly regulate the chromatin landscape in B-ALL. Using RNA-seq and ATAC-seq data, we were able to identify "latent" signatures of expression related to non-mutant transcription factors (TFs) that also contribute to expression heterogeneity across TF subtypes. These are related to patient specific patterns of 3D genome folding, and in some cases, are predictive of disease outcomes. This study helps shed light on the chromatin landscape in B-ALL and furthers our understanding of the interactions between diverse mutant TFs that drive B-ALL and non-mutant TFs that help shape the B-ALL chromatin landscape.

  Study phs003226

• Recurrent somatic DICER1 mutations in non-epithelial ovarian tumors

  Background: Germline truncating mutations in DICER1, an RNase III-type endoribonuclease essential for processing of microRNAs, are seen in families with the pleuropulmonary blastoma-family tumor and dysplasia syndrome; these individuals have a propensity to develop non-epithelial ovarian tumors (i.e. sex-cord stromal and germ cell tumors). Methods: We sequenced the whole transcriptomes or exomes of 14 non-epithelial ovarian tumors and noted closely clustered mutations in the RNase IIIb domain of DICER1 in four cases. Using Sanger sequencing, we then analyzed additional ovarian tumors for mutations in this region. The impact of the mutations on the enzymatic activity of Dicer1 was determined using in vitro RNA cleavage assays. Results: RNase IIIb domain DICER1 mutations were found in 30/102 non-epithelial ovarian tumors (29%), predominantly Sertoli-Leydig cell tumors (26/43, 60%), including 4/4 from individuals with germline DICER1 mutations. The mutations were restricted to metal binding sites within the RNase IIIb catalytic centres critical for miRNA interaction and cleavage, and were somatic in all 14 cases where germline DNA was available for testing. Of 266 epithelial ovarian and endometrial cancers tested, one case, an ovarian carcinosarcoma, had a hotspot mutation. In vitro, the mutant DICER proteins showed reduced RNase IIIb activity but retained RNase IIIa activity. Conclusions: Somatic missense mutations of the RNase IIIb domain of DICER1 are common in non-epithelial ovarian tumors. Genetic, pathologic, and functional evidence suggest that these mutations do not obliterate DICER1 function, rather, they alter it in specific cell types, a novel mechanism through which perturbed microRNA expression is oncogenic.

  Study EGAS00001000135

• Resolving the Full Spectrum of Human Genome Variation using Linked-Reads

  Large-scale population based analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. Standard short-read approaches, used primarily due to accuracy, throughput and costs, fail to give a complete picture of a genome. They struggle to identify large, balanced structural events, cannot access repetitive regions of the genome and fail to resolve the human genome into its two haplotypes. Here we describe an approach that retains long range information while harnessing the power of short reads. Starting from only 1ng of DNA, we produce barcoded short read libraries. The use of novel informatic approaches allows for the barcoded short reads to be associated with the long molecules of origin producing a novel datatype known as 'Linked-Reads'. This approach allows for simultaneous detection of small and large variants from a single Linked-Read library. We have previously demonstrated the utility of whole genome Linked-Reads (lrWGS) for performing diploid, de novo assembly of individual genomes. In this manuscript, we show the utility of reference based analysis using a single Linked-Read library for full spectrum genome analysis. We demonstrate the ability of Linked-Reads to reconstruct megabase scale haplotypes and to recover parts of the genome that are typically inaccessible to short reads, including phenotypically important genes such as STRC, SMN1 and SMN2. We demonstrate the ability of both lrWGS and Linked-Read Whole Exome Sequencing (lrWES) to identify complex structural variations, including balanced events, single exon deletions, and single exon duplications. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone.

