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• Insights into Adult Gut Microbiota Composition Using the Estonian Cohort

  This study explores the gut microbiota of 1,826 adult individuals, predominantly from the Estonian population. The cohort includes 16S rRNA gene V4 region amplicon sequencing data along with metadata, such as age, sex, health status, anthropometric parameters, and stool consistency. The research aims to characterise the microbial community structure, identify distinct enterotypes, and examine their associations with host characteristics. The dataset provides a valuable reference for understanding gut microbiota composition and supports research in personalised nutrition and lifestyle-related health strategies.

  Study EGAS50000001611

• The Genomic Complexity of Primary Human Prostate Cancer

  Seven primary prostate cancers and their paired normal counterparts were DNA-sequenced on a massively parallel sequencing platform. This approach was taken to investigate the genomes for mutations and genomic alterations that would be undetectable by lower-resolution methods. As result, tumors containing chains of balanced rearrangements that occurred within or adjacent to known cancer genes were discovered.

  Study phs000330

• A benchmark of DNA methylation deconvolution methods for tumoral fraction estimation using DecoNFlow

  In cancer patients, circulating cell-free DNA (cfDNA) originates from both healthy and cancer cells, and the proportion of tumor-derived cfDNA serves as a surrogate marker of tumor burden. Tumoral cfDNA can be identified using patient-specific mutations or more general tumor-specific DNA methylation patterns that are preserved in cfDNA, enabling non-invasive cancer detection and monitoring. Accurately estimating tumor fractions remains challenging due to the heterogeneous mixture of cfDNA sources in body fluids. Computational DNA methylation deconvolution methods can address this by estimating tumoral fraction with or without reference methylomes. Here, we benchmarked 10 reference-based and 2 reference-free DNAm deconvolution tools and provide the data generated for this benchmarking, consisting of 10 neuroblastoma cell lines and one healthy cfDNA sample (pooled from 15 healthy cfDNA samples), profiled using cfRRBS.

  Study EGAS50000001529

• Recurrent adeno-associated virus 2-related insertional mutagenesis in human hepatocellular carcinomas

  Hepatocellular carcinomas (HCC) are liver tumors related to various etiologies including alcohol intake, hepatitis B (HBV) or C (HCV) virus infection. Additional risk factors remain to be identified, particularly in patients who develop HCC without cirrhosis. We identified clonal integration of adeno-associated virus type 2 (AAV2) in 11 out of 193 HCC. These AAV2 integrations occurred within known cancer driver genes, namely, CCNA2 (Cyclin A2, 4 cases), TERT (Telomerase Reverse-Transcriptase, 1 case), CCNE1 (Cyclin E1, 3 cases), TNFSF10 (Tumor Necrosis Factor member 10, 2 cases) or KMT2B (Lysine (K)-Specific Methyltransferase 2B, 1 case) leading to over-expression of the target genes. Tumors with viral integration mainly developed in non-cirrhotic liver (9 out of 11 cases) and without known risk factors (6 out of 11) suggesting a pathogenic role of AAV2 in these patients. In conclusion, AAV2 is a DNA virus associated with oncogenic insertional mutagenesis in human HCC.

  Study EGAS00001001284

• Single-cell RNA-seq of bronchoalveolar lavage (BAL) fluid of late stage severe COVID-19 patients

  COVID-19-induced ‘acute respiratory distress syndrome’ (ARDS) is associated with prolonged respiratory failure and high mortality, but the mechanistic basis of lung injury remains incompletely understood. Here, we analyzed pulmonary immune responses and lung pathology in two cohorts of patients with COVID-19 ARDS using functional single cell genomics, immunohistology and electron microscopy. We describe an accumulation of CD163-expressing monocyte-derived macrophages, that acquired a profibrotic transcriptional phenotype during COVID-19 ARDS. Gene set enrichment and computational data integration revealed a significant similarity between COVID-19-associated macrophages and profibrotic macrophage populations identified in idiopathic pulmonary fibrosis. COVID-19 ARDS was associated with clinical, radiographic, histopathological, and ultrastructural hallmarks of pulmonary fibrosis. Exposure of human monocytes to SARS-CoV-2, but not Influenza A virus or viral RNA analogs, was sufficient to induce a similar profibrotic phenotype in vitro. In conclusion, we demonstrate that SARS-CoV-2 triggers profibrotic macrophage responses and pronounced fibroproliferative ARDS.

