12277 results for ""statistically+reactive"+taxa+in+microbial+community"

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• A Study of the Genetic Causes of Complex Pediatric Disorders

  The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is a high-throughput, highly automated genotyping and sequencing facility equipped with state-of-the-art genotyping and sequencing platforms. Children who are treated at the Children's Hospital Healthcare Network and their parents may be eligible to take part in a major initiative to collect more than 100,000 blood samples, covering a wide range of pediatric diseases. A large majority of participants consenting to prospective genomic analyses also consent to analysis of their de-identified electronic medical records (EMRs). EMRs are longitudinal, with a mean duration of 6.5 years. CAG has committed to releasing genotype and phenotype data for 4000 individuals diagnosed with asthma, ADHD, atopic dermatitis, GERD (1000 for each), and 1000 individuals on the upper and lower ranges of Low-Density Lipoprotein (LDL) levels to dbGaP. We will also release genotype/phenotype of 3000 controls. Relevant phenotype data includes primary diagnoses (ICD9 codes), secondary diagnoses (ICD9 codes), medical procedures/tests conducted in relation to the phenotype, and a listing of relevant medications. Further details of CAG's research programs and capacity are available at: http://www.caglab.org

  Study phs000490

• Genomic Characterization CS-MATCH-0007 Arm Z1D

  The CS-MATCH-0007 protocol is a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing, RNA sequencing and if possible, whole-genome, methylation and miRNA sequencing using pre-and posttreatment tumor biopsy specimens from all patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to their corresponding genomic alterations. Arm Z1D is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with MMR deficiency are treated with nivolumab. This subprotocol is one of the treatment arms in the EAY-131 trial included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood and RNA from tumor tissue. A fuller genomic landscape of tumors from these patients will enable discovery of potential molecular features correlated to clinical outcomes or lay the foundation for future studies leading to new and more effective treatments.

  Study phs001859

• Epigenomes and Transcriptomes of Brain Samples of Schizophrenics and Controls

  We examined the effects of antipsychotic medications on the cell-specific epigenomics and transcriptomics in the frontal cortex of schizophrenic subjects. We performed ChIP-seq (H3K4me3 and H3K27ac) and RNA-seq on neuronal and non-neuronal nuclei of postmortem frontal cortex samples from two cohorts of schizophrenics, either previously treated or not with antipsychotic medications, and control subjects individually matched by sex and age. In total, we tested 29 schizophrenics (15 untreated and 14 treated patients) and their matched control samples. Two replicates were produced on each brain sample for each assay. ChIP-seq data were generated using MOWChIP-seq (Zhu et al., PMID: 31666743) and RNA-seq data were produced using the combination of SMART-seq2 (Picelli et al., PMID: 24385147) and a Nextera XT DNA library preparation kit. The filename contains the information on the experimental group, the number of the sample within the group, the type of the brain nuclei, the epigenomic/transcriptomic data set (either H3K27ac or mRNA), and the number of replicate. For example, “SCZ-1-untreated-neuron-H3K4me3-R1” refers untreated schizophrenic sample #1, replicate 1 ChIP-seq data on H3K4me3.

  Study phs002487

• Genomic Characterization CS-MATCH-0007 Arm Y

  The CS-MATCH-0007 protocol is a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing, RNA sequencing and if possible, whole-genome, methylation and miRNA sequencing using pre-and post-treatment tumor biopsy specimens from all patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to their corresponding genomic alterations. Arm Y is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with AKT mutations are treated with AZD5363. This subprotocol is one of the treatment arms in the EAY-131 trial included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood and RNA from tumor tissue. A fuller genomic landscape of tumors from these patients will enable discovery of potential molecular features correlated to clinical outcomes or lay the foundation for future studies leading to new and more effective treatments.

  Study phs001904

• Genetics of Congenital Anomalies of the Kidney and Urinary Tract

  The Genetics of Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) contributes data from unrelated individuals who were recruited at the Columbia University Medical Center (New York, USA), the Polish Registry of Congenital Malformations (Poland), the Universities of Parma, Bari, and Brescia, and the Gaslini Institute (Italy), the University of Skopje (Macedonia), and VUMC of Amsterdam (Netherlands). These individuals consented to share their data for scientific discovery. The purpose of the study is to investigate the genetic architecture of CAKUT.  Additionally, part of the data in this study was generated from 418 DNA samples from the Randomized Intervention for Children with Vesicoureteral Reflux (RIVUR) study, and supplied by the NIDDK Central Repository. The RIVUR study was conducted by the RIVUR study investigators, and supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). The Genetics of CAKUT study was not conducted in collaboration with investigators of the RIVUR study and does not necessarily reflect the opinions or views of the RIVUR study, the NIDDK Central Repository, or the NIDDK. Genomic DNA samples were genotyped on Illumina Multi-Ethnic Global Arrays.

  Study phs001749

• Comprehensive Epigenetic Landscape of Rheumatoid Arthritis Fibroblast-Like Synoviocytes

  We characterized the epigenetic landscape of rheumatoid arthritis fibroblast-like synoviocytes (FLS) compared with osteoarthritis FLS. Multiple technologies were used, including ChIP-seq to assay H3K27ac, H3K4me1, H3K4me3, H3K36me3, H3K27me3, and H3K9me3, ATAC-seq for chromatin accessibility, the transcriptome by RNA-seq and whole genomic bisulfite sequencing for DNA methylation. Integrative analysis was performed using a novel unbiased method to identify regions of the genome that have similar epigenetic marks. The regions that distinguished RA and osteoarthritis cells were primarily located in active enhancers and promoters. The regions and genes identified included immunological pathways. In addition, some unexpected pathways, most notably "Huntington's Disease Signaling", were discovered. The Huntington's Disease pathway was biologically validated for Huntingtin-interacting protein-1, which regulated invasive behavior of FLS. For a complete description, see R. Ai et al., Comprehensive epigenetic landscape of rheumatoid arthritis fibroblast-like synoviocytes. Nat Commun 9, 1921 (2018). Sequencing data of study participants are available through dbGaP's Authorized Access portal, while analyses of the sequencing data may be obtained through NCBI's GEO portal under GSE112658.

  Study phs001615

• Genome-Wide Discovery of Novel Breast Cancer Predisposing Mutations

  Cancer risk shows clear heritability, but the inherited genetic factors remain largely unknown. This project will seek to identify new genes in which mutations confer hereditary risk for early onset breast cancer, with important implications for both biological understanding and clinical prediction and prevention. Identifying cancer predisposing mutations can provide new biological insights and significantly impact important clinical decision making regarding treatment, surveillance and preventive approaches. Examples include the BRCA1 breast cancer susceptibility gene, which affects treatment decisions (surgical management), surveillance (frequent breast MRI) and prevention (oophorectory for prevention of ovarian cancer). Hereditary early onset breast cancer patients commonly present to Cancer Genetics clinics, but the majority of these patients do not have identifiable mutations in known candidate genes. Here, we will perform whole exome sequencing to discover novel cancer susceptibility genes. The patients have been recruited from Memorial Sloan Kettering Cancer Center (PIs Kenneth Offit and Zsofia Stadler) and Massachusetts General Hospital (PI Daniel Haber). All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Agilent SureSelect Human All Exon Kit v2 and sequencing was performed on an Illumina HiSeq 2000 or 2500.

