11196 results for "fc coins to buy Visit Buyfc26coins.com FC 26 kolikoni ilmestyivät juuri kun pelasin. Täydellinen ajoitus!.iZqe"

in 121.03 milliseconds.

• Genome-Wide Association Study of Heparin-Induced Thrombocytopenia

  Heparin-induced thrombocytopenia (HIT) is an unpredictable, potentially catastrophic adverse effect resulting from an immune response to platelet factor 4 (PF4)/heparin complexes. We performed a genome-wide association study (GWAS) with positive functional assay as the outcome. Genetic associations were investigated in a cohort of functional assay-confirmed HIT cases, antibody-positive (function assay-negative) controls, and antibody negative controls. Both PF4-specific enzyme-linked immunosorbent assay (ELISA) and serotonin release assay (SRA) were positive in every HIT case. GWAS genotyping was performed at the Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences (IMS). All samples in the discovery and replication cohorts were genotyped using the lllumina® Infinium HumanOmniExpressExome BeadChip, which contains 958,497 markers, including 273,000 functional exonic markers. Quality control was accomplished using sample and marker call rate ≥98%, sex mismatch, duplicate concordance, and removal of related samples through identity by descent. Genomic imputation was performed for samples using Minimac4 and the phase3 v5 reference panel data from the 1000 genomes project. The primary GWAS analysis used multivariable logistic regression assuming an additive genetic model with functional assay-confirmed case status as the outcome. Both PF4/heparin antibody negative and antibody positive controls were considered controls in the primary analysis. Logistic regressions were used to generate odds ratios and 95% confidence intervals (95%CIs) after adjustment for age, sex, and first three principal components.

  Study phs002863

• The Haplotype-Resolved Genome and Epigenome of the Aneuploid HeLa Cancer Cell Line

  The genomic architecture of HeLa remains largely unexplored beyond its karyotype, partly because like many cancers, its extensive aneuploidy renders such analyses challenging. We carried out haplotype-resolved whole-genome sequencing of the HeLa CCL-2 strain, examined point- and indel-mutation variations, mapped copy-number variations and loss of heterozygosity regions, and phased variants across full chromosome arms. We also investigated variation and copy-number profiles for HeLa S3 and eight additional strains. We find that HeLa is relatively stable in terms of point variation, with few new mutations accumulating after early passaging. Haplotype resolution facilitated reconstruction of an amplified, highly rearranged region of chromosome 8q24.21 at which integration of the human papilloma virus type 18 (HPV-18) genome occurred and that is likely to be the event that initiated tumorigenesis. We combined these maps with RNA-seq and ENCODE Project data sets to phase the HeLa epigenome. This revealed strong, haplotype specific activation of the proto-oncogene MYC by the integrated HPV-18 genome approximately 500 kilobases upstream, and enabled global analyses of the relationship between gene dosage and expression. These data provide an extensively phased, high-quality reference genome for past and future experiments relying on HeLa, and demonstrate the value of haplotype resolution for characterizing cancer genomes and epigenomes. Reprinted from Adey et. al. 2013, Nature, with permission from Nature Publishing Group.

  Study phs000642

• Genomic characterization of retinoblastoma (targeted sequencing)

  Retinoblastoma is the most frequent intraocular malignancy in children, originating from a maturing cone precursor in the developing retina. Little is known on the molecular basis underlying the biological and clinical behavior of this cancer. Here, using multi-omics data, we demonstrate the existence of two retinoblastoma subtypes. Subtype 1, of earlier onset, includes most of the heritable forms. It harbors few genetic alterations other than the initiating RB1 inactivation and corresponds to differentiated tumors expressing mature cone markers. By contrast, subtype 2 tumors harbor frequent recurrent genetic alterations including MYCN-amplification. They express markers of less differentiated cone together with neuronal/ganglion cell markers with marked inter- and intra-tumor heterogeneity. The cone dedifferentiation in subtype 2 is associated with stemness features including low immune and interferon response, E2F and MYC/MYCN activation and a higher propensity for metastasis. The recognition of these two subtypes, one maintaining a cone-differentiated state, and the other, more aggressive, associated with cone dedifferentiation and expression of neuronal markers, opens up important biological and clinical perspectives for retinoblastomas. In this study, we performed targeted sequencing of the exonic regions of RB1, BCOR and ARID1A on 37 samples from the series of 102 retinoblastomas. Among them, 23 samples were not subjected to whole-exome sequencing, and 14 samples have the whole-exome sequencing data (deposited in EGAS00001005248).

  Study EGAS00001005550

• Papuan Y chromosome Diversity Panel

  Island Southeast Asia and Oceania host one of the world’s richest assemblages of human phenotypic, linguistic and cultural diversity. Despite this, the region’s male genetic lineages are globally among the last to remain unresolved. We compiled ~9.7 Mb of Y chromosome sequence from a diverse sample of over 380 men from this region, including 152 first reported here. The granularity of this dataset allows us to fully resolve and date the regional Y chromosome phylogeny. This new high-resolution tree confirms two main population bursts: multiple rapid diversifications following the region’s initial settlement ~50 kya, and extensive expansions <6 kya. Notably, ~40-25 kya the deep rooting local lineages of C-M130, M-P256, and S-B254 show almost no further branching events in Island Southeast Asia, New Guinea and Australia, matching a similar pause in diversification seen in maternal mitochondrial DNA lineages. The main local lineages start diversifying ~25 kya, at the time of the Last Glacial Maximum. This improved Y chromosome topology highlights localized events with important historical implications, including pre-Holocene contact between Mainland and Island Southeast Asia, potential interactions between Australia and the Papuan world, and a sustained period of diversification following the flooding of the ancient Sunda and Sahul continents as the insular landscape observed today formed. The high-resolution phylogeny of the Y chromosome presented here thus enables a detailed exploration of

  Study EGAS00001006025

• Human Pancreatic Islet RNAseq - Lund

  Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.