  Study EGAS00001003121

• RNA seq on 19 samples of Radiation-Induced Meningiomas

  Purpose: Majority of pediatric cancers require the irradiation of the central nervous system (CNS), and as more patients survive into adulthood from improved oncological therapy the sequelae of brain radiation are increasing in prevalence. Radiation-induced meningiomas (RIMs), one such secondary effect, demonstrate a clinically more aggressive behaviour than sporadic meningiomas (SMs). We aimed to describe the genomic mutational landscape of RIMs.Methods: We analyzed a principal cohort of 18 RIMs, with 31 RIMs overall, from patients who received childhood radiation therapy and 30 SMs, as a comparator population. We performed a multiplatform integrative genomic analysis; including methylation, whole exome and RNA sequencing. Results: RIMs exhibited a five-fold increase in copy number alterations, commonly the loss of chromosome 1p (17/18 RIMs) and 22q (17/18 RIMs), which was significantly more than observed in sporadic meningiomas. Furthermore, RNA sequencing data revealed an NF2 gene fusion event in 35.3% of RIMs. In all 6 cases, there was a complete NF2 exon spliced into a complete exon of a reciprocal gene, suggesting that the breakpoints of genomic rearrangement are intronic. All tumours with the NF2 fusion also possessed monosomy of chromosome 22q, rendering the cells with homozygous disruption of NF2. Clinically, RIMs with the NF2 fusion exhibited ill-defined borders and a tendency to develop in anatomic frontal location. Also, targeted sequencing panel confirmed that RIMs had fewer nonsynonymous NF2 mutations (6.5% vs. 30% in SM) and absence of mutations in TRAF7, SMO, KLF4, PIK3CA and AKT1, genes traditionally involved in SMs.Conclusion: Our study demonstrates that RIMs have distinct genomic drivers of oncogenesis as compared to SMs, specifically NF2 inactivation through fusion event. Radiation therapy possibly triggers genomic structural rearrangements through error-prone repair of double-stranded DNA breaks.

  Study EGAS00001002318

• Suppressors and activators of JAK-STAT signaling at diagnosis and relapse of acute lymphoblastic leukemia in Down Syndrome

  Children with Down Syndrome (DS) are prone to development of high risk B-cell precursor ALL (DS-ALL) that differs genetically from most sporadic pediatric ALLs. Increased expression of CRLF2, the receptor to thymic stromal lymphopoietin (TSLP) characterizes about half of DS-ALLs and also a subgroup of sporadic “Philadelphia-like ALLs”. To understand the pathogenesis of relapsed DS-ALL we performed integrative genomic analysis of 25 matched diagnosis remission and relapse DS-ALLs. We found that the CRLF2 rearrangements are early events during DS-ALL evolution and generally stable between diagnoses and relapse. Secondary activating signaling events in JAK-STAT/RAS pathway were ubiquitous but highly redundant between diagnosis and relapse, suggesting that signaling is essential but that no specific mutations are “relapse driving”. We further found that activated JAK2 may be naturally suppressed in 25% of CRLF2 positive DS-ALL by loss-of-function aberrations in USP9X, a deubuitinase previously shown to stabilize the activated phosphorylated JAK2. Interrogation of large ALL genomic databases extended our findings up to 25% of CRLF2 positive, “Ph like” ALLs. Pharmacological or genetic inhibition of USP9X as well as treatment with low-dose Ruxolitinib enhanced the survival of pre-B ALL cells overexpressing mutated JAK2. Thus, somehow counterintuitive, we found that suppression of JAK-STAT “hyper-signaling” may be beneficial to leukemic B cell precursors. This and the reduction of JAK mutated clones at relapse suggest that the therapeutic effect of JAK specific inhibitors may be limited. Rather, combined signaling inhibitors or direct targeting of the TSLP receptor may be a useful therapeutic strategy for DS-ALL.

  Study EGAS00001002410

• A reference map of potential determinants for the human serum metabolome

  The collection of metabolites circulating in the human blood, termed the serum metabolome, contains a plethora of biomarkers and causative agents. Although the origin of specific compounds is known, we have a poor understanding of the key determinants of most metabolites. Here, we measured the levels of 1251 circulating metabolites in serum samples from a healthy human cohort of 491 individuals, and devised machine learning algorithms to predict their levels in held-out subjects based on a comprehensive profile consisting of host genetics, gut microbiome, clinical parameters, diet, lifestyle, anthropometric measurements and medication data. Notably, we obtained statistically significant predictions for over 76% of the profiled metabolites. Despite using the strict out-of-sample prediction metric, which is a lower bound for the explained variance, diet and microbiome each explained hundreds of metabolites, with over 50% of the variance explained in some metabolites. We further validated the robustness of the microbiome related associations by showing a high replication rate in two geographically independent cohorts that were not available to us when developing the algorithms. We also demonstrate that some of these interactions are causal, as some metabolites we predicted to be positively associated with bread increased in level following a randomized clinical trial of bread intervention. Microbiome-explained metabolites were enriched with unnamed metabolites, and we devised an algorithm that accurately predicts their biological pathway, finding that they mainly include food components, aromatic amino acids and secondary bile acid derivatives. Overall, our results unravel potential determinants of over 800 metabolites, paving the way towards mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating circulating metabolite levels.