  Study phs000822

• eMERGE Phase III Clinical Center at Partners HealthCare

  The Partners HealthCare Biobank is a large research data and sample repository working within the framework of Partners Personalized Medicine. It provides researchers access to high quality, consented samples to help foster research, advance understanding of the causes of common diseases, and advance the practice of medicine. The Partners Biobank provides banked samples (plasma, serum and DNA) collected from consented patients. These samples are available for distribution to Partners HealthCare investigators with appropriate approval from the Partners Institutional Review board (IRB). They are linked to clinical data that originates in the Electronic Medical Record (EMR), as well as additional health information collected in a self-reported survey. The Partners Biobank will be genotyping 25,000 subjects with the Illumina Multiethnic Beadchip 1.6 million SNPs with exome and custom content (> 60,000 LoFs). Of the participants genotyped so far, 4929 of 4962 (99.3%) individuals have genotype data that passed the default quality thresholds for the Infinium array (call rate >= 0.99). We are submitting the genotype data to dbGaP for 4929 subjects with 12 phenotypes (based on icd9 codes). We will do annual releases until we reach the full 25,000 genotyped subjects.

  Study phs000944

• VA APOLLO Project - Research for Precision Oncology (RePOP)

  The Research for Precision Oncology Program (RePOP) is a research activity that establishes a cohort of Veterans diagnosed with cancer and who have had genomic analyses performed on their tumor tissue as part of standard of care. All data relevant to a patient's cancer and cancer care will be collected under RePOP, including patient demographics, co-morbidities, genomic analysis, treatments, medications, lab values, imaging studies, and outcomes. All RePOP participants will have signed/verbal informed consent and signed HIPAA authorization to have their data stored and shared from RePOP's Precision Oncology Program Data Repository (PODR). The Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) network is a collaboration between NCI, the Department of Defense (DoD), and the Department of Veterans Affairs (VA) to incorporate proteogenomics into patient care as a way of looking beyond the genome, to the activity and expression of the proteins that the genome encodes. The emerging field of proteogenomics aims to better predict how patients will respond to therapy by screening their tumors for both genetic abnormalities and protein information, an approach that has been made possible in recent years due to advances in proteomic technology.

  Study phs001374

• Epigenetic Biomarkers of Aging

  The aim of the study was to discover new epigenetic biomarkers of aging. We used a genome-wide screen for genetic loci showing consistent changes of DNA methylation with progressive aging. Blood DNA samples from 19 apparently healthy individuals aged 22-80 years obtained from the NINDS repositories were analyzed for DNA methylation using Reduced Representation Bisulfite Sequencing. We followed the New England Biolabs (NEB) protocol for methylated adaptors as described previously. Briefly, 1 microgram of genomic DNA was spiked with 100 picograms of lambda phage DNA as the unmethylated standard and digested with MspI endonuclease at C’CGG sites. Ends of restriction fragments were filled in, 3’-dA tailed and methylated adaptors were ligated to the ends of restriction fragments. Bisulfite treatment using the Epitect kit (Qiagen) followed. Bisulfite-converted libraries were amplified using EpiMark Taq DNA polymerase (NEB) and primers with dual barcode indices. The libraries were pooled and sequenced on Illumina HiSeqX instrument using paired end reads of 150 bases. We used Bismark v0.23.1 to align the sequences to hg19 human genome assembly. We used methylKit v1.22.0 to analyze differential methylation in individuals of different ages.

  Study phs003046

• Whole Genome Association Study of Systemic Lupus Erythematosus

  The goal of this collaborative study was to identify new genetic risk factors for Systemic Lupus Erythematosus (SLE). To do this we conducted a genome-wide scan by combining the resources and expertise from a number of SLE researchers to establish a large sample set comprising 1311 SLE cases and 3340 controls. The SLE case samples were genotyped from the following collections: 338 subjects from the Autoimmune Biomarkers Collaborative Network (ABCoN), an NIH/NIAMS funded repository, 141 subjects from the Multiple Autoimmune Disease Genetics Consortium (MADGC), 613 subjects from the University of California San Francisco (UCSF) Lupus Genetics, and 335 subjects from the University of Pittsburgh Medical Center (UPMC), plus 8 samples collected at The Feinstein Institute for Medical Research. A total of 3583 control samples were examined in the association analyses. As part of this project, 1861 control samples were selected and then genotyped from the New York Cancer Project (NYCP), based on self-described ethnicity, gender and age. In addition, genotype data from 1722 control samples (all self-described North Americans of European descent) were obtained from the publicly available iControlDB database (http://www.illumina.com/pages.ilmn?ID=231).

  Study phs000122

• Integrated Analysis of Multimodal Single-Cell Data

  The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce 'weighted nearest neighbor' analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity. All CITE-seq and ECCITE-seq raw matrices are available in GEO database under the accession number GEO: GSE164378.

  Study phs002315

• Genetic Epidemiology of Ovarian Cancer Histotypes

  Epithelial ovarian cancer is a highly fatal malignancy with known genetic etiology; however, it is estimated that a substantial portion of narrow sense heritability remains to be discovered. The goal of this research was to use genetic information from distantly related ovarian cancer cases to identify regions of the genome that may harbor rare risk variants for epithelial ovarian cancer. The study was conducted in the setting of the Utah Population Database, a statewide data resource in which extensive ancestry data are linked to Utah Cancer Registry records. Focusing on families with a statistically significant excess risk of epithelial ovarian cancer, we used the Infinium Global Screening Array v.3.0 to generate germline genotyping data for distantly related cases. We then applied Shared Genomic Segment Analysis to each set of related cases to identify genomic regions that may harbor ovarian cancer risk variants. Eleven regions were identified. Genotype data are available through dbGaP for one case from each pedigree. Genotype data from other ovarian cancer cases within the high-risk pedigrees as well as the pedigrees' corresponding structures can be requested and made available with approval from the Utah Resource for Genetic and Epidemiologic Research (RGE).

  Study phs003140

• Mapping Genes for Mammographic Density

  We recruited 1,521 women from the Old Order Amish (OOA) population of Lancaster County, Pennsylvania, with the primary goal of identifying genetic factors that influence mammographic density. All women were between the ages of 40 and 88 years, with a mean of 54 years. Additional study design details, including eligibility criteria, are described elsewhere (Douglas et al., 2008). The present-day OOA of Lancaster County are the descendants of approximately 550 individuals from central Western Europe who immigrated to the U.S. in the early eighteenth century. All living individuals derive from a single, 14-generation pedigree (Lee et al., 2010). Although the OOA are a genetically closed founder population, allele frequencies and LD profiles are remarkably similar between the OOA and U.S. participants in the International HapMap project (HapMap CEU) for common SNPs (MAF>/=5%) (Van Hout et al., 2010). We recently completed genome-wide linkage and association analyses of mammographic density, including dense and non-dense areas of the breast and the ratio of dense to total area of the breast. Summary-level data from our GWAS are available here and through the Marker of DEnsity (MODE) Consortium.

  Study phs000604

• Genomic Characterization CS-MATCH-0007 Arm H

  The CS-MATCH-0007 protocol is a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from all patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to their corresponding genomic alterations. Arm H is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with BRAF V600K/V600E mutations are treated with Dabrafenib and Trametinib. This subprotocol is one of the treatment arms in the EAY-131 trial included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood and RNA from tumor tissue. A fuller genomic landscape of tumors from these patients will enable discovery of potential molecular features correlated to clinical outcomes or lay the foundation for future studies leading to new and more effective treatments.