  Study EGAS00001004042

• Phenotyping data on human pancreatic islets from 191 donors - Lund

  Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.

  Study EGAS00001004056

• Enrichment of oral-derived bacteria in inflamed colorectal tumors and distinct associations of Fusobacterium in the mesenchymal subtype

  The association between colorectal cancer (CRC) clinical variables and Fusobacterium, but not other intra-tumoral bacteria, has been extensively studied. Here we leveraged whole-transcriptome sequencing from 807 CRC tumor samples from the AVANT phase III trial to dually characterize tumor gene expression and intra-tumoral bacteria. After stringent filtering, 74 high-confidence taxa were identified. 17 of these species, including 4 Fusobacterium spp., were classified as orally-derived and had a robust signal within right-sided, MSI-H, and BRAF mutant tumors. Across consensus molecular subtypes (CMS), integration of Fusobacterium animalis presence and tumor gene expression revealed that F. animalis had the greatest number of associations in mesenchymal CMS4 tumors, despite an overall lower prevalence than in immune CMS1 tumors. Pathway analysis within CMS4 revealed that F. animalis, but not other highly prevalent species, was uniquely associated with pathways for collagen degradation and formation as well as IL-6 and IL-1 cytokine signaling. These associations could explain in part why Fusobacterium has been previously associated with reduced survival in mesenchymal populations. Overall, this study identified oral-derived bacteria, including Fusobacterium, as broadly more prevalent in inflamed CRC tumors compared to the other subtypes, and the association of intra-tumoral bacteria on tumor gene expression is context- and species-specific.

  Study EGAS00001006757

• RNA-sequencing of six Pilocytic astrocytoma tumors

  Pilocytic astrocytoma (PA) is the most common pediatric brain tumor. A recurrent feature of PA is deregulation of the mitogen activated protein kinase (MAPK) pathway most often through KIAA1549-BRAF fusion, but also by other BRAF- or RAF1-gene fusions and point mutations (e.g. BRAFV600E). These features may serve as diagnostic and prognostic markers, and also facilitate development of targeted therapy. The aim of this study was to characterize the genetic alterations underlying the development of PA tumor in six cases, and evaluate methods for fusion oncogene detection. Using a combined analysis of RNA sequencing and copy number variation data we identified a new BRAF fusion involving the 5’ gene fusion partner GTF2I (7q11.23), not previously described in PA. The novel GTF2I-BRAF 19-10 fusion was found in one case, while the other five cases harbored the frequent KIAA1549-BRAF 16-9 fusion gene. Comparing fusion detection methods, Fluorescence in situ hybridization with BRAF break apart probe was the most sensitive method for detection of the two different BRAF rearrangements (GTF2I-BRAF and KIAA1549-BRAF). Our finding of a novel BRAF fusion in PA further emphasis the important role of B-Raf in tumorigenesis of these tumor types. Also, the growing list of BRAF/RAF gene fusions suggests these to be informative tumor markers in molecular diagnostics, which could guide future treatment strategies.

  Study EGAS00001002149

• GWAS data on human pancreatic islets from 191 donors - Lund

  Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.

  Study EGAS00001004044

• GENETIC HISTORY OF ITALY

  Recent scientific literature has highlighted the relevance of population genetic studies both for disease association-mapping in admixed populations and for understanding the history of human migrations. Deeper insight into the history of Italian population is critical for understanding the peopling of Europe. Because of its crucial position at the centre of the Mediterranean basin, the Italian peninsula has experienced a complex history of colonization and migration, whose genetic signatures are still present in contemporary Italians. In this study, we investigated genomic variation in the Italian population using 2.5 million single nucleotide polymorphisms (SNPs) in a sample of more than 300 unrelated Italian subjects with well-defined geographical origins. We combined several analytical approaches to interpret genome-wide data on 1,272 individuals from European, Middle Eastern, and North African populations. We detected three major ancestral components contributing different proportions across the Italian peninsula, and signatures of continuous gene flow within Italy, which has produced remarkable genetic variability among contemporary Italians. In addition, we have extracted novel details about the Italian population’s ancestry: we identified genetic signatures of major historical events in Europe and the Mediterranean basin from the Neolithic (e.g., peopling of Sardinia) to recent times (e.g., ‘barbarian invasion’ of Northern and Central Italy). These results are valuable for further genetic, epidemiological and forensic studies in Italy and in Europe.

  Study EGAS00001001458

• Comprehensive analysis of atypical teratoid rhabdoid tumour (ATRT) using genomic, epigenomic and transcriptomic techniques.

  ATRTs (Atypical teratoid rhabdoid tumours) represent one of the most aggressive pediatric brain cancers, but intriguingly exhibit few other recurrently mutated loci except for SMARCB1/hSNF5. We integrated whole genome (n=15), exome, copy number, gene expression and methylation analyses to comprehensively interrogate 64 ATRTs and observed that structural events were relatively frequent in the ATRT genome (~3 tumour). In addition to SMARCB1, which was targeted by structural events in a majority (49/64) of tumours, recurrent structural alterations targeting the LRP1B, CDH13, BCR and MKL1 loci were observed. We observed novel translocation events, including 2 targeting SMARCB1 which were detected only by NGS analyses. Significantly, integration of gene expression and methylation profiles with genomic analyses revealed ATRT comprise two sub-groups with distinct clinical and genetic features. Group 1 tumours were characterized by supra-tentorial brain location, focal intragenic alterations of SMARCB1 and a pro-neural gene expression signature with evidence of NOTCH pathway activation. While Group 2 ATRTs were characterized by infra-tentorial brain location, broad SMARCB1 alterations and an activation of the BMP signalling pathway. Our findings highlight epigenetic mechanisms as important determinants of ATRT tumour phenotypes, and demonstrate for the first time that ATRTs arising in different anatomical compartments comprise distinct molecular and therapeutic sub-groups.