  Study EGAS00001005634

• CLL targeted exome sequencing (2018-03-14)

  Aim to characterise cancer gene landscape in CLL, particularly in cases with mutated POT1 gene. Treatment-naive CLL cases will be interrogated by targeted exome sequencing using a cancer gene panel. . This dataset contains all the data available for this study on 2018-03-14.

  Dataset EGAD00001004037

• Bisulphite MPN colonies (2019-09-05)

  Swift kit whole genome bisulphite of MPN colonies . This dataset contains all the data available for this study on 2019-09-05.

  Dataset EGAD00001005313

• Genetic architecture of autism spectrum disorder in India

  The dataset consists of whole exome sequencing data (fastq format) of 100 non-syndromic autism spectrum disorder patients from India. Whole exome sequencing data is generated using Agilent SureSelect v6 capture kit and Illumina HiSeq sequencing platform. Paired end fastq files are available.

  Dataset EGAD00001008621

• scEC&T-seq manuscript data

  This dataset includes all data produced in the study describing "scEC&T-seq", a method for parallel sequencing of extrachromosomal circular DNA and transcriptome in single cells. This dataset includes: - Illumina scEC&T-seq Circle-seq data (scCircle-seq) for a total of 626 single cells / nuclei - bam files - Illumina scEC&T-seq RNA-seq data (scRNA-seq-Illumina) for the same single cells / nuclei - bam files - Nanopore scCircle-seq data for 18 single cells - bam files - Nanopore bulk WGS for 2 cell lines and 2 primary tumor samples - bam files - Illumina bulk WGS for 2 cell lines - bam files - Illumina bulk Circle-seq data from 1 cell line - bam file - Illumina ChIP-seq H3K27me3 data from 1 cell line - fasta files + peaks bed file + coverage bw file

  Dataset EGAD00001010071

• Genetic origins of the Kiritimati population from central-eastern Micronesia

  The migration of Austronesian-speaking populations through Oceania has intrigued researchers for decades. The Kiribati islands, situated along the boundaries of Micronesia and Polynesia, provide a crucial link in this migration. We analyzed the genome-wide data of the Kiritimati population of Kiribati to uncover their genetic origins and connections with other Oceanian groups. Our study reveals that the Kiritimati population primarily exhibits Remote Oceanian-related ancestry associated with ancient Lapita and present-day Polynesian populations. In addition, our identity-by-descent analysis identifies populations from Philippines as their closest relatives in Island Southeast Asia. The genetic links between Kiritimati, ancient Lapita, and modern Polynesians underscore the shared ancestry and continuous gene flow across these regions. This genetic continuity and ongoing links are supported by linguistic and cultural evidence, illustrating a complex history of migration and admixture in Oceania.

  Study EGAS00001008060

• Lymphocyte LCM WGS (2020-02-20)

  Using whole genome sequencing of lymphocytes excised from human tissue using laser capture microscopy (LCM), we identify the mutations arising in these microenvironments. This work will contribute towards developing a catalogue of mutations present in tissue resident lymphocytes across a range of tissues, and will characterize the mutational signatures that result from each microenvironment. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005992

• Deep targeted DNA sequencing dataset for the study "Molecular characteristics in Burkitt lymphoma over age groups"

  We performed deep targeted DNA sequencing with a panel of 134 selected cancer-related genes previously identified to be recurrently mutated in BL/B-AL. A Nextera rapid capture custom kit was designed using the Illumina DesignStudio. For every gene, all regions in which previous mutations had been described were covered. For 40 of these genes, the entire coding sequence was covered. Targeted deep sequencing was performed on a MiSeq-Sequencer using MiSeq Reagent Kit v2 (300 cycle) with 24 samples per run. There are 396 samples in this targetedDNAseq-dataset with 298 tumors (288 patients and 10 cell lines) and 98 normals. There are 132 female, 262 male, and 2 unknown gender samples in this dataset.