  Study phs001888

• Regulation of T Cell CXCL13 Production

  This study evaluated the signals that regulate production of the B cell chemoattractant CXCL13 by human CD4 T cells. Single-cell and bulk RNA-seq datasets evaluated the gene expression changes induced by TGF-beta and the aryl hydrocarbon receptor (AHR), two signals that regulate CXCL13 production. Bulk ATAC-seq data evaluated the epigenetic changes in T cell stimulated with an AHR agonist or antagonist. Ex vivo bulk RNA-seq data of sorted T cell subsets from blood of patients with lupus and control donors interrogated the gene expression differences in sorted T cell subsets. Ex vivo ATAC-seq data allowed comparison of epigenetic profiles of PD-1hi Tph cells from rheumatoid arthritis synovial fluid and PD-1hi T follicular helper (Tfh) cells from tonsil to PD-1low CD4 T cells from the same samples. Single-cell RNA-seq data of T cells from lupus patients before and after treatment with anifrolumab (anti-IFNAR) allowed interrogation of T cell populations that change with anifrolumab treatment. These datasets allowed for genomic interrogation of changes induced by AHR, TGF-beta, and interferon and their relationship to CXCL13 production.

  Study phs003582

• Chronic Renal Insufficiency Cohort (CRIC) Study Metabolomics and Proteomics

  The Chronic Renal Insufficiency Cohort (CRIC study) was established in 2001 by the National Institute of Diabetes, Digestive, and Kidney Diseases (NIDDK) to improve the understanding of the relationship between chronic kidney disease and cardiovascular disease. The goals of the CRIC Study are to examine risk factors for progression of chronic kidney disease and cardiovascular disease among patients with chronic kidney disease and to develop predictive models to identify high-risk subgroups, informing future treatment trials and increasing application of available preventive therapies. This record includes plasma metabolomics and plasma proteomics data. Genotype data for 3527 CRIC Study partcipants is available at dbGaP in phs000524, "Chronic Renal Insufficiency Cohort (CRIC)-GWAS". Additional phenotypic, clinical, and outcomes data are available at the NIDDK Central Repository and can be linked to data available at dbGaP.More than 330 manuscripts have been published, reporting on the effects of a broad range of risk factors (from molecular biomarkers of disease pathways to clinical, demographic, and behavioral characteristics) on the progression of CKD and other health consequences. The full CRIC bibliography can be found at the BIBLIOGRAPHY for the Chronic Renal Insufficiency Cohort (CRIC) Study.

  Study phs003709

• Final results and ctDNA analyses from the randomized phase 3 IMpassion031 trial evaluating peri-operative atezolizumab for early-stage triple-negative breast cancer

  In IMpassion031, adding atezolizumab to neoadjuvant chemotherapy significantly improved pathologic complete response (pCR) rate (primary endpoint) for stage II/III triple-negative breast cancer (TNBC). Patients with stage II/III TNBC were randomized 1:1 to neoadjuvant chemotherapy plus peri-operative atezolizumab or pre-operative placebo. Descriptive secondary endpoints included event-free, disease-free, and overall survival. Long-term outcomes favored the atezolizumab group (event-free survival HR 0.76, 95% CI: 0.47–1.21). Among patients without pCR, 14/70 (20%) atezolizumab-treated and 33/99 (33%) placebo-treated patients received additional adjuvant therapy, frequently capecitabine. In exploratory analyses, pCR was prognostic for long-term outcome. Patients with baseline ctDNA-negative status (6%) had excellent long-term outcomes. Most patients (87%) had cleared ctDNA at surgery. ctDNA-positive status at surgery identified a subset of non-pCR patients with poorest prognosis. Long-term safety was consistent with primary results. Adding atezolizumab to chemotherapy for stage II/III TNBC is associated with more favorable long-term outcomes. ctDNA dynamics provide prognostic value beyond pCR. ClinicalTrials.gov identifier: NCT03197935

  Study EGAS50000000974

• Chicago Infant Mortality Study

  The Chicago Infant Mortality Study (CIMS) was a population-based, prospective, case-control study conducted in metropolitan Chicago, Cook County, Illinois, to examine the risk factors for sudden infant death syndrome (SIDS) among a primarily Black population. Eligible case infants were aged birth to one year where the cause of death was determined to be SIDS while eligible control infants were aged one month to one year who died of other sudden unexpected infant death (SUID) causes. Recruitment occurred between November 1993 and April 1996. The goal of this ancillary multiomics study was to evaluate possible genetic and epigenetic determinates of SIDS and together with metabolomic profiles, identify novel clinical diagnostic tools to enable molecular autopsies and biomarkers to proactively identify and intervene in infants at greater risk of death from SIDS. The multiomics data was generated from medical examiner autopsy specimens and includes: whole exome sequencing genotypes; RNA-seq transcriptome and methylome profiles from autopsy heart tissue; and serum metabolomics profiles. The sample size available varies with the modality of the omics assay, but the total number of unique infants included is about 400.

  Study phs003790

• Error-corrected flow-based sequencing at whole genome scale and its application to circulating cell-free DNA profiling

  Differentiating sequencing errors from true variants is a central genomics challenge calling for error suppression strategies that balance costs when sparse material or ultra-rare variants require high-accuracy methods. For example, circulating cell-free DNA (ccfDNA) sequencing for cancer monitoring is limited by sparsity of circulating tumor DNA (ctDNA), abundance of genomic material in samples, library preparation error rates and sequencing errors. Whole-genome sequencing (WGS) can overcome the low abundance of ccfDNA by integrating signal across the mutation landscape, but higher cost limits adoption compared with targeted panels, where ccfDNA abundance limits maximal coverage depths. Here we applied deep (~120x) lower-cost WGS (Ultima Genomics) with analytic error correction for tumor-informed ctDNA detection within the part-per-million range. We further developed high-coverage duplex error-corrected WGS of ccfDNA, achieving 7.7x10-8 error rates, to assess disease burden in melanoma and urothelial cancer patients without matched tumor sequencing. Together, we show that deeply sequenced error-corrected WGS accurately calls somatic variants, demonstrating the feasibility of WGS for tumor-informed and tumor-agnostic ctDNA detection.

  Study EGAS50000000844

• Development of cell lines and mouse models of bone and soft tissue sarcoma to establish novel treatment

  Malignant giant-cell tumors are extremely rare bone sarcomas that transform from conventional giant-cell tumors during long periods of treatment. We have applied the culture methods and succeeded in establishing patient-derived organoids (PDO) of rare sarcomas. This study aimed to investigate the genomic characteristics of our established novel organoids from human malignant giant-cell tumors. The developed tumors with xenograft were genomically analyzed to compare their characteristics with those of the original tumors. Genetic changes over time throughout treatment were analyzed, and the genomic status of the established organoid was confirmed. Next generation sequencing revealed that the established organoids lacked the H3-3A G34W mutation. The xenografted organoids of the malignant giant-cell tumor had phenotypes genetically similar to those of the original tumor. The established organoids were confirmed to be derived from human malignant giant-cell tumors. In summary, the present study demonstrated a novel organoid model of a malignant giant-cell tumor that was genetically confirmed to be a malignant transformed tumor. Our organoid model could be used to elucidate the molecular pathogenesis of a malignant giant-cell tumor and develop novel treatment modalities.

