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• Targeted_sequencing_of_blood_DNA_from_Human_twins_

  The goals of this study is to investigate the prevalence and heritability of age-related clonal haemopoeisis (ARCH) in healthy elderly individuals.We will use a bespoke bait set to pull down DNA regions of interest in whole blood samples combined with HiSeq at a deep level . By correlating findings from each individual to their respective twin we hope to elucidate whether heritable traits influence the development of ARCH. a. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002210

• Exome-wide analysis identifies three low-frequency missense variants associated with pancreatic cancer risk in Chinese populations

  Germline coding variants have not been systematically investigated for pancreatic ductal adenocarcinoma (PDAC). Here, we report an exome-wide investigation using the Illumina Human Exome Beadchip with 943 PDAC cases and 3,908 controls in the Chinese population, followed by two independent replicate samples including 2,142 cases and 4,697 controls. We identify three low-frequency missense variants associated with the PDAC risk: rs34309238 in PKN1 (OR = 1.77, 95% CI: 1.48-2.12, P = 5.35 X 10-10), rs2242241 in DOK2 (OR = 1.85, 95% CI: 1.50-2.27, P = 4.34 X 10-9) and rs183117027 in APOB (OR = 2.34, 95% CI: 1.72-3.16, P = 4.21 X 10-8).

  Study EGAS00001003040

• Molecular profiling of longitudinally observed small colorectal polyps: a cohort study

  Knowledge of the natural history of colorectal adenomas is limited because these lesions are removed upon detection. The few studies in which small adenomas have been left in situ for a limited period of time have shown that most lesions remain stable or even completely vanish. Lesions that have grown in size more often turn out to be advanced adenomas when resected. Specific DNA copy number changes (cancer associated events or CAEs) are associated with progression of adenomas to cancer. The aim of the study was to evaluate whether growth of small colorectal polyps left in situ is associated with specific molecular features.

  Study EGAS00001003284

• Exome-sequencing of two UFM individuals and their Fragile X family members.

  Fragile X syndrome (FXS) is a monogenic neurodevelopmental disease often caused by a CGG triplet expansion in the 5’UTR of the FMR1 gene, which results in DNA methylation of the FMR1 promoter and its transcriptional silencing. Exceptional healthy individuals named "unmethylated full mutation (UFM)" have been identified in the families of FX patients. They carry an expanded CGG repeat, but show normal FMR1 epigenetic configuration and expression. In this study we performed exome-sequencing of two UFM individuals and their family members to identify possible genetic mutations responsible for the escape of silencing in the unmethylated full mutation (UFM) phenotype.

  Study EGAS00001001737

• Native_American_Ancient_DNA_sequencing

  The morphology of the first humans in the Americas (Paleoamericans) differs from that of Native Americans, and has raised the question of whether or not there are also differences in origin or genetics. A few populations who survived until relatively recently have been suggested to retain Paleoamerican morphology. One of these populations is from La Jolla. Here, we have generated genome sequence data from four La Jolla individuals in order to investigate these questions This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001802

• Spatial and temporal genomic evolution in glioblastoma

  Tumor heterogeneity is a challenging barrier to successful targeted therapy in glioblastoma. Identifying the mechanisms that drive cancer cells as they genetically evolve and adapt in response to treatment is a vital goal of modern cancer research. Analysis of sequencing data provides a method for uncovering the mechanisms sustaining tumor heterogeneity and driving evolution. Here, we analyzed genomic profiles of GBM biopsies taken from pre- and post-treatment GBMs (with matched germline controls), to understand 1) the intratumoral clonal compositions of primary GBM and 2) how GBM responds to therapeutic intervention. Our results provide a molecular portrait of GBM recurrence.

  Study EGAS00001001033

• Investigating_low_frequency_variants_in_CAD_MI_cases__controls_and_pedigrees_using_whole_exome_sequencing_and_custom_pulldowns

  The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

  Study EGAS00001000043

• Investigating_low_frequency_variants_in_CAD_MI_cases__controls_and_pedigrees_using_whole_exome_sequencing_and_custom_pulldowns

  The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

  Study EGAS00001000050

• LifeLines-DEEP population multi-omix cohort from the noth of the Netherlands.