  Study EGAS00001000506

• An Empirical Approach Leveraging Tumorgrafts to Dissect the Tumor Microenvironment in Renal Cell Carcinoma Identifies Missing Link to Prognostic Inflammatory Factors

  We undertook an empirical approach to dissect the tumor microenvironment by developing a bulk tumor dissection algorithm, DisHet, and leveraging RNA-Seq data of tumorgrafts (patient-derived tumors implanted in mice), in which only the tumor cell component expands. We found that approximately 65% of previously defined immune signature genes are not abundantly expressed in the Renal Cell Carcinoma (RCC) microenvironment, and we identified more than two times as many novel immune/stromal transcripts. By using refined immune/stroma-specific genes and genomics, electronic medical record data and imaging data of 1084 RCC patients, we discovered a highly-inflamed pan-RCC subtype enriched for Treg cells, NK cells, Th1 cells, neutrophils, macrophages, B cells, and CD8+ T cells. This inflamed subtype (IS) is enriched for aggressive RCCs, including BAP1-deficient clear-cell and type 2 papillary tumors. Interestingly, IS is correlated with systemic manifestations of inflammation in patients such as thrombocytosis and anemia, whose pathogenesis were poorly defined and have been predictors of poor prognosis in RCC. Indeed, we discovered that IS is a strong predictor of poor survival. Lastly, our analyses show that tumor cells may drive stromal immune response. Overall, these data provide a missing link between the tumor cells, the tumor microenvironment, and systemic factors.

  Study EGAS00001002786

• The neo-open reading frame peptides that comprise the tumor framome are a rich source of neoantigens for cancer immunotherapy

  Identification of immunogenic cancer neoantigens as targets for therapy is challenging. Here, we integrate whole genome and long-read transcript sequencing of cancers to identify the collection of neo-open reading frame peptides (NOPs) expressed in tumors. We termed this collection of NOPs the tumor framome. NOPs represent tumor-specific peptides that are different from wild-type proteins and may be strongly immunogenic. We describe a class of hidden NOPs that derive from structural genomic variants involving an upstream protein coding gene driving expression and translation of non-coding regions of the genome downstream of a rearrangement breakpoint, i.e. where no gene annotation or evidence for transcription exists. The entire collection of NOPs represents a vast number of possible neoantigens particularly in tumors with many structural genomic variants and a low number of missense mutations. We show that NOPs are immunogenic and epitopes derived from NOPs can bind to MHC class I molecules. Finally, we provide evidence for the presence of memory T cells specific for hidden NOPs in peripheral blood from a patient with lung cancer. This work highlights NOPs as a major source of possible neoantigens for personalized cancer immunotherapy and provides a rationale for analyzing the complete cancer genome and transcriptome as a basis for detection of NOPs.

  Study EGAS00001006021

• PAX5 biallelic genomic alterations define a novel subgroup of B cell precursor acute lymphoblastic leukemia

  Chromosomal rearrangements and specific aneuploidy patterns are initiating events and define subgroups in B cell precursor acute lymphoblastic leukemia (BCP-ALL). Here we analyzed 250 BCP-ALL cases and identified a novel subgroup (‘PAX5-plus’, n=19) by distinct DNA methylation and gene expression profiles. All patients in this subgroup harbored mutations in the B-lineage transcription factor PAX5, with p.P80R as hotspot. Mutations either affected two independent codons, consistent with compound heterozygosity, or suffered LOH predominantly through chromosome 9p aberrations. These biallelic events resulted in disruption of PAX5 transcriptional programs regulating B cell differentiation and tumor suppressor functions. Homozygous CDKN2A/B deletions and RAS activating hotspot mutations were highly enriched as cooperating events in the genomic profile of PAX5-plus ALL. Together this defined a specific pattern of triple alterations, exclusive to the novel subgroup. PAX5-plus ALL was observed in pediatric and adult patients. Although restricted by the limited sample size, a tendency for more favorable clinical outcome was observed with 10 of 12 adult PAX5-plus patients achieving long-term survival. PAX5-plus represents the first BCP-ALL subgroup defined by sequence alterations in contrast to gross chromosomal events and exemplifies how deregulated differentiation (PAX5), impaired cell cycle control (CDKN2A/B) together with sustained proliferative signaling (RAS) cooperatively drives leukemogenesis.

  Study EGAS00001003209

• Epigenetic profiling of human CD4+ memory T cells reveals their proliferative history and argues in favor of a progressive differentiation model driven by epigenetically controlled master regulators.

  A key element of adaptive immunity is the development of long-lived memory cells, which protect against recurring infection by providing a highly enriched pool of antigen-specific cells ready to react to the pathogen. Different classes of memory T cells occur upon primary activation of naive T cells, however, their detailed differentiation pathway is not entirely clear. As part of the IHEC consortium, we generated genome-wide epigenetic maps of a number of CD4+ T cell memory (Tmem) stages including rare subsets such as terminally differentiated (TEMRA) and bone marrow-resident Tmem. We found that CD4+ T cells show progressive global DNA demethylation with differentiation into memory stages, which reflects their proliferative history and likely indicates their decline in differentiation and proliferation potential. Furthermore, transcriptomic profiling combined with co-regulation network analyses arranged different Tmem subsets into a successive differentiation pathway. In addition, we identified a number of epigenetically controlled candidate master regulators for Tmem formation, of which we functionally validated a new methylation-sensitive promoter for the known 'naive-keeper' transcription factor Foxp1. Our study highlights the power of epigenomic datasets in the elucidation of the cellular history but also of the functional potential of T cell populations including the identification of epigenetically controlled master regulators.