  Study JGAS000618

• Whole-genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis

  Endometriosis is a highly prevalent condition that remains underdiagnosed and poorly managed due to the lack of clinically validated biomarkers and limited understanding of its underlying pathophysiology. Although menstrual blood–derived stem cells (MenSCs) have been implicated in disease pathogenesis, their potential as a diagnostic source has not been systematically explored. We conducted a clinical study including 42 women (19 with endometriosis and 23 controls) to evaluate whether DNA methylation profiles from freshly isolated MenSCs could identify disease-specific biomarkers. Whole-genome DNA methylation sequencing identified differentially methylated regions (DMRs) enriched in genes associated with key features of endometriosis, including inflammation, tissue remodelling, and developmental processes. These DMRs robustly discriminated cases from controls, independently of technical and clinical confounders. Machine learning models trained and validated on these regions demonstrated strong diagnostic performance (specificity 83%, sensitivity 79%). Integration with an independent single-cell RNA sequencing dataset suggested that the identified DMRs may influence gene expression, supporting their biological relevance. Collectively, these findings highlight MenSC DNA methylation profiling as a promising, non-invasive strategy for early diagnosis and personalised management of endometriosis. (PubMed IDs will be provided once the manuscript is published.)

  Study EGAS50000001640

• RNA sequencing and Illumina 2.5M SNP array data collected from 675 commonly used human cancer cell lines.

  Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic response1. Although substantial effort has been directed to defining the genomic constitution of cancer cell line panels2–4, the transcriptome – which represents the active program of a cell – remains understudied. Here, we describe RNA sequencing and SNP array analysis of 675 commonly used human cancer cell lines. We explore numerous transcriptome features including coding and non-coding gene expression, transcribed mutations, gene fusion and expression of non-human sequences. Aside from many known aberrations we find new surprising characteristics, including more than 2200 unique fusion gene pairs representing a vast, testable repertoire of oncogenic fusions, many of which have analogs found in primary human tumors. We show that a combination of multiple genome and transcriptome features in a novel pathway-based approach enhances prediction of response to various targeted therapeutics. Our results provide valuable new insights into these critical pre-clinical models and provide added context for interpreting the numerous studies that employ these widely used cell lines.

  Study EGAS00001000610

• Determination_of_cell_specific_regulatory_enhancers_in_hematopoetic_models

  The BLUEPRINT project is a large-scale project investigating epigenetic mechanisms involved in blood formation, in health and disease. The human variation workpackage (WP10) of the project seeks to characterize the effect of common sequence variation on the epigenome status of a cell. To do this, the project will use highly purified blood cells to minimise “experimental noise” and therefore enhance the power to discover modest effects. Two peripheral blood cell types, the CD14+CD16- monocyte (an important central orchestrator of adaptive immunity and a bridge between innate and adaptive immunity) and the CD65+CD9- neutrophilic granulocyte (the frontline cell for innate immunity) have been selected for this purpose. The two types of cells will be obtained at high purity from adult blood (AB) of 200 healthy males and females, respectively. Cells will be purified by using already validated and fully operational protocols that are based on density gradient centrifugation of the buffy coat obtained from whole blood, followed by magnetic bead-based purification using monoclonal antibodies against Cluster of Differentiation (CD) lineage-specific cell surface markers. This data set contains functional genomics data for gene expression and chromatin state.

  Study EGAS00001000586

• Global Anaplastic Thyroid Cancer Initiative

  Thyroid cancer is the most common endocrine malignancy. Most thyroid cancers are of the well-differentiated (non-aggressive) phenotype, and are almost always cured with standard treatments. In contrast, anaplastic thyroid cancer (ATC) is rare, accounting for only 1% of thyroid cancers, however it is perhaps the most lethal human malignancy with an average survival of 3 to 6 months. ATC presents with dramatic and rapid onset of airway and esophageal blockage with frequent spread to the lungs. Interestingly, 21–79% of ATCs have coexisting areas or a previous history of well-differentiated cancers. Although this suggests a progression from well-differentiated cancers to ATC, to date there is little molecular conformation that such a progression exists versus de novo generation of ATC. As ATC is extremely rare and most cases are inoperable, there are a paucity of tissue samples for study at any one center. The Global Anaplastic Thyroid Cancer Initiative (GATCI) aims to unite international institutions in order to pool samples (ATC with or without a paired well-differentiated component) for a comprehensive analysis of the genomic landscape of this disease.

  Study EGAS00001002234

• Comprehensive molecular profiling identifies novel genetic drivers and subtypes underlying medulloblastoma

  Current therapies for medulloblastoma (MB), a highly malignant childhood brain tumor, impose debilitating effects on the developing child, warranting the development of molecularly targeted treatments with reduced toxicities. Prior studies have failed to disclose the full spectrum of driver genes and molecular processes operative in MB or adequately explain heterogeneity among molecular subgroups. Herein, we detail the somatic landscape across 491 sequenced MBs and molecular heterogeneity amongst 1,256 epigenetically analyzed cases, identifying subgroup-specific mutational signatures, driver genes, and pathway alterations including previously unappreciated actionable therapeutic targets. Integrative approaches for assigning driver genes to subgroups explained >65-70% of Group 3 and Group 4, doubling previous knowledge. Novel subtypes underlying Group 3 and Group 4 were differentially enriched for specific driver events, including hotspot in-frame indels targeting KBTBD4 and ‘enhancer hijacking’ driving activation of PRDM6. Thus, application of integrative genomics to an unprecedented cohort of clinical samples derived from a single childhood cancer entity has disclosed a series of new cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for treating MB.

  Study EGAS00001001953

• We performed whole-exome sequencing of 20 samples (10 actinic keratosis and 10 cutaneous squamous cell carcinoma) to investigate a potential relationship between DNA methylation-based subtypes and genetic mutation patterns (Rodriguez-Paredes et al., Nat Commun 2017)

  Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer type and arises from keratinocytes. Most cSCC progress from a UV-induced precancerous lesion termed actinic keratosis (AK). Despite various efforts to characterize these lesions molecularly, the etiology of AK and its progression to cSCC remain only partially understood. Here we have used Infinium MethylationEPIC BeadChips to interrogate the DNA methylation status of about 850.000 CpGs in epidermal preparations from healthy skin, AK and cSCC. Importantly, we found that the premalignant AK samples displayed classical features of cancer methylomes and were highly similar to cSCC methylomes. Further analysis identified typical features of stem cell methylomes, such as a reduced DNA methylation age, non-CpG methylation and stem cell-related keratin and enhancer methylation patterns. Interestingly, this signature was detected only in one half of the AK and cSCC samples, while the other half showed keratin and enhancer methylation patterns that were more closely related to the control epidermis. These findings suggest the existence of two distinct subclasses of AK and cSCC that originate from distinct keratinocyte differentiation stages.

  Study EGAS00001002670

• Epigenome wide DNA methylation assay of gingivo-buccal oral squamous cell carcinoma using single base resolution high throughput array

  Gingivo-buccal oral squamous cell carcinoma (OSCC-GB) is the most common cancer among men in India and is associated with high mortality. Although OSCC-GB is known to be quite different from tongue cancer in its genomic presentation and its clinical behavior, it is treated identically as tongue cancer. Predictive markers of prognosis and therapy that are specific to OSCC-GB are, therefore, required. To achieve this, we have carried out epigenomic (n=87) profiling of paired tumor-normal tissues collected from OSCC-GB patients from India and genome-wide DNA methylation assays were performed. DNA was isolated using DNeasy Blood and Tissue Kit (Qiagen). The purity and concentration was estimated using NanoDrop 2000 (Thermo Fisher Scientific). Approximately 500 ng genomic DNA from each sample was used for sodium bisulfite conversion using the EZ DNA methylation Gold Kit (Zymo Research, USA). Genome-wide DNA methylation was assayed using iScan (Illumina), for paired tumour and adjacent normal samples of 25 patients using the Infinium Human Methylation450 BeadChip and of 62 patients using the Infinium MethylationEPIC BeadChip.