  Study EGAS00001004512

• 18 Whole Exome Sequencing for Radiation Induced-Meningiomas

  Purpose: Majority of pediatric cancers require the irradiation of the central nervous system (CNS), and as more patients survive into adulthood from improved oncological therapy the sequelae of brain radiation are increasing in prevalence. Radiation-induced meningiomas (RIMs), one such secondary effect, demonstrate a clinically more aggressive behaviour than sporadic meningiomas (SMs). We aimed to describe the genomic mutational landscape of RIMs.Methods: We analyzed a principal cohort of 18 RIMs, with 31 RIMs overall, from patients who received childhood radiation therapy and 30 SMs, as a comparator population. We performed a multiplatform integrative genomic analysis; including methylation, whole exome and RNA sequencing. Results: RIMs exhibited a five-fold increase in copy number alterations, commonly the loss of chromosome 1p (17/18 RIMs) and 22q (17/18 RIMs), which was significantly more than observed in sporadic meningiomas. Furthermore, RNA sequencing data revealed an NF2 gene fusion event in 35.3% of RIMs. In all 6 cases, there was a complete NF2 exon spliced into a complete exon of a reciprocal gene, suggesting that the breakpoints of genomic rearrangement are intronic. All tumours with the NF2 fusion also possessed monosomy of chromosome 22q, rendering the cells with homozygous disruption of NF2. Clinically, RIMs with the NF2 fusion exhibited ill-defined borders and a tendency to develop in anatomic frontal location. Also, targeted sequencing panel confirmed that RIMs had fewer nonsynonymous NF2 mutations (6.5% vs. 30% in SM) and absence of mutations in TRAF7, SMO, KLF4, PIK3CA and AKT1, genes traditionally involved in SMs.Conclusion: Our study demonstrates that RIMs have distinct genomic drivers of oncogenesis as compared to SMs, specifically NF2 inactivation through fusion event. Radiation therapy possibly triggers genomic structural rearrangements through error-prone repair of double-stranded DNA breaks.

  Study EGAS00001002317

• DSRCT RNA genomic sequencing

  Purpose: To further understand the molecular pathogenesis of desmoplastic small round cell tumor (DSRCT), a rare but often fatal malignancy occurring primarily in young males, we used next-generation RNA sequencing to investigate the gene expression profiles intrinsic to this disease.Experimental Design: RNA from DSRCT tumor samples were obtained from the Cooperative Human Tissue Network biorepository. RNA sequencing was completed using the Illumina HiSeq 2000 system. Presence of the EWSR1-WT1 fusion was verified using both RNA-sequencing and PCR. Validation studies, including WT1 ChIP-seq, RNA sequencing, and EWS-WT1 knockdown experiments, were performed on an established DSRCT cell line, JN-DSRCT-1. Protein expression of clinically relevant genes determined by RNA sequencing was confirmed using immunohistochemistry. A panel of immune signature genes was also evaluated to identify possible immune therapeutic targets. Results: We analyzed the RNA from 14 tumor samples, of which two were confirmed negative for the diagnostic EWSR1-WT1 translocation. Principal component analysis of the sequencing data indicated that fusion-negative and fusion-positive tumors are transcriptionally distinct entities. Overlapping the significant ChIP-seq peaks with genes found to be highly expressed in the RNA sequencing data revealed that IGF2 and FGFR4 were both highly expressed, and targets of the EWS-WT1 fusion gene. This finding has potential clinical relevance for targeted therapeutic intervention. In addition, we identified the immune checkpoints CD200 and CD276 as potentially targetable genes whose expression is independent of the EWS-WT1 fusion gene in vitro.Conclusions: Despite the transcriptional complexity of this disease, we were able to identify IGF2, FGFR4, CD200, and CD276 as potential therapeutic targets for patients suffering from DSRCT.