  The LifeLines-DEEP cohort is a sub-cohort of the LifeLines cohort (167,729 participants) that employs a broad range of investigative procedures to assess the biomedical, socio-demographic, behavioral, physical and psychological factors that contribute to health and disease in the general Dutch population, (Scholtens 2015). A subset of approximately 1,500 participants also took part in LifeLines-DEEP. For these participants, additional biological materials were collected, including analysis of the gut microbiome composition. The phenotyping and processing of LifeLines-DEEP has been described in Tigchelaar (2015).

  Study EGAS00001001704

• Somatic_mutation_and_clonal_evolution_in_premalignant_lung_disease___WGS

  Cancer is a genetic disease caused by an accumulations of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from the lung tissue of individuals with a variety of lung diseases (COPD, UIP, IPF, Emphysema, pulmonary hypertension). This will allow us to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. Smoking is a large risk factor for developing many of these lung diseases so we are particularly keen to determining whether there is evidence of a smoking signature in these patients.

  Study EGAS00001002747

• Genome Wide Association Study:GR@ACE Stage I

  The Genome Research program at Fundacio ACE (GR@ACE, Barcelona, Spain), represents a new effort to study Alzheimer's Disease susceptibility. The GR@ACE study comprises 7,409 unrelated individuals. 4,120 AD cases were diagnosed at Fundació ACE Memory Clinic (Barcelona, Spain). 3,289 Controls were obtained from three collections (Fundació ACE, Barcelona; DNA National Biobank, Salamanca and HU Valme, Seville). Genotyping was carried out using the 815K Axiom Spain Biobank array (Affymetrix.) in the Spanish national center for genotyping (CEGEN, Santiago de Compostela, Spain). After genotyping, an extensive quality control was conducted, including re-sampling, gender match, stratification, relatedness, heterozygosity, differential missingness and HWD analyses.

  Study EGAS00001003424

• MutWP5__CRUK_Mutographs_of_Cancer__Lung__PD38234__Targeted_

  Sequencing of LCM-derived microbiopsies from explanted lung from pulmonary fibrosis patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs.

  Study EGAS00001003325

• PTPN22 SNPs and outcome after lung transplantation

  Obstructive chronic lung allograft dysfunction (BOS) is the major limiting factor for lung transplantation (LTx) outcome. PTPN22 is described as the hallmark autoimmunity gene, and one specific single nucleotide polymorphism (SNP), rs2476601, is associated with multiple autoimmune diseases, impaired T cell regulation and autoantibody formation. Taking into consideration the contribution of autoimmunity to LTx outcome, we hypothesized that polymorphisms in the PTPN22 gene could be associated with BOS incidence. We selected six SNPs within PTPN22 and analyzed both patient and donor genotypes on BOS development post-LTx. A total of 144 patients and matched donors were included, and individual SNPs and haplotype configurations were analyzed.

  Study EGAS00001003380

• Overrepresentation of genetic variation in the AnkyrinG interactome is related to a range of neurological disorders

  Upon the discovery of numerous genes involved in the pathogenesis of neurodevelopmental disorders, several studies showed that a significant proportion of these genes converge on common pathways and protein networks. Here, we used a reversed approach, by screening the well-characterized AnkyrinG protein-protein interaction network, implicated in a variety of neurodevelopmental disorders, for genetic variation in a large cohort of 1009 cases with neurodevelopmental disorder. We identified a significant enrichment of de novo potentially disease-causing variants in this network, confirming that this protein network plays an important role in the emergence of several neurodevelopmental disorders.

  Study EGAS00001004326

• Volasertib preclinical activity in high-risk hepatoblastoma

  Relapsed and metastatic hepatoblastoma represents an unmet clinical need with limited chemotherapy treatment options. In a chemical screen, we identified volasertib as an agent with in vitro activity, inhibiting hepatoblastoma cell growth while sparing normal hepatocytes. Volasertib targets PLK1 and prevents the progression of mitosis, resulting in eventual cell death. PLK1 is overexpressed in hepatoblastoma biopsies relative to normal liver tissue. As a potential therapeutic strategy, we tested the combination of volasertib and the relapse-related hepatoblastoma chemotherapeutic irinotecan. We found both in vitro and in vivo efficacy of this combination, which may merit further preclinical investigation and exploration for a clinical trial concept.

  Study EGAS00001004827

• A GWAS in uveal melanoma identifies risk polymorphisms in the CLPTM1L locus.