  Study EGAS00001003896

• TRACERx Renal 100

  Evolutionary dynamics of clear cell renal cell carcinoma (ccRCC) have not been studied prospectively or across all disease stages. Through the multi-centre prospective cohort study, Renal TRACERx Renal, we analysed 1209 primary tumour regions from 101 patients with ccRCC. We detect up to 30 driver events in a single tumour, and show that subclonal diversification is associated with known clinical parameters. Defining driver event co-occurrence, mutual exclusivity and timing at clone level, we reveal deterministic patterns of clonal evolution and disease progression. We find that ccRCC can be grouped into seven distinct evolutionary subtypes, ranging from tumours characterised by early fixation of multiple mutational and copy number driver events that can disseminate widely and rapidly; to highly branched tumours with >10 subclonal drivers and extensive parallel evolution presenting with oligometastatic disease. We identify either heterogeneity or chromosome instability, or both, as determinants of patient outcome. Our insights reconcile the variable clinical behaviour of ccRCC and the benefit of surgical intervention in early and late-stage disease; and offer potential biomarker opportunities to maximise the benefit of both surgery and active surveillance.

  Study EGAS00001002793

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Gastric_Organoids

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003151

• Circulating tumor cells Exome sequencing from breast cancer

  Single cell technologies allow interrogating the extent of tumor heterogeneity, providing novel insights into tumor evolution and treatment resistance mechanisms. Here, we investigated the level of genetic heterogeneity among circulating tumor cells (CTCs) at the single nucleotide variation and copy number aberration (CNA) levels and compared it to synchronous matched primary tumor/metastatic lesion from 3 metastatic breast cancer patients with triple-negative (TNBC), HER2-positive (HER2+) and estrogen-receptor-positive (ER+) tumors. Whole exome sequencing was performed on 3 synchronous bulk tumor tissue and 21 single/pooled CTC samples. When comparing bulk tissue with CTCs from the same patient, we found similar CNA profiles and the same patient-specific driver mutations for the HER2+ and TNBC tumors. Different CNA profiles and driver mutations were found for the ER+ tumor, with two distinct clones being identified in the CTCs, one harboring an activating ESR1 mutation, the other one bearing a TP53 mutation. These data suggest that tumor tissue and CTCs provide in a subset of patients complementary clinically relevant information to map tumor heterogeneity and monitor tumor evolution. Further validation is needed.

  Study EGAS00001005228

• Clonal Decomposition and DNA Replication States Defined by Scaled Single-Cell Genome Sequencing

  Accurate measurement of clonal genotypes, mutational processes, and replication states from individual tumor-cell genomes will facilitate improved understanding of tumor evolution. We have developed DLP+, a scalable single-cell whole-genome sequencing platform implemented using commodity instruments, image-based object recognition, and open source computational methods. Using DLP+, we have generated a resource of 51,926 single-cell genomes and matched cell images from diverse cell types including cell lines, xenografts, and diagnostic samples with limited material. From this resource we have defined variation in mitotic mis-segregation rates across tissue types and genotypes. Analysis of matched genomic and image measurements revealed correlations between cellular morphology and genome ploidy states. Aggregation of cells sharing copy number profiles allowed for calculation of single-nucleotide resolution clonal genotypes and inference of clonal phylogenies and avoided the limitations of bulk deconvolution. Finally, joint analysis over the above features defined clone-specific chromosomal aneuploidy in polyclonal populations.

  Study EGAS00001003190

• Target gene sequencing for human normal endometrial glands

  To elucidate the timing and mechanism of the clonal expansion of somatic mutations in cancer-associated genes in the normal endometrium, we conducted target sequencing of 112 genes for 1,298 endometrial glands and matched blood samples from 36 women. By collecting endometrial glands from different parts of the endometrium, we showed that multiple glands with the same somatic mutations occupied substantial areas of the endometrium. The 112 genes are as follows: ABCC1, ACRC, ANK3, ARHGAP35, ARID1A, ARID5B, ATCAY, ATM, ATR, BARD1, BCOR, BRCA1, BRCA2, BRD4, BRIP1, CAMTA1, CDC23, CDYL, CFAP54, CHD4, CHEK1, CHEK2, CTCF, CTNNB1, CUX1, DGKA, DISP2, DYNC2H1, EMSY, FAAP24, FAM135B, FAM175A, FAM65C, FANCA, FANCB, FANCC, FANCD2, FANCE, FANCF, FANCG, FANCI, FANCL, FANCM, FAT1, FAT3, FBN2, FBXW7, FGFR2, FRG1, GPR50, HEATR1, HIST1H4B, HNRNPCL1, HOOK3, KIAA1109, KIF26A, KMT2B, KMT2C, KRAS, LAMA2, LRP1B, MLH1, MON2, MRE11A, MSH2, MSH6, MTOR, NBN, PALB2, PHEX, PIK3CA, PIK3R1, PLXNB2, PLXND1, PMS2, POLE, POLR3B, PPP2R1A, PTEN, PTPN13, RAD50, RAD51, RAD51B, RAD51C, RAD51D, RAD52, RAD54B, RAD54L, RICTOR, SACS, SIGLEC9, SLC19A1, SLX4, SPEG, STT3A, TAF1, TAF2, TAS2R31, TFAP2C, TNC, TONSL, TP53, TTC6, UBA7, VNN1, WT1, XIRP2, ZBED6, ZC3H13, ZFHX3, ZFHX4, ZMYM4.

  Study EGAS00001005914

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Pancreatic_Organoids

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003520

• Thymic epithelial transplantation for complete DiGeorge syndrome: RNA (2025-07-22)

  Single cell transcriptomics study of thymic transplant biopsies Allogeneic thymus transplantation is the only curative therapy for complete DiGeorge Syndrome (cDGS), a rare severe primary immunodeficiency characterised by athymia. GOSH is one of only two centres worldwide to offer this treatment. Despite a lack of major histocompatibility complex (MHC)-matching between donor and host, transplanted thymus becomes repopulated by recipient bone marrow derived precursor cells and supports development of functional T-cells. The mechanisms underlying thymopoiesis in this context are poorly understood, but over time we observe reconstitution of T-cell immunity, with the ability to produce host naïve T-cells showing a broad T-cell receptor (TCR) repertoire and to generate MHC-restricted T-cell proliferative responses. Although lifesaving, the achieved immunological reconstitution is typically not complete with circulating T-cell numbers usually remaining below the age related normal ranges. Additionally, we observe persistence of donor-derived T-cells of unknown clinical significance. To gain more insight into the mechanisms by which MHC-mismatched transplanted thymus supports T-cell development with self-tolerance, as well as into the basis of suboptimal T-cell immunity, we now aim to investigate immune reconstitution after thymus transplantation in further detail by using single-cell transcriptomics, applied to thymic transplant biopsies and peripheral blood samples collected during standard post-transplant patient care. By identifying which lineages of host- derived cells repopulate the thymic tissue after transplantation, we will be able to address the role of MHC in positive and negative T-cell selection during T-cell differentiation. We will also be able to clarify the exact ontogeny of the persistent donor T-cells, as well as their possible role. Understanding the mechanisms of action of HLA-mismatched transplanted thymus will contribute to treatment optimisation. Additionally, our research provides a unique opportunity to further investigate key immunological concepts, such as tolerance and autoimmunity, challenging existing paradigms in thymus immunology. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2025-07-22.