  Dataset EGAD00001007708

• Population Genetic Testing and SERPINA1 Sequencing Identifies Unidentified Alpha-1 Antitrypsin Deficiency Alleles and Gene-Environment Interaction with Hepatitis C Infection

  Design and aims: Data were available through an institutional effort to combine de-identified electronic health records (EHR) data with genomic information from a DNA biobank. The design of this work was a retrospective cohort study in which we investigated the rates of liver transplantation and hepatitis C infection as it relates to genotype risk for alpha-1 antitrypsin deficiency (AATD). We used regression analysis to look for relationships between these risks and outcomes. This led to further investigation of environmental exposures and phenotypes as it related to the underlying genotypic risk. Population information: The cohort consisted of 72,027 individuals of European ancestry for whom genotype and EHR data were available. Molecular technologies employed: Genome-wide genotyping was previously performed using the Illumina Infinium Expanded Multi-Ethnic Genotyping Array plus custom content (referred to as the Vanderbilt University Medical Center BioVU MEGAEX). Individuals' AATD-related alleles were inferred from the genotyping data. Principal findings of the study: Liver transplantation was associated with presence of the Z AATD allele and with hepatitis C infection. There was a significant interaction between AATD genotype groups and hepatitis C infection as it related to liver transplantation. Data available through dbGaP: Inferred AATD genotype status, sex, age, length of EHR in years, presence/absence of AATD clinical diagnosis, liver transplant status, and hepatitis C infection status.

  Study phs003297

• A WTCCC2 genome-wide association study for psychosis endophenotype (PE) in individuals from UK, Germany, Holland, Spain and Australia.

  A WTCCC2 project genome-wide association study for psychosis endophenotype (PE) in 5831 individuals from UK, Germany, Holland, Spain and Australia, genotyped on the Affymetrix 6.0 array. Information about the family structure of the samples can be found in the .info file which accompanies the data. It should be noted that a number of samples in this study have no phenotype information including sex, case status and family membership. Details of the WTCCC2 analysis can be found in Bramon et al. [Biol Psychiatry. 2014 Mar 1;75(5):386-97].

  Study EGAS00001000817

• Neuroblastoma cell-lines and healthy cfDNA used for the benchmarking study

  This dataset comprises nine neuroblastoma cell lines used to construct the reference matrix for the RRBS-CL dataset in the corresponding benchmarking study. In addition, it includes one extra neuroblastoma cell line and a pooled cfDNA sample from multiple donors, which were used to generate the in silico mixtures. All the samples were profiled using DNA methylation sequencing.

  Dataset EGAD50000002199

• Infant Spindle Tumour Study (2019-04-11)

  We aim to describe the transcriptomic landscape of infant spindle cell tumours. . This dataset contains all the data available for this study on 2019-04-11.

  Dataset EGAD00001004954

• Dataset for 9 samples from the study EGAS00001007891

  This dataset links 9 samples from the study "Phosphoproteomics adds value to treatment recommendations in molecular tumor boards" (EGAS00001007891) to the study EGAS00001007934. Further information about the samples can be found in the respective studies.

  Dataset EGAD50000002316

• Response labels from NABUCCO cohort 1 (NCT03387761)

  Data from NABUCCO cohort 1 (NCT03387761). This dataset includes the Response labels used for the analysis of the data. Details about the clinical definitions of Response can be found on the paper (https://doi.org/10.1038/s41591-020-1085-z)