  Uveal melanoma, a rare malignant tumor of the eye, is predominantly observed in populations of European ancestry. A genome-wide association study of 259 uveal melanoma patients compared to 401 controls all of European ancestry revealed a candidate locus at chromosome 5p15.33 (region rs421284: OR = 1.7, CI 1.43-2.05). This locus was replicated in an independent set of 276 cases and 184 controls. In addition, risk variants from this region were positively associated with higher expression of CLPTM1L. In conclusion, the CLPTM1L region contains risk alleles for uveal melanoma susceptibility, suggesting that CLPTM1L could play a role in uveal melanoma oncogenesis.

  Study EGAS00001002334

• Hepatitis B virus integrations promote local and distant oncogenic driver alterations in hepatocarcinogenesis

  Infection by Hepatitis B Virus (HBV) is the main risk factor for Hepatocellular Carcinoma (HCC) worldwide. HBV can directly drive carcinogenesis through integrations in human genome. This integrative analysis of a French cohort of 190 patients mainly coming from Europe and Africa provides a deep characterization of HBV integrations, in relation with viral and host genomics and clinical features. Clonal HBV integrations directly contribute to HCC development through alterations of cancer driver genes, either at distance when co-localizing with copy number alterations, either locally through viral Enhancers. Together, this analysis gives new insights on HBV-associated driver mechanisms involved in hepato-carcinogenesis.

  Study EGAS00001004629

• The landscape of somatic mutation in normal colorectal epithelial cells

  The colorectal adenoma-carcinoma sequence has provided a paradigmatic framework for understanding the successive somatic genetic events and consequent clonal expansions leading to cancer. As for most cancer types, however, understanding of the earliest phases of colorectal neoplastic change, which may occur in morphologically normal tissue, is comparatively limited because of the difficulty of detecting somatic mutations in normal cells. Each colorectal crypt is a small clone of cells derived from a single recently-existing stem cell. Here, we sequenced hundreds of normal crypts from 42 individuals. Signatures of multiple mutational processes were revealed, some ubiquitous and continuous, others only found in some individuals, in some crypts or during some phases of the cell lineage from zygote to adult cell. Likely driver mutations were present in ~1% of normal colorectal crypts in middle-aged individuals, indicating that adenomas and carcinomas are rare outcomes of a pervasive process of neoplastic change across morphologically normal colorectal epithelium.

  Dataset EGAD00001004192

• Genomic and ecologic characteristics of the airway microbial-mucosal complex

  Lung diseases due to infection and dysbiosis affect hundreds of millions of people world-wide. Microbial communities at the airway mucosal barrier are conserved and highly ordered, reflecting symbiosis and co-evolution with human host factors. We show here the results of the first systematic culture and whole-genome sequencing of the principal airway bacterial species. We match the gene content of bacterial isolates to human transcripts and metabolites expressed late in airway epithelial differentiation, identifying pathways that can sustain host interactions with the microbiota. Our results provide a systematic basis for decrypting interactions between commensals, pathogens, and mucosal immunity in lung diseases of global significance.

  Study EGAS00001006689

• Diet driven microbial ecology underpins associations between cancer immunotherapy outcomes and the gut microbiome

  This study profiled baseline gut (fecal) microbiota signatures and dietary patterns of 103 trial patients from Australia and the Netherlands treated with neoadjuvant ICIs for high risk resectable metastatic melanoma and performed an integrated analysis with data from 115 patients with melanoma treated with ICIs in the United States. We observed geographically distinct microbial signatures of response and immune-related adverse events. Overall, response rates were higher in Ruminococcaceae-dominated microbiomes than in Bacteroidaceae-dominated microbiomes. Poor response was associated with lower fiber and omega 3 fatty acid consumption and elevated levels of C-reactive protein in the peripheral circulation at baseline.

  Study EGAS00001006982

• Linked-read based analysis of Medulloblastomas

  Medulloblastoma (MB) is the most common type of malignant pediatric brain tumor with group 4 medulloblastomas (G4 MBs) accounting for 40% of cases of medulloblastomas. The molecular mechanisms that underlie this subgroup are still poorly understood. Point mutations are detected in a large number of genes at low incidence per gene while the detection of complex structural variants (SVs) in recurrently affected gene typically requires the application of long-read technologies. Here, we applied linked-read sequencing, which combines the long-range genome information of long-read sequencing with the high base pair accuracy of short read sequencing and very low sample input requirements.