  Dataset EGAD00001015648

• Functional single-cell characterization of immune aplastic anemia shows convergence of NK and NK-like CD8+ T cells with disease-associated TCR signature

  Immune aplastic anemia (AA) is a life-threatening bone marrow (BM) failure disorder driven by an autoimmune T cell attack against the hematopoietic stem and progenitor cells (HSPCs). However, the autoantigen targets and the role of other immune cells are unknown. Here, by analyzing an international cohort of 156 AA patients with scRNA+TCRαβ-seq, TCRβ-seq, flow cytometry, and plasma cytokine profiling with comparisons to healthy controls and patients with other hematological disorders, we identify NK cells and CD8+ TEMRA cells expressing NK receptors with AA-associated TCRβ-seq motifs as the most dysregulated immune cell populations in AA BM. Functional co-culture experiments with scRNA-TCRαβ-seq readout utilizing primary HSPCs and immune cells provide evidence that NK cellscannot kill HSPCs alone, but sensitize them to CD8+ T cell-mediated killing. Furthermore, HSPCs induce strong activation of T cell clones with CD8+ TEMRA NK-like phenotype and AA-associated TCR motifs. Our results reveal the convergent evolution of innate and adaptive immune cells in AA, where NK cells support CD8+ T cell-mediated autoimmunity.

  Study EGAS00001007602

• Functional single-cell characterization of immune aplastic anemia shows convergence of NK and NK-like CD8+ T cells with disease-associated TCR signature

  Immune aplastic anemia (AA) is a life-threatening bone marrow (BM) failure disorder driven by an autoimmune T cell attack against the hematopoietic stem and progenitor cells (HSPCs). However, the autoantigen targets and the role of other immune cells are unknown. Here, by analyzing an international cohort of 156 AA patients with scRNA+TCRαβ-seq, TCRβ-seq, flow cytometry, and plasma cytokine profiling with comparisons to healthy controls and patients with other hematological disorders, we identify NK cells and CD8+ TEMRA cells expressing NK receptors with AA-associated TCRβ-seq motifs as the most dysregulated immune cell populations in AA BM. Functional co-culture experiments with scRNA-TCRαβ-seq readout utilizing primary HSPCs and immune cells provide evidence that NK cellscannot kill HSPCs alone, but sensitize them to CD8+ T cell-mediated killing. Furthermore, HSPCs induce strong activation of T cell clones with CD8+ TEMRA NK-like phenotype and AA-associated TCR motifs. Our results reveal the convergent evolution of innate and adaptive immune cells in AA, where NK cells support CD8+ T cell-mediated autoimmunity.

  Study EGAS00001007604

• Massively parallel functional dissection of schizophrenia associated non-coding genetic variants

  Schizophrenia (SCZ) is a severe mental disorder affecting 1% of the world population. SCZ is characterized by an underlying genetic architecture that is highly polygenic. Genome wide association studies have identified thousands of genetic variants that are statistically linked to the disease. However, the translation of these associations into insights on the pathomechanisms has been challenging because the causal genetic variants, their molecular function, and their target genes remain largely unknown. To address these questions, we combined induced pluripotent stem cell technology with a massively parallel variant annotation pipeline (MVAP) to functionally characterize 35,000 SCZ associated non-coding genetic variants. This approach identified a set of 620 (1.7%) single nucleotide polymorphisms as functional on the molecular level in a highly cell type and condition specific fashion. Subsequent multi-modal integration of epigenomic data combined with CRISPR screening in human neurons enabled us to systematically translate SCZ variant associations into target genes, biological processes, and ultimately alterations of neuronal physiology. These results provide a new high-resolution map of functional variant-gene combinations and offer comprehensive biological insights into the developmental context and stimulus dependent molecular processes modulated by SCZ genetic variation beyond statistical association.

  Study EGAS00001007542

• Transcriptomic analysis of peripheral blood dendritic cells and monocytes from patients with familial chilblain lupus and hetereozygous mutations in TREX1

  Study EGAS00001006215

• Clean sequence of LUAD in young never-smoker

  we conducted whole genome sequencing (WGS) to characterize the genomic alterations of 36 never-smoker Chinese patients with lung adenocarcinomas (LUADs). This dataset is containing clean fastq files of 36 never-smoker Chinese patients with lung adenocarcinomas (LUADs)

  Dataset EGAD00001003890

• KASP1-22

  234 samples genotyped at 15 loci LGC Genomics, Hoddesden, UK using the PCR-based KASP assay (Semagn,e tal (2014). Single nucleotide polymorphism genotyping using Kompetitive Allele Specific PCR (KASP): overview of the technology and its application in crop improvement. Mol Breeding 33, 1–14.)

  Dataset EGAD00010001905

• Tumor reactive γδ T cells contribute to a complete response to PD-1 blockade in a Merkel cell carcinoma patient

  Single cell RNA and TCR sequencing of γδ T cells FACS sorted from peripheral blood of two Merkel cell carcinoma patients

  Dataset EGAD50000000137

• Redefined indel taxonomy reveals insights into mutational signatures

  Deposited here are whole-genome sequencing bam files from the experimental isogenic cell lines used in the study "Redefined indel taxonomy reveals insights into mutational signatures, Koh, Gene (2023)".

  Dataset EGAD50000000209

• WGS of human colorectal cancer organoid exposed to genotoxic pks+ E. coli

  Organoid cultures were exposed to different E.Coli strains and a dye control. In total 25 organoid cultures were whole-genome sequenced using the Novaseq6000 platforms. The data is deposited as .bam format.

  Dataset EGAD50000000304

• A neoadjuvant, phase II trial demonstrates efficacy and tolerability of Talimogene laherparepvec in cutaneous basal cell carcinoma (NeoBCC trial)

  This dataset is related to the NeoBCC trial and includes 12 human tissue samples

  Dataset EGAD50000000371

• Cityscape Source Tables

  Source data of clinical study data corresponding to figures reported in the paper titled: Anti-TIGIT antibody improves PD-L1 blockade through myeloid and Treg cells. PMID: 38418879 DOI: 10.1038/s41586-024-07121-9

  Dataset EGAD50000000366

• GO30103 Source Tables

  Source data of clinical study data corresponding to figures reported in the paper titled: Anti-TIGIT antibody improves PD-L1 blockade through myeloid and Treg cells. PMID: 38418879 DOI: 10.1038/s41586-024-07121-9

  Dataset EGAD50000000367

• OAK GO28915 Source Table

  Source data of clinical study data corresponding to figures reported in the paper titled: Anti-TIGIT antibody improves PD-L1 blockade through myeloid and Treg cells. PMID: 38418879 DOI: 10.1038/s41586-024-07121-9

  Dataset EGAD50000000368

• Mutational Landscape Determines Sensitivity to PD-1 Blockade in Non-Small Cell Lung Cancer

  Patients with non-small cell lung cancer were treated with pembrolizumab. Their tumors and matched normal blood were sequenced.