  Study EGAS00001001624

• Glioblastoma epigenome profiling identifies SOX10 as a master regulator of molecular tumour subtype

  Glioblastoma in adult patients are classified into four subtypes, IDH, MES, RTK I, and RTK II, based on DNA methylation and RNA expression data. Tumour subtype transitions commonly occur during the treatment of glioblastoma patients, and transitions to the mesenchymal (MES) subtype have been associated with therapy resistance and adverse prognosis. Here, we generate DNA methylome and histone modification data of glioblastoma primary tumours and show that glioblastoma subtypes differ by their enhancer landscapes. Using Core Regulatory Circuitry analysis of H3K27ac data, and independent analysis of RNA-derived gene regulatory networks, we identified 38 subtype master regulators whose cell type-specific activities we mapped in single-cell RNA sequencing data. These analyses identified the chromatin modifier SRY-Box 10 (SOX10) as a master regulator in tumours of the RTK I subtype. In functional studies we demonstrate that SOX10 loss causes a transition of RTK I tumour cells to a mesenchymal cellular state by altering the accessibility of enhancer-rich chromatin regions and their occupancy by Bromodomain Containing 4 (BRD4), a dynamic constituent of super-enhancers. Treatment with the BRD4 inhibitor JQ1 blocked this transition. These data demonstrate the fundamental role of enhancer chromatin remodelling and master regulator activity in the establishment, maintenance and plasticity of glioblastoma cellular states. We also make our data publically browsable at https://dkfz-b060.github.io/gb_browse/

  Study EGAS00001003953

• SG Peranakan Project: Genetic admixture in the culturally unique Peranakan Chinese population in Southeast Asia

  The Peranakan Chinese are culturally unique descendants of immigrants from China who settled in the Malay Archipelago ~300-500 years ago. Today, among large communities in Southeast Asia, the Peranakans have preserved Chinese traditions with strong influence from the local indigenous Malays. Yet, whether or to what extent genetic admixture co-occurred with the cultural mixture has been a topic of ongoing debate. We performed whole-genome sequencing (WGS) on 177 Singapore (SG) Peranakans and analyzed the data jointly with WGS data of Asian and European populations. We estimated that Peranakan Chinese inherited ~5.62% (95% confidence interval [CI]: 4.75-6.46%) Malay ancestry, much higher than that in SG Chinese (1.08%, 0.69-1.53%), southern Chinese (0.86%, 0.57-1.31%), and northern Chinese (0.25%, 0.18-0.33%). A sex-biased admixture history, in which the Malay ancestry was contributed primarily by females, was supported by X chromosomal variants, and mitochondrial (MT) and Y haplogroups. Finally, we identified an ancient admixture event shared by Peranakan Chinese and SG Chinese ~1,612 (95% CI: 1,345-1,923) years ago, coinciding with the settlement history of Han Chinese in southern China, apart from the recent admixture event with Malays unique to Peranakan Chinese ~190 (159-213) years ago. These findings greatly advance our understanding of the dispersal history of Chinese and their interaction with indigenous populations in Southeast Asia.

  Study EGAS00001005379

• ATAC-Seq of CD4 T cell subsets

  Blood samples were taken from 4 age-matched healthy volunteers (two males and two females), and naïve CD4 T cells were isolated using the naïve CD4+ T Cell Isolation Kit II, human (Miltenyi Biotec). Two hundred thousand cells were plated in a 96-well plate, activated with Dynabeads Human T-activator CD3/CD28 (bead-to-cell ratio of 1:1, as recommended by the manufacturer) (ThermoFisher Scientific) and polarized towards CD4 T cell subtypes (Teff, Th1, Th2, rTh17, pTh17, and Treg cells) with specific cocktails of recombinant cytokines and neutralizing antibodies (see details in the material and methods) for each subset. At day 4 post-stimulation, forty thousand cells were used to perform ATAC-Seq on CD4 T cell subtypes. Again, crude nuclei of live CD4+ T cell subsets were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry.

  Study EGAS00001007345

• Towards standardized whole exome sequencing (WES) for cancer patients: lessons from a multicentric pilot study

  A growing number of druggable targets and national initiatives for precision oncology necessitate broader genomic profiling for many cancer patients. Whole exome sequencing (WES) offers unbiased analysis of the entire coding sequence, segmentation-based detection of copy number alterations (CNAs), and accurate determination of complex biomarkers including tumor mutational burden (TMB), homologous recombination repair deficiency (HRD), and microsatellite instability (MSI). To assess the inter-institution variability of clinical WES, we performed a comparative pilot study between German Centers of Personalized Medicine (ZPMs) from five participating institutions. Tumor and matched normal DNA from 30 patients were analyzed using custom sequencing protocols and bioinformatic pipelines. Calling of somatic variants was highly concordant with a sensitivity between 91-95% and a positive predictive value (PPV) of 82-95% compared with a three-institution consensus and full agreement for 16 of 17 druggable targets. Deviations were observed for cases with low VAF or coverage, differing annotations, and different filter protocols. CNAs showed overall agreement in 76% for the genomic sequence with high wet-lab variability. Complex biomarkers correlated strongly between institutions (HRD: 0.79-1, TMB: 0.97-0.99) and all institutions agreed on microsatellite instability. This study will contribute to the development of quality control frameworks for comprehensive genomic profiling and sheds light onto parameters that require stringent standardization.

  Study EGAS00001007363

• Prognostic relevance of microenvironmental factors CD163 and CD8 combined with EZH2 and chromosome 18 gain in a validation cohort of follicular lymphoma patients of the Lunenburg Lymphoma Biomarker Consortium

  Background: In follicular lymphoma (FL), studies addressing the prognostic value of microenvironment-related immunohistochemical (IHC) markers and tumor cell-related genetic markers have yielded conflicting results, precluding implementation in practice. Therefore, the Lunenburg Lymphoma Biomarker Consortium (LLBC) performed a validation study for published markers. Methods: To maximize sensitivity, an end-of-spectrum design was applied for 122 uniformly immunochemotherapy-treated FL patients retrieved from international trials and registries; early failure (EF): progression or lymphoma-related death <2 years versus long remission: response duration of >5 years. IHC staining for T-cells and macrophages was performed on tissue microarrays from initial biopsy and scored with a validated computer-assisted protocol. Shallow whole-genome and deep targeted sequencing was performed on the same samples. Results: 96/122 cases with complete molecular and immunohistochemical data were included in the analysis. EZH2 wild-type (p=0.006), gain of chromosome 18 (p=0.002), low percentages of CD8+ cells (p=0.011) and CD163+ areas (p=0.038) were associated with EF. No significant differences in other markers were observed, thereby refuting previous claims on their prognostic significance. Conclusion: Using an optimized study design, this LLBC study validates wild-type EZH2 status, gain of chromosome 18, low percentages of CD8+ cells and CD163+ area as predictors of EF to immunochemotherapy in FL.