  Dataset EGAD00001006853

• Molecular Biomarkers Predicting Lung Cancer Response Phenotypes

  We have used a "chemistry first" approach to discover druggable acquired vulnerabilities that arised in the pathogenesis of non-small cell lung cancer (NSCLC). We screened chemical libraries (~200,000 compounds) for chemical toxins that killed subsets of NSCLC but not normal human lung epithelial cells (HBECs). We first screened a panel of 12 NSCLC lines that represented a variety of known oncogenotypes and identified chemicals with large Z scores and appropriate properties including re-supply, chemistry, and reproducible drug response phenotypes. This was then narrowed down to a list of 202 chemicals and 18 drugs with known targeting (henceforth called "Precision Oncology Probe Set", or POPS). These, and a panel of 30 clinically available drugs, targeted therapies, and drug combinations, already in use or in trials for NSCLC treatment, were then tested on a panel of 96 NSCLC lines for their drug response phenotypes in 12-point dose response curves. This information was analyzed using scanning ranked KS (Kolmogorov-Smirnov) and elastic net biostatistics approaches to identify molecular biomarkers (mutations, mRNA expression, copy number variation, protein expression, and metabolomics) which could predict for sensitivity or resistance to a particular chemical toxin or treatment regimen. From this we have discovered that: our approach identifies already known molecular biomarker of drug sensitivities (e.g. EGFR mutations and EGFR TK inhibitors); many clinically available chemotherapy agents have molecular biomarkers predicting preclinical model drug responses; the POP set of chemical toxins provides novel drug response phenotype patterns in the large NSCLC panel different from those found with clinically available agents including a therapeutic window; many of the POP toxins only hit a small percentage (~5%) of the NSCLC panel but the POP set as a whole provides "coverage" of the entire NSCLC panel; there are simple, one or 2 component molecular biomarkers (mutations, mRNA expression) that predict responses to the different chemical toxins in the NSCLC panel; and that the molecular biomarkers provide some information on the targets and pathways involved in response to the chemical toxins. Thus, we have identified a group of chemical toxins with selectivity for subsets of NSCLC and associated tumor molecular biomarkers to facilitate their development for precision medicine, and also, in some cases, information on the targets and pathways interdicted by these chemical compounds. In addition, we have discovered NSCLC predictive biomarkers for clinically available agents.

  Study phs001823

• Multi-omics analysis reveals immune programs delineating disease severity in extrapulmonary tuberculosis

  This study investigates the immune response in extrapulmonary tuberculosis (EPTB) using a combination of bulk and single-cell RNA sequencing. Hierarchical clustering of patient transcriptomes identified three distinct levels of disease severity, uncovering immunological pathways involved in disease progression, including interferon and IL-1β-mediated signaling. The findings also led to the development of a diagnostic gene expression signature for both EPTB and pulmonary TB, offering potential improvements in TB diagnosis and treatment.

  Study EGAS50000000668

• Multi-omics analysis reveals immune programs delineating disease severity in extrapulmonary tuberculosis

  This study investigates the immune response in extrapulmonary tuberculosis (EPTB) using single-cell RNA sequencing. Hierarchical clustering of patient transcriptomes identified three distinct levels of disease severity, uncovering immunological pathways involved in disease progression, including interferon and IL-1β-mediated signaling. The findings also led to the development of a diagnostic gene expression signature for both EPTB and pulmonary TB, offering potential improvements in TB diagnosis and treatment.

  Study EGAS50000000758

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__BRCA_Carriers__Exome_

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastectomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer.

  Study EGAS00001003316

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__BRCA_Carriers__Targeted_

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastectomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Targeted data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer.

  Study EGAS00001003315

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Cancer_Mastectomy__Targeted_

  Sequencing of LCM-derived microbiopsies from 30 women who mastectomies due to Breast Cancer. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Targeted data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with germline BRCA 1/2 mutations.

  Study EGAS00001003318

• Pan Prostate Cancer Group data

  The Pan Prostate Cancer Group intends to provide breakthrough advances from the analysis of a very large series of Whole Genome DNA data, contributed by many of the leading scientists and clinicians working in prostate cancer genomics generating Whole Genome DNA Sequence (WGS) data from prostate cancer patients. The accumulated data, collected and compared in a common format including common storage, re-analysis through a single pipeline, and investigation to achieve a variety of scientific goals, are presented in this series. This project will provide a global framework for the future analysis of even larger series of genomes as costs of DNA sequencing, storage, and sequence analysis decrease. In addition to these WGS data from different clinical categories, ethnicities, levels of aggressiveness, and disease managed by different treatments with information linked to long-term clinical follow up, we intend to add additional layers of data, including transcriptome and methylation data. The current data series focuses primarily on the analysis of WGS data. For further information, please refer to https://panprostate.org/, and The Pan Prostate Cancer Group Data Sharing Policy, EGAP00001003712.

  Study EGAS00001002876