  Study phs000980

• RNASeq of PAX4 KO vs WT in 7 stages of differentiation from human iPSCs to BLC

  Transcriptomes were profiled along with the differentiation from human induced pluripotent stem cell (iPSC) to beta-like cell (BLC) with PAX4 knocked out or not.

  Dataset EGAD00001008582

• NTNU Data Access Committee for “ProstOmics: spatial and bulk multi-omics of prostate cancer” datasets archived in Federated EGA Norway

  The ProstOmics project of NTNU contains spatial and bulk multi-omics datasets of prostate cancer, and access request to these datasets are handled by this Data Access Committee on behalf of NTNU.

  Dac EGAC50000000277

• Paired Biopsy Project: West Coast Dream Team

  This project contains the 16 WGS tumor samples and the corresponding 15 WGS normal tissue samples (germline control) not yet deposited in the public domain (e.g., EGA, dbGaP) at the time of submission of the manuscript (Zhu et al.)

  Dataset EGAD50000000473

• Chemotherapy induces myeloid-driven spatial T-cell exhaustion in ovarian cancer

  Gene expression profiles of single cells from 26 chemo-naïve and IDS tumor tissue and ascites samples from 17 HGSC patients

  Study EGAS50000000607

• DAC Dr. PORTEU – Gustave Roussy

  Targeting Heterochromatin Eliminates Malignant Stem Cells in Chronic Myelomonocytic Leukemia Through Reactivation of Retroelements and Innate Immune pathways Data Access Committee Members (Name, Email, Job Title): Principal Investigator PORTEU Françoise (FRANCOISE.PORTEU@gustaveroussy.fr) Head of Bioinformatics platform DELOGER Marc (Marc.DELOGER@gustaveroussy.fr) Data Protection Officer BECHET Clara (Clara.BECHET@gustaveroussy.fr)

  Dac EGAC50000000252

• PETAL trial Whole Exome Sequencing (WES)

  Associated with Molecular profiling of DLBCL patients treated in the PETAL trial. Whole Exome Sequencing (WES) of 224 Samples (162 Tumor + 62 Normal). WES was used for Molecular Profiling by simultaneous screening of mutations. Data is Complementary to sWGS.

  Dataset EGAD50000001172

• WGS data of 100 Breast Cancer patients from SV Based ctDNA Detection study

  Whole Genome Sequencing data of 100 Breast Cancer patients from "Ultrasensitive Detection and Monitoring of Circulating Tumor DNA using Structural Variants in Early-Stage Breast Cancer" study.

  Dataset EGAD50000001175

• B cell single cell sequencing (RNA + VDJ) - Autoproliferation

  10X 3' (RNA) and 10X 5' (VDJ) samples of B cells (non-proliferating/hi and autoproliferating/Dim) for healthy donor and Multiple sclerosis patients used in the paper.

  Dataset EGAD50000001237

• Methylome and transcriptome of memory B cells - Autoproliferation

  Methylome and the corresponding transcriptome of autoproliferating/Dim B cells and resting/hi B cells in Multiple sclerosis patients

  Dataset EGAD50000001236

• Short-read RNA-seq of doxycycline-inducible DUX4 human myoblast cell lines

  The dataset includes the short-read RNA sequencing data of DUX4i myoblasts (Clone-5 and Clone-7) with and without 16-hour DOX-treatment (n=1 in each condition).

  Dataset EGAD50000000719

• Tumor mutational landscape in individuals with CMMRD

  Whole exome sequencing data from the tumors (n=16) of individuals with constitutional mismatch repair deficiency. Data was aligned to GRCh38.

  Study EGAS50000000081

• Dataset for "HPV integration induces gene fusions" (pacBio)

  pacBio whole-genome sequencing data for "HPV integration induces gene fusions" We performed long read whole-genome sequencing on four HPV+ head and neck cancer samples using pacBio HiFi. The sequence reads were submitted in fastq format.

  Dataset EGAD50000001304

• Boyes Lab - DAC policy

  Access to this data is controlled. Upon request from a third party for access to the data, a separate Data Sharing Agreement would be put in place between the University of Leeds and the third party prior to EGA granting access to the data to the third party.

  Dac EGAC50000000283

• miRNA

  miRNA Sequencing of olfactory mucosa (OM) cells derived from cognitively healthy and individuals with AD exposed to traffic-related ultrafine particles (UFPs) for 72h in submerged cultures. The UFPs used for exposures were: A0 and A20. Exposures were compared to the corresponding blank samples.

  Dataset EGAD50000001532

• bulk RNAseq from metastatic uveal melanoma tumour biopsies

  Tumour biopsies were obtained from uveal melanoma patients (n = 35) pre and 16 days post treatment with tebentafusp. Biopsies, which were either snap frozen or put in RNA later, were analysed by bulk RNA sequencing (50 million reads per sample) using the Illumina NovaSeq system.

  Dac EGAC50000000519

• BCR repertoir sequences from human buffy coat purified B-Cells with DIS3 and control ASO

  This dataset contains BCR sequences of buffy coat purified B-cells from 5 healthy donors. For each sample, sequences were obtained in two conditions : with control Aso and Dis Aso treatment.

  Dataset EGAD50000001601

• RNA-seq in endometrial healthy and tumor tissues

  RNA has been extracted by Rneasy mini kit from around 30mg of flash frozen tissue derived from 3 healthy and 3 tumor endometrial tissues of post-menopausal patients. Raw paired-end fastq.gz files are provided.

  Dataset EGAD50000000200

• Whole genome sequencing data of cfDNA and WBC from 5 patients with mUC

  Whole genome Illunima sequencing of cfDNA of 5 metastatic urothelial carcinoma patients. White blood cell (WBC) samples are used as patient matched germline samples (n=5). All files are in paired-end fastq format.

  Dataset EGAD50000001570

• DNA methylation and transposable element landscapes in human regulatory and conventional Tcells

  Whole genome bisulfate sequencing using tagmentation of Tcells from skin and blood.The method improved TWGBS protocol (Weichenhan et al.), Methods Mol. Biol. 2018, vol. 1708 pp.105-122) was used

  Dataset EGAD50000001022

• Whole-exome-sequencing in Motor neuron disease (MND)

  To identify the genetic cause and modifiers of Motor neuron disease (MND), we performed Whole-exome-sequencing of Motor neuron disease (MND) patients.

  Study JGAS000422

• Whole-genome-sequencing and Whole-exome-sequencing in Myopathy

  To identify the genetic cause and modifiers of Myopathy, we performed Whole-genome-sequencing and Whole-exome-sequencing of Myopathy patients.

  Study JGAS000365

• Whole-exome-sequencing in Charcot-Marie-Tooth disease (CMT)

  To identify the genetic cause and modifiers of Charcot-Marie-Tooth disease (CMT), we performed Whole-exome-sequencing of CMT patients.

  Study JGAS000337

• Multi-modal spatial characterization of tumor-immune microenvironments identifies targetable inflammatory niches in diffuse large B-cell lymphoma

  This dataset includes NGS data of large B-cell lymphoma, including bulk RNAseq data of 71 biopsies and germline WES data of 70 biopsies.