  Study EGAS00001002049

• Neurodevelopmental Genomics: Trajectories of Complex Phenotypes

  This study is a collaboration between the Center for Applied Genomics (CAG) at Children's Hospital of Philadelphia (CHOP) and the Brain Behavior Laboratory at the University of Pennsylvania (Penn). The cohort consists of youths aged 8-21 years who consulted the CHOP network and volunteered to participate in genomic studies of complex pediatric disorders. All participants underwent clinical assessment, including a neuropsychiatric structured interview and review of electronic medical records. They were also administered a neuroscience based computerized neurocognitive battery (CNB) and a subsample underwent neuroimaging. These are described separately below. Clinical Testing: GOASSESS, a computerized, structured screener developed from a modified version of the Kiddie-Schedule for Affective Disorders and Schizophrenia (K-SADS, Kaufman et al. 1997, PMID: 9204677). Components of the interview include a timeline of life events, demographics and medical history, Global Assessment of Functioning, and Interviewer Observations. A psychopathology symptom and criterion-related assessment of mood disorders (depression, mania/hypomania), anxiety disorders (overanxious/generalized-, separation-, social-anxiety, specific phobia, panic disorder, agoraphobia, obsessive compulsive disorder, post-traumatic stress disorder), behavioral disorders (attention deficit hyperactivity disorder, oppositional defiant disorder, conduct disorder), psychosis spectrum (psychosis and prodromal symptoms), eating disorders, suicidal thinking and behavior, and treatment history. This is also based on K-SADS. An abbreviated Family Interview for Genetics Studies (FIGS) to assess major domains of psychopathology in the proband's first-degree relatives. Computerized Neurocognitive Battery: The CNB, developed for large-scale studies, yields measures of accuracy and speed for domains of executive-control functions (abstraction, attention, working memory), episodic memory (verbal, facial, spatial), complex cognitive processing (language reasoning, nonverbal reasoning, spatial processing), social cognition (emotion identification, emotion intensity differentiation, age differentiation) and sensorimotor and motor speed. The following neurobehavioral domains were assessed: Penn Conditional Exclusion Test is a measure of abstraction and concept formation. Participants decide which of 4 objects does not belong with the other 3, based on one of three sorting principles, which change. Feedback is used. Attention: The Penn Continuous Performance Test. Participants respond to a set of 7-segment displays whenever they form a digit or letter. Working Memory: The Letter N-back Test displays sequences of uppercase letters with a stimulus duration of 500 ms (ISI 2,500 ms.) In the 0-back condition, participants respond to a single target (i.e., X). In the 1-back condition they respond if the letter is identical to that preceding it. In the 2-back condition, they respond if the letter is identical to that presented two trials back. Verbal Memory: The Penn Word Memory Test presents 20 target words that are then mixed with 20 distracters equated for frequency, length, concreteness and low imageability. A 20 min delayed recall procedure is also administered. Face Memory: The Penn Face Memory Test presents 20 digitized faces that are then mixed with 20 distracters equated for age, gender and ethnicity. The procedure is repeated at 20 min delay. Spatial Memory: The Visual Object Learning Test uses Euclidean shapes as stimuli with the same paradigm as the word and face. Language and Analogical Reasoning: The Penn Verbal Reasoning consists of verbal analogy problems. Spatial Processing: Penn Line Orientation Test presents two lines at an angle, and participants click on a button that makes one line rotate until it has the same angle as the other. Emotion Processing: Facial displays of 4 emotions (Happy, Sad, Anger, Fear) and Neutral faces, 8 each, are presented and the subject identifies the emotion in a multiple-choice format. The facial stimuli are balanced for gender, age, and ethnicity. Sensory-motor Processing Speed: The task requires moving the mouse and clicking on a green square that disappears after the click. The square gets increasingly small and appears in unpredictable locations. Neuroimaging Protocol: Studies were performed at Penn using a Siemens Trio (Erlangen, Germany) 3T scanner equipped with 40mT/m gradients and 200 mT/m/s slew-rates. RF transmission utilized a quadrature body-coil, and reception a 12-channel head coil optimized for parallel imaging. Total image acquisition time was about 45 min. Structural Imaging: The T1-weighted protocol utilized a 3D, inversion-recovery, and magnetization-prepared rapid acquisition gradient echo. Relevant imaging procedures include: Structural magnetic imaging Diffusion tensor imaging ASL perfusion BOLD fMRI Neuroimaging tasks: Fractal N-Back Task of Spatial Working Memory Face Emotion Identification Task Neuroimages: The current data release includes over 9700 MRI images that may be downloaded through Authorized Access.