  Study EGAS00001002770

• Genetic Risk for Subsequent Neoplasms among Long-term Survivors of Childhood Cancer in the St. Jude Lifetime Cohort

  While childhood cancer survivors are known to be at increased risk of subsequent neoplasms (SNs), the contribution of germline mutations in cancer predisposition genes to the risk of SN is largely unknown. Whole-genome sequencing (30X) was performed on 3,006 5+ year survivors of childhood cancer (median age, 35.8 [range: 7.1-69.8] years) from the St. Jude Lifetime Cohort. Survivors underwent a comprehensive clinical assessment. Germline mutations in 156 cancer predisposition genes (SJCPG156), including a subset of 60 (SJCPG60) autosomal dominant genes with moderate to high penetrance, were classified for their pathogenicity. Piecewise exponential regression, stratified by radiation exposure, was used to evaluate the relative rate (RR) and 95% confidence interval (95% CI) of SN occurrence by mutation status. Pathogenic or likely pathogenic mutations in SJCPG156 and SJCPG60 were identified in 11.7% and 5.8% of survivors, respectively. The most frequently mutated SJCPG60 genes included RB1 (n=43), NF1 (n=22), BRCA2 (n=14), BRCA1 (n=12) and TP53 (n=10). Mutations in SJCPG60 were associated with the rate of subsequent sarcoma (RR, 10.3; 95% CI, 4.2 to 25.6) and breast cancer (RR, 13.3; 95% CI, 5.8 to 30.5) among irradiated survivors, and the rate of developing any SN (RR, 4.8; 95% CI, 2.4 to 9.4) and breast cancer (RR, 7.8; 95% CI, 2.5 to 24.0) among non-irradiated survivors. The rate of developing ≥2 histologically distinct SNs was increased 17.8-fold (95% CI, 3.5 to 89.8) among SJCPG60 mutation carriers treated without radiotherapy. Similar but attenuated associations were observed for mutations in SJCPG156. Survivors who develop a SN without prior radiotherapy or who are diagnosed with a subsequent sarcoma or breast cancer within a site of prior radiotherapy should be referred to genetic counseling.

  Study EGAS00001002499

• SYSCOL Human colorectal cancer project pilot RNA-seq and germline genotyping

  Genotyping by array and Transcriptome profiling by high-throughput sequencing

  Dataset EGAD00001000880

• RNA-seq and WGS data of MB-0152

  Identification of fusion transcripts by RNA-sequencing and Whole genome sequencing of a breast cancer patient sample (METABRIC ID MB-0152)

  Dataset EGAD00001003342

• uganda_autosomes

  Genotype data (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 1391 individuals from EMaBS in Entebbe, Uganda.

  Dataset EGAD00010002578

• Walter and Eliza Hall Institute - University of Melbourne

  Data Access Committee for Gocuk, Lancaster et al. 2024: nanopore sequencing data of patients with choroideremia and X-linked retinitis pigmentosa, to determine X inactivation skew.

  Dac EGAC50000000301

• First in vivo investigation of the impact of PARP inhibition with rucaparib alone and in combination with atezolizumab: results of the phase Ib COUPLET clinical study in advanced gynecologic and triple-negative breast cancers

  Study EGAS00001006100

• Whole Genome Sequencing of Insulinomas

  Whole Genome Sequencing of Insulinomas and paired blood controls from the same patients.

  Study EGAS50000000321

• HUG-CELL ASD Data Access Committee

  Data Access Committee for data generated by projects involving ASD and associated phenotypes by the Human Genome and Stem Cell Research Center (HUG-CELL), University of São Paulo

  Dac EGAC50000000475

• Nanopore whole-genome sequencing of human osteosarcomas

  We performed single and multi-region nanopore whole-genome sequencing on human osteosarcoma samples from adult and paediatric patients.

  Dataset EGAD50000000925

• Nanopore whole genome sequencing data of HG002

  Data generated from single cell, 10 cells, and bulk samples of HG002.