  Study EGAS00001007064

• Comprehensive Deep Sequencing Atlas in HCC tumors

  Establishment of a comprehensive deep sequencing atlas focused on Hepatocellular Carcinoma (HCC) tumors, employing Whole Genome Sequencing (WGS), RNA Sequencing (RNAseq), and Whole Exome Sequencing (WES). The atlas aims to unravel the intricate genetic landscape of HCC, providing a detailed characterization of genomic alterations, transcriptomic profiles, and key mutations associated with this liver cancer. The integration of WGS, RNAseq, and WES data offers a holistic perspective, facilitating a deeper understanding of the molecular mechanisms driving HCC pathogenesis. The resulting atlas serves as a valuable resource for researchers, clinicians, and the broader scientific community, contributing to advancements in HCC diagnostics, prognostics, and therapeutic interventions.

  Study EGAS00001007694

• Isala Citizen Science Project: Cross-sectional branch

  The Isala Citizen Science Project, is named after the first female doctor in Belgium, Isala Van Diest (1842-1916). In a co-creative way, volunteers provided samples and data, proposed research objectives and survey questions, and helped to disseminate and interpret the objectives and results through different media platforms, jointly breaking taboos on women’s and vaginal health. In Flow 1, we collected a single sample from a cross-section of the population, characterized the microbiome, and associated it with data collected in questionnaires. Here, we provide extensive sample meta-data for over 3000 women who completed questionnaires on their lifestyle, diet, health, contraceptive use and environment.

  Study EGAS00001006934

• Raw multi-omics dataset from the lungNENomics cohort of lung neuroendocrine tumours

  This study contains raw multi-omics data generated as part of the lungNENomics project, a multi-omics study aimed at deep molecular profiling of lung neuroendocrine tumours, including typical carcinoids (grade 1) and atypical carcinoids (grade 2). The study includes whole-genome sequencing (WGS), RNA sequencing (RNA-seq), and Infinium MethylationEPIC array data from samples in the lungNENomics cohort. These raw data complement the associated processed molecular data released on Zenodo (10.5281/zenodo.19366762) and the corresponding whole-slide pathology images deposited in the EBI BioImage Archive (10.6019/S-BIAD3143). See Sexton-Oates et al medrxiv 2025 (https://www.medrxiv.org/content/10.1101/2025.07.18.25331556v1) for details.

  Study EGAS00001005979

• Host genotyping data from Dutch adult bacterial meningitis patients and linked bacterial genome sequences

  Streptococcus pneumoniae is a common nasopharyngeal colonizer, but can also cause life-threatening invasive diseases such as empyema, bacteremia and meningitis. Genetic variation of host and pathogen is known to play a role in invasive pneumococcal disease, though to what extent is unknown. This study includes 1146 samples of host genotyping data (genotyped and imputed) from Illumina Omni arrays. Samples were collected from adults (>16 yrs) patients with CSF confirmed bacterial meningitis in the Netherlands between 2006 and 2015. Metadata includes patient outcome, species of bacteria, and for 467 samples a link to an ENA run with the associated bacterial genome (S. pneumoniae only).

  Study EGAS00001005993

• Genomic landscape of malignant peripheral nerve sheath tumor (MPNST)

  Neurofibromatosis type 1 (NF1) is the most common tumor predisposition syndrome, and is associated with an aggressive soft-tissue sarcoma, malignant peripheral nerve sheath tumours (MPNSTs), the greatest cause of morbidity and mortality in people with NF1. The only potentially curative therapy involves surgery which is not always possible. Even therapy with curative intent is associated with poor overall survival for both sporadic and NF1-related MPNSTs. The development of novel therapies has been largely hindered by a lack of understanding of the molecular events underpinning MPNST pathogenesis. This is a comprehensive multi-omic study of MPNST evolution based on whole genome sequencing and transcriptomic data.

  Study EGAS00001006069

• Single-cell roadmap of immune cell responses in chronic myeloid leukemia

  To study the innate and adaptive immune responses in CML, we profiled 25 samples from CML patients including samples at diagnosis (n = 7, N = 9, where n is the number of subjects and N the number of samples if different from n) and before and after TKI-cessation with imatinib (n = 6, N = 15) with paired single-cell RNA and T cell receptor (TCR) αβ chain sequencing (scRNA+TCRαβ-seq) and compared our data to different cancers (n = 29) and healthy donors (n = 7). This dataset contains the samples from before and after TKI-cessation, please see the manuscript for info related to the other datasets.