  Study phs000607

• CIDR: The Role of Rare Coding Variation in Prostate Cancer in Men of African Ancestry - RESPOND Project 2

  In RESPOND Project 2, we seek to identify rare genetic factors that are associated with prostate cancer (PCa) risk and aggressiveness in men of African ancestry (AA). We will conduct exome sequencing of 15,000 prostate cancer cases and 5,000 controls from the RESPOND cohort and the African Ancestry Prostate Cancer Consortium (AAPC) with cases selected based on risk categories: high-risk (stage T3/T4 or Gleason 8+ or PSA>20 ng/ml), intermediate-risk (stage T2b/T2c or Gleason 7 or PSA 10-20 ng/ml) and low-risk disease (stage T1/T2a and Gleason ≤ 6 and PSA<10 ng/ml). We expect the findings from this Project to significantly advance knowledge of susceptibility to aggressive PCa and racial/ethnic disparities in PCa risk, and to guide the development of future preventive, early detection and prognostic measures for AA men. The first phase of the study will include exome sequence data for approximately 7,500 cases and 5,000 controls from AAPC. The second phase of the study will include exome data for 5,000 cases from RESPOND and AAPC.ACKNOWLEDGMENTS and CONTRIBUTING SITES Multiethnic Cohort (MEC): The MEC and the genotyping in this study were supported by National Institutes of Health (NIH) grants CA63464, CA54281, CA1326792, CA148085, and HG004726. Cancer incidence data for the MEC and Los Angeles Study of Aggressive Prostate Cancer (LAAPC) studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with federal funds from the National Cancer Institute (NCI)/NIH/Department of Health and Human Services (DHHS) under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the Centers for Disease Control and Prevention (CDC). Ghana Prostate Study (GPS): The Ghana Prostate Study was funded by the Intramural Program of the NCI/NIH/DHHS under Contract No. HHSN261200800001E. Men of African Descent and Carcinoma of the Prostate (MADCaP): We thank all MADCaP study participants. This work is a product of the MADCaP network. This work was supported by NCI/NIH grant U01CA184374 to Timothy Rebbeck and National Institute of General Medical Sciences (NIGMS) MIRA grant R35GM133727 to Joseph Lachance. Additional funding includes a seed grant from the Integrated Cancer Research Center at Georgia Institute of Technology. UGANDA: The UGANDA study was supported by NIH grant R01CA165862. Southern Community Cohort (SCCS) is funded by NIH grant CA092447. SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt Ingram Cancer Center (CA68485). Data on SCCS cancer cases were provided by Alabama Statewide Cancer Registry, Kentucky Cancer Registry, Office of Cancer Surveillance at Tennessee Department of Health, Florida Cancer Data System, Central Cancer Registry at North Carolina Division of Public Health, Georgia Comprehensive Cancer Registry, Louisiana Tumor Registry, Mississippi Cancer Registry, South Carolina Central Cancer Registry, Virginia Cancer Registry at Virginia Department of Health, and Cancer Registry at Arkansas Department of Health. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries (NPCR)/Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the NPCR/CDC. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. Karuprostate: The Karuprostate study was supported by the French National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la Prostate. Séverine Ferdinand, Marc Romana. The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. We would also like to acknowledge the UNC BioSpecimen Facility and the LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). Gene-Environment Interaction in Prostate Study (GECAP) was supported by NIH grant ES011126. King County Prostate Cancer Study (KCPCS) was supported by NIH grants CA056678, CA082664, and CA092579, with additional support from the Fred Hutchinson Cancer Research Center. We thank the participants in these studies, and Ms. Suzanne Kolb for help with study management. The Los Angeles Study of Aggressive Prostate Cancer (LAAPC) was funded by grant 99-00524V-10258 from the Cancer Research Fund, under Interagency Agreement #97-12013 (University of California contract #98-00924V) with the Department of Health Services Cancer Research Program. Cancer incidence data for the MEC and LAAPC studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with Federal funds from the NCI/NIH/DHHS under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the CDC. Prostate Cancer Studies at MD Anderson (MDA) was supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388.

  Study phs002637

• DAC of "Gene expression adaptation of metastases to their host tissue"

  The DAC consists of Prof. Axel Hillmer, University of Cologne, Faculty of Medicine and University Hospital Cologne, Institute of Pathology, Cologne, Germany, e-mail: ahillmer@uni-koeln.de and Prof. Andreas Beyer, University of Cologne, Faculty of Mathematics and Natural Sciences, Cologne Excellence Cluster for Aging and Aging-Associated Diseases (CECAD), Cologne, Germany, e-mail: andreas.beyer@uni-koeln.de

  Dac EGAC50000000514

• Single-Cell Profiling of the Human Endometrium in Polycystic Ovary Syndrome: Uncovering Disease Signatures and Treatment Responses

  Single-nuclei map of human endometrial biopsies from women with and without PCOS to identify cell-type-specific disease signatures, compositional variations, and transcriptomic reversibility after a 16-week intervention with metformin or lifestyle. Single nuclei were extracted from 27 frozen endometrial biopsies for snRNA-seq using the 10X Genomics protocol.

  Dac EGAC50000000468

• GeoMx digital spatial profiling of NGS mRNA expression in pre-treatment biopsies from patients.

  This DAC is created to define the data controller (the person that determines the purposes for which and the means by which personal data is processed) for the following study: GeoMx digital spatial profiling of NGS mRNA expression in pre-treatment biopsies from patients with metastatic triple-negative breast cancer treated with PARP inhibitors.

  Dac EGAC50000000774

• Data Access Committee for Maurice Lab - UMC Utrecht

  The Data Access Committee of the Maurice lab at the Center for Molecular Medicine, University Medical Center Utrecht, is responsible for reviewing and approving requests for access to controlled human transcriptomics and genomics data generated by the lab. The DAC ensures that data access requests are consistent with informed consent, ethical approvals, and applicable legal and institutional regulations, including GDPR.

  Dac EGAC50000000876

• DAC for CTOS colorectal cancer organoids

  This Data Access Committee (DAC) is responsible for reviewing and approving access requests to controlled-access human sequencing data generated from colorectal cancer patient-derived organoids established using the CTOS method. The dataset includes whole-exome sequencing (WES) and RNA sequencing (RNA-seq) data. Access requests are evaluated for consistency with the original informed consent and the approved research purposes.

  Dac EGAC50000000915

• Chronic lymphocytic leukemia patient-derived xenografts recapitulate clonal evolution to Richter transformation

  Whole-genome sequencing (WGS) and RNA-seq data from patient-derived xenografts (PDXs) obtained from CLL and RT primary samples as described in Playa-Albinyana et al.