  Study EGAS50000000552

• ADARIO / Targeting ADAR1 in Immuno-Oncology

  RNA editing analyses of BRCA-isogenic cell lines and patient-derived xenografts (PDX)

  Study EGAS50000000518

• HCA_Immune_UAI_Paediatric_Spatial_Managed_Access

  Comparison of immune populations in adenoid tissue in patients with and without history of otitis media

  Study EGAS00001006471

• _RNAseq___Colorectal_organoids_and_tumoroids

  Transcriptome sequencing of tumour tissue, adjacent normal tissue and derived organoids/tumoroids from colorectal cancer

  Study EGAS00001000985

• Mutational_Analysis_of_Colorectal_PDX_models

  Targeted exome sequencing of patient derived xenografts from primary colorectal tumours and liver metastases.

  Study EGAS00001001171

• Illumina HiSeq X Ten

  Three files of patients 10, 11 and 13 with WGS done on Illumina HiSeq X Ten. For research purpose and authorised user only.

  Dataset EGAD00001003439

• (h)MeDIP-Seq of high-risk prostate cancer

  high-throughput sequencing of methylated and hydroxymethylated DNA from tumor and non-tumor tissue of patients with high-risk prostate cancer

  Dataset EGAD00001002010

• Clinical Implications of Genomic Alterations in the Tumour and Circulation of Pancreatic Cancer Patients

  Clinical Implications of Genomic Alterations in the Tumour and Circulation of Pancreatic Cancer Patients

  Dataset EGAD00001001421

• HIV exome pilot, exome data hs37d5

  exome sequence data for 57 HIV elite long term non-progressors and rapid progressors. Complete dataset of improved BAMs mapped to hs37d5 and including phenotype information.

  Dataset EGAD00001003345

• ATAC-Seq of human stimulated and cultured CD4+ Treg cells

  This dataset includes whole genome sequence data for ATAC-seq (42 samples) of human stimulated and cultured CD4+ Treg cells.

  Dataset EGAD00001004829

• Single Cell RNAseq of blood and tumor from renal cancer patients

  Single Cell RNAseq of blood and tumor from renal cancer patients

  Dataset EGAD00001005977

• NanoString gene expression of PBMC from bladder cancer and RCC patients

  This dataset contains NanoString gene expression of PBMC from patients from IMvigor210, IMvigor211 and IMmotion150 cohorts

  Dataset EGAD00001005976

• Single cell sequencing of mild and critical COVID19 PBMC

  Single-cell RNA sequencing of 13 ‘mild-moderate’ and 10 ‘critical’ COVID19 PBMC samples

  Dataset EGAD00001006997

• Additional Sanger Sequencing and qPCR data to PSCNL samples

  Sanger sequencing and RT-qPCR data for validation used in Primary lymphomas of the central nervous system (PCNSL).

  Dataset EGAD00001008583

• Artificial mixtures of sonicated human and mouse DNA at different sizes were sequenced (Nanopore)

  Artificial mixtures of sonicated human and mouse DNA at different sizes were sequenced

  Dataset EGAD00001008981

• Artificial mixtures of sonicated human and mouse DNA at different sizes were sequenced (PacBio)

  Artificial mixtures of sonicated human and mouse DNA at different sizes were sequenced

  Dataset EGAD00001008982

• RNA-Sequencing and Somatic Mutation Status of Adrenocortical Tumors: Novel Pathogenetic Insights

  RNA paired end sequencing of 59 adrenocortical tumors and 4 controls.