  Study EGAS00001005044

• Single cell epigenomic study of H3-K27M mutant diffuse midline glioma across age and location

  Histone 3 lysine27-to-methionine (H3-K27M) mutations most frequently occur in childhood diffuse midline gliomas (DMGs) of the pons, but are also increasingly recognized in adult DMGs. Their potential heterogeneity at different ages and midline locations are vastly understudied. Here, through dissecting the single-cell epigenomic architectures of a comprehensive cohort of patient H3-K27M DMGs, we delineate how age and anatomical location shape glioma cell-intrinsic and -extrinsic features in light of the shared driver mutation. We analyzed the open chromatin profiles of 8 tumors utilizing the single-cell/nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq)

  Study EGAS00001007035

• Ovarian Cancer Organoid Biobank

  WGS of ovarian cancer organoids, tumor samples and blood references. Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a novel protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing the spectrum of ovarian neoplasms, including non-malignant borderline tumors, as well as mucinous, clear-cell, endometrioid, low- and high-grade serous carcinomas. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and inter-patient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

  Dataset EGAD00001004387

• Epigenome maps of time-resolved monocyte to macrophage differentiation and innate immune memory

  Innate immune memory is the phenomenon whereby innate immune cells such as monocytes or macrophages undergo functional reprogramming after exposure to microbial components such as LPS. We apply an integrated epigenomic approach to characterize the molecular events involved in LPS-induced tolerance in a time dependent manner. ChIP-seq, RNA-seq, WGBS and ATAC-seq data were generated. This analysis identified epigenetic programs in tolerance and trained macrophages, and the potential transcription factors involved. Experimental set-up Time-course in vitro culture of human monocytes. Two innate immune memory states can be induced in culture through an initial exposure of primary human monocytes to either LPS or BG for 24 hours, followed by removal of stimulus and differentiation to macrophages for an additional 5 days. Cells were collected at baseline (day 0), 1 hour, 4 hour, 24 hour and 6 days.

  Dataset EGAD00001002693

• THE GENOMIC LANDSCAPE OF ACTINIC KERATOSIS

  Actinic keratoses (AK) are lesions of epidermal keratinocyte dysplasia and are precursors for invasive cutaneous squamous cell carcinoma (CSCC). Identifying the specific genomic alterations driving progression from normal skin-AK-invasive CSCC is challenging due to the massive ultraviolet radiation-induced mutational burden characteristic at all stages of this progression. Here, we report the largest AK whole exome sequencing study to date and perform mutational signature and candidate driver gene analysis on these lesions. We demonstrate in 37 AK, from both immunosuppressed and immunocompetent patients, that there are significant similarities to CSCC in terms of mutational burden, copy number alterations, mutational signatures and patterns of driver gene mutations. We identify 44 significantly mutated AK driver genes and confirm that these genes are similarly altered in CSCC. We identify the azathioprine mutational signature in all AK from patients exposed to the drug, providing further evidence for its role in keratinocyte carcinogenesis. CSCC differ from AK in having higher levels of intra-sample heterogeneity. Alterations in signaling pathways also differ, with immune-related signaling and TGF-β signaling significantly more mutated in CSCC. Integrating our findings with independent gene expression datasets confirms that dysregulated TGF-β signaling may represent an important event in AK-CSCC progression.

  Dataset EGAD00001006894

• A110632A

  Whole genome sequencing for single cells for library A110632A 1151 cells; filetype=bam

  Dataset EGAD00001007094

• A110632B

  Whole genome sequencing for single cells for library A110632B 892 cells; filetype=bam

  Dataset EGAD00001007095

• A118833A

  Whole genome sequencing for single cells for library A118833A 919 cells; filetype=bam

  Dataset EGAD00001007096

• A118833B

  Whole genome sequencing for single cells for library A118833B 1147 cells; filetype=bam

  Dataset EGAD00001007097

• A118845B

  Whole genome sequencing for single cells for library A118845B 1209 cells; filetype=bam

  Dataset EGAD00001007098

• A118869A

  Whole genome sequencing for single cells for library A118869A 1165 cells; filetype=bam

  Dataset EGAD00001007099

• A118869B

  Whole genome sequencing for single cells for library A118869B 1124 cells; filetype=bam