  Study EGAS00001006965

• SCIMAP ACTUAL D0, D3, D6, D8, D14, D49

  The first experiment with multimodal sequencing in the SCI-MAP project. Here, human induced pluripotent stem cells underwent differentiation to chondrocytes for 21 days following an established protocol. Nuclei were isolated and sequenced in two modalities simultaneously; RNA and ATAC.

  Dataset EGAD50000002520

• Whone genome DNA methylation profile

  Primary human CD4+ naive T cells were cultured in vitro and sorted based on the defined number of division steps which they have undergone. Of those populations (division 0/div4/div6) EMseq data were generated to assess the whole-genome DNA methylation profile. 2 independent experiments with 2 different donors were conducted

  Dataset EGAD50000001815

• Bulk RNA sequencing of metastatic colorectal cancer patient-derived xenografts with known response to irinotecan

  Standard polyA enriched RNA-seq profiles of patient-derived xenograft (PDX) models from NOD/SCID mice without treatment. These PDX are obtained from tumors from patients with metastatic colorectal cancer after serial passaging in mice.

  Dataset EGAD50000002138

• PacBio Revio WGS on 10 carriers of ring and marker chromosomes

  Bam files containing PacBio HiFi reads from carriers of ring and marker chromosomes. The reads where genereated using the PacBio Revio platform. Each individual was sequenced to roughly 30X coverage on one flow cell per individual. The chromosome of interest is indicated in the file name.

  Dataset EGAD50000002111

• HIV-phyloTSI: PANGEA (PCR amplicon)

  This dataset includes sample numbers TSI_0426 to TSI_0527 for the PANGEA (PCR amplicon) cohort of the study. Samples were generated by pooling four overlapping PCR amplicons (see Gall et al 2012, DOI: 10.1128/JCM.01516-12). The sequencing was conducted using the Illumina NovaSeq system. Each sample has a BAM file, and its associated reference file.

  Dataset EGAD50000001308

• Single-cell RNA-sequencing on malignant and benign tissue samples

  Single-cell RNA-sequencing on malignant and benign tissue samples from untreated donors with colorectal adenocarcinoma and liver metastasis was performed in order to deduce tissue adaptive expression patterns of the disease. Matching tissue from five donors with untreated CRC and liver metastasis were sampled.

  Dataset EGAD50000001203

• Expression quantitative trait loci influence DNA damage-induced apoptosis in cancer

  Dataset with eQTL and e2QTL metadata. The analyses were performed using CD8+ T cells from 461 healthy European participants stimulated with high doses of 5 different carcinogens to induce early apoptosis. These include Methyl-methanesulfonate (MMS), tert-butyl-hydroperoxide (TBOOH), benzo(a)pyrene-7,8-diol-9,10-epoxide (BPDE), 4-hydroxycyclophosphamide (HC) and UVC radiation.

  Dataset EGAD50000000941

• Exonic Counts

  Read counts, per gene, aligning to exons. Alignment performed with GSNAP. 20 samples.

  Dataset EGAD50000000820

• BipEx-Landen: Bipolar Exome Sequencing

  This research project was a collaboration between the Karolinska Institute and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 5,876 Bipolar case/control samples from collaborators in Sweden. Genomic DNA from each samples was sequenced to a mean depth of 20x.

  Dataset EGAD50000000307

• Investigating differential diagnostic and prognostic biomarkers in primary cutaneous follicle center lymphoma and follicular lymphoma using low-coverage whole-genome sequencing

  In this study, we analyzed 28 primary cutaneous follicle center lymphoma samples from 20 patients and compared the copy number profiles to a cohort of diagnostic samples of 64 nodal follicular lymphoma patients using low-coverage whole genome sequencing (lcWGS).

  Dataset EGAD50000000199

• Transcriptome atlas of brain organoid developent

  Single-cell Cut&Tag of three histone modifications and chromatin accessibility over a timecourse of brain organoid development from pluripotency. We profiled 5 time points of brain organoid development and 2 time points of retinal organoid development. We used scRNA-seq to profile transcriptome. Library preparation was carried out with the 10x genomics platform.

  Dataset EGAD50000000223

• Spatial and temporal transcriptome analysis on human skeletal muscle regeneration

  Skeletal muscle carries a unique ability for adaptation as well as regeneration that highly depends on a supportive cellular microenvironment. Here we show that spatial and single-cell transcriptomic analysis in human skeletal muscle is a unique approach to illuminate cellular interactions in the microenvironment.

  Dataset EGAD50000000263

• Heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer

  A mutation accumulation experiment in colorectal cancer (CRC) derived tumoroids. A sequential single-cell cloning approach was adopted to measure the mutation rate in eight tumoroids obtained from five patients. WGS was also performed on their matched normal tissue and on standard tumoroids cultures without any cloning step.

  Dataset EGAD50000000411

• PDX_HTA2.0_Guergen2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) and RCC metastases related to Guergen et al, Front Oncol 12:2022 889789. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.34.0). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 25).

  Dataset EGAD00010002392

• DNA methylation-based classification of sinonasal tumors [Proteomics data]

  This dataset includes raw label-free mass spectrometry proteomics data of different sinonasal tumor entities as well as normal sinonasal tissue. 72 samples were processed on a Q Exactive HF-X instrument coupled to an easy nanoLC 1200 system using one microgram of peptides and an 110 minutes gradient.

  Dataset EGAD00010002381

• RCC_HTA2.0_Buettner2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) related to Buettner et al, Genome Med 2022. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.26.0, R version 3.6.1). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 23).

  Dataset EGAD00010002353

• Colorectal cancer GWAS on the Spanish population

  Data on Affymetrix 6.0 arrays for Genome-Wide Association Study of colorectal cancer in the Spanish population. Additionally, geographical origin for each sample is provided, which constitutes the largest to-date Spanish genomic sample population

  Dataset EGAD00010001715

• ICGC Benchmarking Exercise

  The main objective of this benchmark is the comparison of the full sequencing pipeline of different ICGC partners, including procedures, methods and performance of library preparation and whole-genome deep-sequencing. A secondary objective will be a follow-up comparison of data analysis pipelines for identification of germline and somatic variants subsequent to the results of the ICGC Somatic Variant Calling Pipeline Benchmark.