  Dataset EGAD50000001641

• Microarray CDX or EDX from primary tumor and metastasis

  expression analysis of FACS sorted human cells from primary tumors and distant organs micrometastases in xenografts. Patient Derived xenografts were generated transplanting tumor cells from metastatic breast cancer patients into mammary fat pad of immunocompromised mice

  Dataset EGAD00010002711

• non-malignant plasma cfRNA

  Dataset contains mRNA capture sequencing data from plasma of 125 different human donors: 88 patients with a non-malignant disease and 37 cancer-free controls. Samples were sequenced on a NovaSeq X and sequencing data is provided in FASTQ format.

  Dataset EGAD50000001806

• Two scRNA-seq datasets from control and irradiated organoids.

  Dataset includes two scRNA-seq samples from control and irradiated organoids. Files included in the dataset are Fastq files. Sample libraries produced with Chromium X were sequenced on an Illumina NovaSeq 6000 sequencer.

  Dataset EGAD50000001933

• HOVON152 Trial Targetted Sequencing

  Associated with Molecular profiling of HGBCL-DH-BCL2 patients treated in the HOVON-152 triaL. Targeted sequencing of 30 samples from 30 High-grade B-cell lymphoma patients. Targeted sequencing was used for identify genomic alterations associated with patient outcome.

  Dataset EGAD50000002093

• CFTR Gene Variant Detection in Moroccan Individuals via Nanopore Long-Read Sequencing

  This study consists of sequencing the whole CFTR gene (coding and non-coding regions) using Oxford Nanopore on Moroccan CF patients

  Study EGAS50000001423

• Germline Pan-cancer Lynch syndrome sequencing dataset from India

  The dataset consists of germline whole exome sequencing data generated on the Illumina NovaSeq X Plus platform for 48 patients with MSI-high/ MMRd gastro-intestinal and genito-urinary cancers, in order to detect Lynch syndrome.

  Dataset EGAD50000002088

• Semibulk RNA-seq analysis as a convenient method for measuring gene expression statuses in a local cellular environment

  For two cases of breast cancers, semibulk RNA-seq and single cell RNA-seq were performed.

  Study JGAS000387

• Project for Development of Innovative Research on Cancer Therapeutics; Identifiying the predictive factors for response to chemoherapy in ovarian cancer

  To identify novel predictive biomarkers of response to chemotherapy for clear cell carcinoma of the ovary

  Study JGAS000076

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

  Whole exome sequencing 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 EGAD50000002137

• Department of Human Genetics at Yokohama City University (YCU) — Data Access Committee

  The Data Access Committee at Yokohama City University (Department of Human Genetics) is overseeing controlled access to data for our research manuscripts. Access is granted to bona fide researchers in line with the Data Access Agreement and DUO restrictions.

  Dac EGAC50000000770

• Single-cell multidimensional profiling of tumor cell heterogeneity in supratentorial ependymomas

  55 Supratentorial Ependymomas patient samples were sequenced scRNA-sequencing using Smart-Seq2 and 10x protocol (51 samples) and 10x Genomics protocol (4 samples) on a NextSeq 550 sequencer (Illumina).

  Dataset EGAD50000002186

• Multi-omics characterisation of the response to stimulation in Long Covid patients

  We stimulated immune cells of 15 patients (5 timepoints) with Long Covid with RPMI or P. Aeruginosa strains (4h stimulations).

  Study EGAS50000000143

• WGS of cfDNA in PDAC Breast Cancer and Matched Controls

  This dataset contains WGS data derived from plasma cfDNA. The cohort includes PDAC and breast cancer patients alongside matched controls. These data are intended to support research into ctDNA and genomic fragmentation patterns.

  Dataset EGAD50000002323

• 10x Genomics scRNA-seq for 3 samples

  This dataset contains 10x Genomics single-cell RNA-seq data from two primary leukemia samples and their corresponding patient-derived xenograft (PDX) models. All the 3 samples are in bam file type.

  Dataset EGAD50000001788

• RNA-seq for 8 samples

  This dataset contains RNA-seq data from 8 acute leukemia cases (diagnosis or relapse) belonging to a newly identified subtype, termed FOXF1/FENDRR ALL. All the 8 samples are in bam file type.

  Dataset EGAD50000001789

• ATAC-seq for 2 samples

  This dataset contains ATACseq data from ta primary sample and a patient derived model (PDX) of the novel FOXF1/FENDRR ALL subtype. All the 2 samples are in bam file type.

  Dataset EGAD50000001791

• Zimbabwe Mendelian Disorders Genomics DAC

  Data Access Committee responsible for reviewing and approving access requests to human genomic data generated from individuals with suspected Mendelian disorders. The DAC ensures ethical use of genomic data in accordance with institutional, national, and international guidelines, protecting participant privacy while enabling responsible data sharing for research purposes.

  Dac EGAC50000000963

• Fungal infection in neural tissue from Amyotrophic Lateral Sclerosis

  The study shows that fungus infection, isolated from neural tissue, can be a risk factor to develop Amyothophic lateral sclerosis (ALS).

  Study EGAS00001002473

• Landscape and significance of multiple mutations in oncogenes.

  This study is a comprehensive pan-cancer study of oncogenic multiple mutations (MMs) which includes long-read whole-genome sequencing data (n = 3).

  Study EGAS00001003763

• WES of multi-regional CRC samples

  BAM files of Whole Exome Sequencing (WES) experiment on multi-regional colorectal cancer (CRC) samples. 32 tumour and 16 normal samples corresponding to 16 patients were sequenced, which makes 32 tumour BAMs and 16 normal BAMs (48 BAMs in total).

  Dataset EGAD00001006165

• sWGS of CRC patients

  Paired end (47/98) and single end (51/98) shallow whole genome sequencing (sWGS) data for the identification of somatic copy number alterations (SCNA) and the estimation of tumor fractions in plasma DNA of colorectal cancer (CRC) patients.

  Dataset EGAD00001006101

• EPC (eccrine porocarcinoma) WES samples

  Whole-exome sequencing (WES) in a well-characterized sample of 14 matched EP tumour/healthy surrounding tissue samples. The sequencing was done with paired EXOME sequencing on Illumina HiSeq 4000 using Agilent SureSelect XT HS + Human All Exon V7.

  Dataset EGAD00001006395

• DKFZ-St.Jude Medulloblastoma - 3 XI046 SF controls, WGS data

  3 control whole genomes, SF cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006662

• Dataset for breast_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 12 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008867

• Phased melanoma whole genomes

  We have sequenced whole genomes of 10 melanoma samples (1 cell line; A375 and 9 patient derived short term cultures). Libraries were prepared with 10X linked reads technology in order to obtain phase information and subsequently sequenced on Illumina NovaSeq6000.

  Dataset EGAD00001005773

• Fibromyalgia versus small fiber neuropathy: Diverse keratinocyte transcriptome signature dataset

  We provide a diverse keratinocyte transcriptome signature between SFN and FMS patients, which may hint towards distinct pathomechanisms of small fiber sensitization and lay the basis for advanced diagnostics in both entities

  Dataset EGAD00001006918

• The University of Hong Kong Gastric Cancer RHOA Study RNASeq Data

  RNAseq data generated from paired tumor frozen tissues in which the tumor organoids were established for cell-cell or cell-matrix adhesion dependency assay.

  Dataset EGAD00001008830

• WES and RNA-seq raw sequence data for HIFI project

  WES sequence data from 15 samples, RNA-seq sequence data from 19 samples, all sequence data are raw pair-end sequence data in fastq format, sequenced by Illumina platform.

  Dataset EGAD00001004799