  Dataset EGAD00001006258

• EGA metadata schema

  EGA Schemas In this page, you will find information on how the European Genome-phenome Archive (EGA) manages its metadata standards using both XML Schema Definition (XSD) and JavaScript Object Notation (JSON) formats. If you are not sure what this means, you may want to explore our brief metadata introduction. This information may be of your interest if you are planning to learn more about how the EGA is built and how to wrap around it for other processes. Nevertheless, if you are a common user (e.g. submitter or requester), you would not have to worry about these schemas nor their format, since they are implemented in user-friendly ways for you. Metadata standards are rules that define how to format and structure data of metadata objects (i.e. entities), like EGA's samples or experiments in a consistent manner. These objects are the nodes of the metadata model of the EGA (Figure 1). Figure 1. Diagram of EGA's metadata model. The model's building blocks are objects (e.g. sample), which can reference each other (e.g. an experiment referencing the used samples). Once your files are uploaded, they can also be referenced by Runs and Analyses. The submission object is an object itself that compiles many others. At EGA, we inherit our metadata schemas from the European Nucleotide Archive (ENA), and we have expanded them to include bespoke objects such as "Policy", "Dataset", and "DAC" (Data Access Committee) for our specific use-case: handling sensitive human data. See below a list of all our metadata objects and some context for each. Metadata Object EGA accession Description Examples of metadata fields Study EGAS… Information about the study Study type, study title, study abstract… Sample EGAN… Information about the used samples in the experiment or analysis Taxon ID, scientific name, biological sex, phenotype… Experiment EGAX… Information about the performed experiment Used libraries, sequencing platform, reference to the used samples… Analysis EGAZ… Contains information about the analysis Type of analysis, used assembly, reference sequence… Run EGAR… The run holds information about the files containing the raw reads generated in a run of sequencing Platform, spot descriptor, raw file references… DAC EGAC… Contains information about the Data Access Committee (DAC) DAC contacts, contact emails… Policy EGAP… Contains the Data Access Agreement (DAA) and policy which its usage complies with Policy text, data use ontologies (DUO) codes… Dataset EGAD… Contains the collection of runs/analysis to be subject to controlled access Dataset type, compilation of Run's and Analysis' IDs There are two different sets of schemas, based on their formats, in which the EGA accepts metadata: XSDs (for XML files) and JSON Schemas (for JSON files). EGA's XML Schema Definition . When programmatic submissions are pushed through the European Bioinformatics Institute (EBI) system, XML format is used. The schemas that are applied for this format are defined in XML Schema Definition (XSD) files, which can be found at ENA's GitHub repository. You can find more information on how to validate and submit your data programmatically in our programmatic submission documentation. Furthermore, see at our GitHub repository some XML examples with either made-up values (similar to what you would submit) or descriptive values for each field (just for documentation). EGA's JSON Metadata Schemas . When programmatic submissions are pushed through the Centre for Genomic Regulation (CRG) system, JSON format specifications are used instead. See the full JSON specifications for further details. In conclusion, the EGA metadata schemas are crucial for maintaining the quality and consistency of submitted data. By understanding and following the rules outlined in these schemas, you can ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource. Sample checklists Besides the standards in our schemas, we have another layer called Sample checklists. These are another system that the EGA inherits from ENA, and specifies what attributes are required or allowed for a sample object. The EGA uses these checklists to enforce that, for example, a sample object has the three mandatory attributes: subject ID, sex and phenotype of the individual the sample was taken from. When you submit to EGA, our checklist is automatically selected by default.

  Documentation submission/metadata/ega-schema

• Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (UC-GENOME): A Bladder Cancer Advocacy Network (BCAN)-Led Collaborative Research Pilot Study

  UC-GENOME is a real-world cohort of patients with metastatic urothelial carcinoma (UC). The study consisted of two co-equal aims: 1) to provide targeted DNA sequencing for clinical decision making at no cost to patients; and 2) to create a resource for collaborative translational science including a clinically annotated biobank. The submitted data represents the foundational analysis of 218 patients accrued at 7 academic medical centers. The analysis includes 176 patients with both targeted DNA sequencing and RNA sequencing. The genomic data was combined with clinical variables to model response to chemotherapy and immune checkpoint inhibitors (ICI). Due to additional sharing restrictions, data from one site can be found in phs003094.

  Study phs003066

• Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (UC-GENOME): a Bladder Cancer Advocacy Network (BCAN)-Led Collaborative Research Pilot Study - for Samples Collected at Johns Hopkins

  UC-GENOME is a real-world cohort of patients with metastatic urothelial carcinoma (UC). The study consisted of two co-equal aims: 1) to provide targeted DNA sequencing for clinical decision making at no cost to patients; and 2) to create a resource for collaborative translational science including a clinically annotated biobank. The submitted data represents the foundational analysis of 218 patients accrued at 7 academic medical centers. The analysis includes 176 patients with both targeted DNA sequencing and RNA sequencing. The genomic data was combined with clinical variables to model response to chemotherapy and immune checkpoint inhibitors (ICI).The larger dataset for this study can be found in dbGaP study phs003066.