  Dataset EGAD00001000625

• Single cell mRNA sequencing of CD11b cells from a primary GBM - SF 10345i

  We collected fresh tissue from an untreated GBM directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine after selection of CD11b+ cells using magnetic beads.

  Dataset EGAD00001003107

• Single cell mRNA sequencing of CD11b cells from a primary GBM - SF 10360i

  We collected fresh tissue from an untreated GBM directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine after selection of CD11b+ cells using magnetic beads.

  Dataset EGAD00001003108

• Single cell mRNA sequencing of CD11b cells from a primary GBM - SF 10592i

  We collected fresh tissue from an untreated GBM directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine after selection of CD11b+ cells using magnetic beads.

  Dataset EGAD00001003109

• Single cell mRNA sequencing of CD11b cells from a primary GBM - SF 10679iA

  We collected fresh tissue from an untreated GBM directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine after selection of CD11b+ cells using magnetic beads.

  Dataset EGAD00001003110

• Single cell mRNA sequencing of CD11b cells from a primary GBM - SF 10360i

  We collected fresh tissue from an untreated GBM directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine after selection of CD11b+ cells using magnetic beads.

  Dataset EGAD00001003111

• Whole Exome Sequencing of 15 Human Embryonic Stem Cell Lines

  This dataset includes deep coverage (>60x) whole exomes of 15 human embryonic stem cell lines. Genomic DNA was purified and fragmented using the Illumina Nextera system for library preparation and sequenced using 150bp paired-end reads. Sequencing reads were aligned to the hg19 reference genome using the BWA MEM alignment program.

  Dataset EGAD00001003446

• Oxford Human Islet whole genome bisulphite data of 10 human pancreatic islet samples

  DNA from 10 human pancreatic islet samples was processed for Whole-genome Bisulphite Sequencing. The resulting libraries were sequenced on an Illumina Hiseq 2000 to generate 100bp paired-end read data. The resulting fastq.gz and mapped bam files were deposited.

  Dataset EGAD00001003946

• Pleomorphic invasive lobular carcinoma targeted exome sequencing

  Fifteen pleomorphic invasive lobular carcionoma samples and their matched normal controls were subjected to targeted exome sequencing using the Beijing Genomics Institute TumorCare gene panel. Genomic DNA samples were randomly fragmented and captured libraries of each exome were sequenced on an Illumina Hiseq2000 system. CRAM files are provided for each tumor and normal pair.

  Dataset EGAD00001003995

• H3K27ac ChiIP-seq of monocyte and granulocytes from TB and non-TB samples

  This dataset contains 135 H3K27ac ChiP-seq experiments. Monocytes and granulocytes from TB and non-TB samples were obtained, ChIP-seq was performed, and the reads were aligned to hg19.

  Dataset EGAD00001004206

• WGS profiling of pediatric osteosarcoma

  Primary pediatric osteosarcoma samples were collected and profiled using WGS. When possible, germline and tumor samples were collected. For some patients, multiple tumor tissues were collected and sequenced. Some of the samples were used to derive PDTX models, which were also profiled with WGS. Paired end sequencing was performed on Illumina HiSeq instruments and FASTQ files reported.

  Dataset EGAD00001004537

• Triple Negative BC WGS Dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001335

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB22_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB22_M

  Dataset EGAD00001001708

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB23_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB23_C

  Dataset EGAD00001001709

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW4_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW4_M

  Dataset EGAD00001001834

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW49_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW49_M

  Dataset EGAD00001001831

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW49_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW49_C

  Dataset EGAD00001001829

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW47_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW47_M

  Dataset EGAD00001001828

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW47_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW47_F

  Dataset EGAD00001001827

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW47_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW47_C

  Dataset EGAD00001001826

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW46_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW46_M

  Dataset EGAD00001001825

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW46_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW46_F

  Dataset EGAD00001001824

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW46_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW46_C

  Dataset EGAD00001001823

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW3_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW3_M

  Dataset EGAD00001001822

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW3_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW3_F

  Dataset EGAD00001001821

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW3_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW3_C

  Dataset EGAD00001001820

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW38_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW38_M

  Dataset EGAD00001001819

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW38_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW38_F

  Dataset EGAD00001001818

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW38_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW38_C

  Dataset EGAD00001001817

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW32_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW32_M

  Dataset EGAD00001001816

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB33_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB33_F

  Dataset EGAD00001001731

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB31_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB31_F

  Dataset EGAD00001001728

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB28_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB28_C

  Dataset EGAD00001001721

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB24_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB24_F

  Dataset EGAD00001001713

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB23_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB23_F

  Dataset EGAD00001001710

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB51_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB51_F

  Dataset EGAD00001001761

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB52_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB52_C

  Dataset EGAD00001001763

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB52_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB52_M

  Dataset EGAD00001001765

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB55_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB55_F

  Dataset EGAD00001001767

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB57_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB57_C

  Dataset EGAD00001001769

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB57_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB57_F

  Dataset EGAD00001001770

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB57_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB57_M

  Dataset EGAD00001001771

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB58_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB58_C

  Dataset EGAD00001001772

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB60_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB60_C

  Dataset EGAD00001001775

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB60_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB60_F

  Dataset EGAD00001001776

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB60_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB60_M

  Dataset EGAD00001001777

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB62_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB62_C

  Dataset EGAD00001001778

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB62_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB62_F

  Dataset EGAD00001001779

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB62_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB62_M

  Dataset EGAD00001001780

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW12_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW12_C

  Dataset EGAD00001001784

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW12_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW12_M

  Dataset EGAD00001001786

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW14_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW14_C

  Dataset EGAD00001001787

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW14_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW14_M

  Dataset EGAD00001001789

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW15_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW15_C

  Dataset EGAD00001001790

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW15_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW15_M

  Dataset EGAD00001001792