  Dataset EGAD00001007100

• A95626A

  Whole genome sequencing for single cells for library A95626A 1040 cells; filetype=bam

  Dataset EGAD00001007103

• A95634B

  Whole genome sequencing for single cells for library A95634B 1335 cells; filetype=bam

  Dataset EGAD00001007105

• A95646A

  Whole genome sequencing for single cells for library A95646A 1071 cells; filetype=bam

  Dataset EGAD00001007106

• A95653B

  Whole genome sequencing for single cells for library A95653B 1342 cells; filetype=bam

  Dataset EGAD00001007107

• A95663B

  Whole genome sequencing for single cells for library A95663B 1364 cells; filetype=bam

  Dataset EGAD00001007108

• A95675A

  Whole genome sequencing for single cells for library A95675A 668 cells; filetype=bam

  Dataset EGAD00001007109

• A95731B

  Whole genome sequencing for single cells for library A95731B 1307 cells; filetype=bam

  Dataset EGAD00001007110

• A96115B

  Whole genome sequencing for single cells for library A96115B 1201 cells; filetype=bam

  Dataset EGAD00001007112

• A96118A

  Whole genome sequencing for single cells for library A96118A 1193 cells; filetype=bam

  Dataset EGAD00001007113

• A96130B

  Whole genome sequencing for single cells for library A96130B 1267 cells; filetype=bam

  Dataset EGAD00001007114

• A96178A

  Whole genome sequencing for single cells for library A96178A 788 cells; filetype=bam

  Dataset EGAD00001007115

• A96178B

  Whole genome sequencing for single cells for library A96178B 846 cells; filetype=bam

  Dataset EGAD00001007116

• A96181C

  Whole genome sequencing for single cells for library A96181C 1216 cells; filetype=bam

  Dataset EGAD00001007117

• A96225B

  Whole genome sequencing for single cells for library A96225B 959 cells; filetype=bam

  Dataset EGAD00001007119

• A96225C

  Whole genome sequencing for single cells for library A96225C 1034 cells; filetype=bam

  Dataset EGAD00001007120

• A96240A

  Whole genome sequencing for single cells for library A96240A 1493 cells; filetype=bam

  Dataset EGAD00001007121

• A98172A

  Whole genome sequencing for single cells for library A98172A 898 cells; filetype=bam

  Dataset EGAD00001007123

• A98256A

  Whole genome sequencing for single cells for library A98256A 1372 cells; filetype=bam

  Dataset EGAD00001007124

• A98256B

  Whole genome sequencing for single cells for library A98256B 1437 cells; filetype=bam

  Dataset EGAD00001007125

• A98257B

  Whole genome sequencing for single cells for library A98257B 1286 cells; filetype=bam

  Dataset EGAD00001007126

• A98258B

  Whole genome sequencing for single cells for library A98258B 1357 cells; filetype=bam

  Dataset EGAD00001007127

• A98274B

  Whole genome sequencing for single cells for library A98274B 1295 cells; filetype=bam

  Dataset EGAD00001007128

• A98282A

  Whole genome sequencing for single cells for library A98282A 1198 cells; filetype=bam

  Dataset EGAD00001007129

• A98283A

  Whole genome sequencing for single cells for library A98283A 1137 cells; filetype=bam

  Dataset EGAD00001007130

• A98285A

  Whole genome sequencing for single cells for library A98285A 1422 cells; filetype=bam

  Dataset EGAD00001007131

• A98295B

  Whole genome sequencing for single cells for library A98295B 1381 cells; filetype=bam

  Dataset EGAD00001007132

• The dataset for Detection and characterization of lung cancer using cell-free DNA fragmentomes

  The dataset for Detection and characterization of lung cancer using cell-free DNA fragmentomes includes 872 bam files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD00001007796

• A110673B

  Whole genome sequencing for single cells for library A110673B 1153 cells; filetype=bam

  Dataset EGAD00001007603

• A118830A

  Whole genome sequencing for single cells for library A118830A 912 cells; filetype=bam

  Dataset EGAD00001007604

• A118862A

  Whole genome sequencing for single cells for library A118862A 1070 cells; filetype=bam

  Dataset EGAD00001007605

• A118862B

  Whole genome sequencing for single cells for library A118862B 1152 cells; filetype=bam

  Dataset EGAD00001007606

• A95623B

  Whole genome sequencing for single cells for library A95623B 1363 cells; filetype=bam