  Study phs003094

• Impaired HLA Class I Antigen Processing and Presentation as a Mechanism of Acquired Resistance to Immune Checkpoint Inhibitors in Lung Cancer

  Mechanisms of acquired resistance to immune checkpoint inhibitors (ICIs) are poorly understood. The purpose of this study was to investigate whether alterations in genes encoding components of the HLA Class I antigen processing and presentation machinery or interferon signaling pathways play a role in acquired resistance to PD-1 or PD-L1 antagonistic antibodies. Whole exome sequencing was performed on tumor samples collected from patients with advanced non-small cell lung cancer at the time of resistance to PD-1 axis inhibitors and on available matched pre-treatment and normal samples. Patient-derived xenografts successfully established from the ICI-resistant samples were also exome sequenced. Additionally, RNA sequencing was performed on cases with sufficient tissue.

  Study phs001464

• Multimodal Profiling of 500,000 Memory T Cells from a Tuberculosis Cohort Identifies Cell State Associations with Demographics, Environment, and Disease

  We conducted CITE-seq to measure whole transcriptome gene expression and surface expression of 31 proteins. We assayed >500K memory T cells from 259 donors from a tuberculosis progression cohort (128 cases: former progressors and 131 controls: non-progresssors/latent infection) >4 years post-infection after returning to immune steady state. We defined 31 memory T cell states influenced by age, sex, genetic ancestry, and season. After correcting for these covariates, we found that one cell state (C-12), resembling the T helper cells Th17s, were depleted in cases compared to controls. When sorted ex vivo, this state responds to polyclonal or Mycobacterium tuberculosis (Mtb) peptide antigen stimulation with interleukin-17 (IL-17) or interferon gamma (IFNg).

  Study phs002467

• Filtering and Annotation of Variants That Are Rare (FAVR)

  The project developed a suite of new methods (FAVR) designed to assist the shortlisting of genetic variants under a rare variant-phenotype/disease model. The methods were designed to work with commonly used massively parallel sequencing analysis pipelines, such as the GATK or ANNOVAR, and have been made publically available as a suite of software tools (https://github.com/bjpop/favr). The FAVR methods use signatures in comparator sequence alignment files to facilitate the filtering of mapping artifacts and common genetic variants, and annotation of genetic variants based on evidence of co-occurrence in individuals. As relevant, FAVR methods can also be used to filter out artifacts derived from imbalanced paired-end sequencing. Pope et al., BMC Bioinformatics, accepted Dec 2012.

  Study phs000601

• Identification of Genomic Markers of Cervical Dystonia and Subtypes

  As the third most common movement disorder, dystonias collectively affect more than 2 million people worldwide. Despite their high prevalence, their biological roots are largely unknown. Genetic influences are suggested in familial studies, however, no specific genetic variants are responsible for a significant proportion of identified cases. Previous genome-wide association studies of the dystonias were limited by smaller sample size and lack of coverage of rare variants. In this study, we use a high-throughput genomic approach to effectively investigate relationships between over genome-wide genetic variations and dystonias. We conduct targeted analyses of candidate genes, as well as agnostic searches for any genomic with the dystonias and subtypes in a large sample of dystonia patients available.

  Study phs001803

• Multi-Modal Single-Cell and Whole-Genome Sequencing of Small, Frozen Clinical Specimens

  Clinical application of single-cell sequencing technologies has been hampered by their need for quick processing of relatively large, fresh specimens. Here, we benchmarked the performance of a new technique for single-cell sequencing from snap-frozen clinical samples, vs. sequencing from fresh samples, on 5 samples from cutaneous melanoma brain metastasis, 6 samples from NSCLC brain metastasis, and 3 from uveal melanoma primary tumor. Additionally, we performed frozen sample sequencing of 20 uveal melanoma liver metastasis samples, and 3 cutaneous melanoma extracranial metastasis samples. Finally, for selected groups of the above-mentioned samples, we also performed TCR sequencing, SlideSeqV2 spatial transcriptomics, ultra-shallow whole-genome sequencing, and whole-exome sequencing, to present a comprehensive multi-modal profiling of all datasets.

  Study phs003097