  Dataset EGAD00001007608

• A95697B

  Whole genome sequencing for single cells for library A95697B 1233 cells; filetype=bam

  Dataset EGAD00001007610

• A95700A

  Whole genome sequencing for single cells for library A95700A 1172 cells; filetype=bam

  Dataset EGAD00001007611

• A95703A

  Whole genome sequencing for single cells for library A95703A 740 cells; filetype=bam

  Dataset EGAD00001007612

• A96233A

  Whole genome sequencing for single cells for library A96233A 637 cells; filetype=bam

  Dataset EGAD00001007622

• A95730A

  Whole genome sequencing for single cells for library A95730A 739 cells; filetype=bam

  Dataset EGAD00001007614

• A96114A

  Whole genome sequencing for single cells for library A96114A 798 cells; filetype=bam

  Dataset EGAD00001007615

• A96124B

  Whole genome sequencing for single cells for library A96124B 1241 cells; filetype=bam

  Dataset EGAD00001007616

• A96155C

  Whole genome sequencing for single cells for library A96155C 1316 cells; filetype=bam

  Dataset EGAD00001007617

• A96162A

  Whole genome sequencing for single cells for library A96162A 1505 cells; filetype=bam

  Dataset EGAD00001007618

• A96183B

  Whole genome sequencing for single cells for library A96183B 1191 cells; filetype=bam

  Dataset EGAD00001007619

• A96226B

  Whole genome sequencing for single cells for library A96226B 1274 cells; filetype=bam

  Dataset EGAD00001007621

• A98168A

  Whole genome sequencing for single cells for library A98168A 1294 cells; filetype=bam

  Dataset EGAD00001007624

• A98168B

  Whole genome sequencing for single cells for library A98168B 1290 cells; filetype=bam

  Dataset EGAD00001007625

• A98234A

  Whole genome sequencing for single cells for library A98234A 1240 cells; filetype=bam

  Dataset EGAD00001007626

• A98244A

  Whole genome sequencing for single cells for library A98244A 1271 cells; filetype=bam

  Dataset EGAD00001007628

• A98253A

  Whole genome sequencing for single cells for library A98253A 1250 cells; filetype=bam

  Dataset EGAD00001007629

• A98253B

  Whole genome sequencing for single cells for library A98253B 1388 cells; filetype=bam

  Dataset EGAD00001007630

• A98254A

  Whole genome sequencing for single cells for library A98254A 1490 cells; filetype=bam

  Dataset EGAD00001007631

• A98255B

  Whole genome sequencing for single cells for library A98255B 1394 cells; filetype=bam

  Dataset EGAD00001007632

• A98271A

  Whole genome sequencing for single cells for library A98271A 1190 cells; filetype=bam

  Dataset EGAD00001007633

• A98289A

  Whole genome sequencing for single cells for library A98289A 1066 cells; filetype=bam

  Dataset EGAD00001007634

• A98290B

  Whole genome sequencing for single cells for library A98290B 869 cells; filetype=bam

  Dataset EGAD00001007635

• A98305A

  Whole genome sequencing for single cells for library A98305A 986 cells; filetype=bam

  Dataset EGAD00001007637

• A108732A

  Whole genome sequencing for single cells for library A108732A 1139 cells; filetype=bam

  Dataset EGAD00001007592

• A108833B

  Whole genome sequencing for single cells for library A108833B 866 cells; filetype=bam

  Dataset EGAD00001007594

• A108842A

  Whole genome sequencing for single cells for library A108842A 1477 cells; filetype=bam

  Dataset EGAD00001007595

• A108863A

  Whole genome sequencing for single cells for library A108863A 1301 cells; filetype=bam

  Dataset EGAD00001007597

• A110618A

  Whole genome sequencing for single cells for library A110618A 1184 cells; filetype=bam

  Dataset EGAD00001007599

• Single Cell Genome Sequence for DLP+ library A118389B

  Single Cell Genome Sequence for Telomerase immortalized breast epithelium cell line 184-hTERT 85.14 p20 cell line AT135 on DLP+ library A118389B

  Dataset EGAD00001009433

• Single Cell Genome Sequence for DLP+ library A118782A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050B passage 1, patient-derived xenograft SA1050E passage 1 on DLP+ library A118782A

  Dataset EGAD00001009435