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• Reconstructing oral cavity tumor evolution through brush biopsy

  Oral potentially malignant disorders (OPMDs) with genomic alterations have a heightened risk of evolving into oral squamous cell carcinoma (OSCC). Currently, genomic data are typically obtained through invasive tissue biopsy. However, brush biopsy is a non-invasive method that has been utilized for identifying dysplastic cells in OPMD but its effectiveness in reflecting the genomic landscape of OPMDs remains uncertain. This pilot study investigates the potential of brush biopsy samples in accurately reconstructing the genomic profile and tumor evolution in a patient with both OPMD and OSCC. We analyzed single nucleotide variants (SNVs), copy number aberrations (CNAs), and subclonal architectures in paired tissue and brush biopsy samples. The results showed that brush biopsy effectively captured 90% of SNVs and had similar CNA profiles as those seen in its paired tissue biopsies in all lesions. It was specific, as normal buccal mucosa did not share these genomic alterations. Interestingly, brush biopsy revealed shared SNVs and CNAs between the distinct OPMD and OSCC lesions from the same patient, indicating a common ancestral origin. Subclonal reconstruction confirmed this shared ancestry, followed by divergent evolution of the lesions. These findings highlight the potential of brush biopsies in accurately representing the genomic profile of OPL and OSCC, proving insight into reconstructing tumor evolution.

  Study EGAS50000000602

• Transcriptome sequencing of human colon organoid after co-cultivation with Bifidobacterium longum

  The large intestine has a dense milieu of indigenous bacteria, generating a complex ecosystem with crosstalk between individual bacteria and host cells. In vitro host cell modeling and bacterial interactions at the anaerobic interphase have elucidated the crosstalk molecular basis. Although classical cell lines derived from patients with colorectal cancer including Caco-2 cells are used, whether they adequately mimic normal colonic epithelial physiology is unclear. To address this, we performed transcriptome profiling of Caco-2 and Monolayer cells derived from healthy Human Colonic Organoid (MHCO) cultured hemi-anaerobically. Coculture with the anaerobic gut bacteria, Bifidobacterium longum subsp. longum differentiated the probiotic effects of test cells from those of physiologically normal intestinal and colorectal cancer cells. We cataloged non- or overlapping gene signatures where gene profiles of Caco-2 cells represented absorptive cells in the small intestinal epithelium, and MHCO cells showed complete colonic epithelium signature, including stem/progenitor, goblet, and enteroendocrine cells colonocytes. Characteristic gene expression changes related to lipid metabolism, inflammation, and cell-cell adhesion were observed in cocultured live Bifidobacterium longum and Caco-2 or MHCO cells. B. longum-stimulated MHCO cells exhibited barrier-enhancing characteristics, as demonstrated in clinical trials. Our data represent a valuable resource for understanding gut microbe and host cell communication.

  Study JGAS000740

• Genome-Wide Association Study of the Taste and Hedonic Ratings of the Low-Calorie Sweetener Acesulfame Potassium

  Acesulfame potassium (Ace-K) is a low-calorie sweetener (LCS) widely used as an additive in foods and beverages and an excipient in pediatric medicines. Because genetic variants play a role in individual variation in the taste of Ace-K, we sought to identify genetic contributions to its taste using a genome-wide association study (GWAS). 141 adult panelists rated the taste of an aqueous solution of Ace-K using the general labelled magnitude scale (gLMS) and its palatability using the hedonic gLMS. Genotypes were assayed on the Infinium Global Screening Array. Imputation of genotypes was performed on the Michigan Imputation Server with 1000 Genomes Project phase 3 genotype data as reference. Linear regression was performed to test genetic associations between genotyped and imputed variants with three gLMS ratings (bitterness (square-root-transformed), hedonic, sweetness) of Ace-K using PLINK2, adjusting for standardized age, sex, and the first 10 principal components of genetic ancestry. We identified that a locus spanning several TAS2R (Taste receptor 2) genes was associated with bitterness ratings of Ace-K and a locus within the gene ELMO1 (Engulfment and Cell Motility Protein 1) was associated with hedonic ratings of Ace-K (p-values 40594245).

  Study phs004031

• Drug Development against Tumor Microtube Networks in Glioblastoma

  Glioblastomas are aggressive brain tumors that resist current therapies by hijacking neurodevelopmental programs to invade the brain and form resilient multicellular networks. Tumor Microtubes (TMs), neurite-like processes extended by cancer cells, drive this pathobiology, but TM-inhibiting drugs are lacking. Here we developed a comprehensive, combined in vitro and in vivo drug screening approach, including novel AI-based analysis tools of TM parameters. Two Protein Kinase C (PKC) activators, TPPB and PMA, exhibited robust inhibition of TM formation in cell-based assays. Since unconnected glioblastoma cells exhibit increased sensitivity to cytotoxic therapy in vivo, brain tumor-bearing mice received TPPB, the most consistent TM-inhibiting compound, in combination with radiotherapy. Long-term intravital 2-photon microscopy confirmed anti-TM and anti-tumor effects of the co-treatment. Mechanistically, TPPB treatment inhibited several key molecular and functional components of TM-related glioblastoma cell network communication and decreased the expression of TTYH1, a key driver of invasive TMs. By establishing a novel screening pipeline for anti-TM drug development, our study identifies a druggable TM master regulator pathway and a small molecule with robust anti-TM effects. It provides a proof-of-principle that disrupting TMs and disconnecting tumor networks is a pharmacologically feasible strategy to make therapies against glioblastoma more effective.

  Study EGAS50000000477

• Recurrent somatic JAK-STAT mutations within a novel RUNX1-mutated pedigree

  The acquisition of somatic mutations is an emerging field of investigation in familial leukemia. Currently, genetic profiles in familial MDS/AML are considered analogous to sporadic disease, although the patterns of clonal evolution within families are poorly defined. We performed whole exome profiling of tumour samples from a novel RUNX1 mutated family, to determine the stepwise evolution of MDS/AML across 4 young siblings. Three siblings developed monocytic AML/RAEB2 at 5 years of age, with hepatosplenomegaly and somatic mutations upregulating JAK-STAT signalling, the latter are typically detected in <5% of sporadic MDS/AML. Two siblings acquired the canonical JAK2 V617F mutation, while another acquired a unique missense mutation of SH2B3, a negative regulator of JAK2. Notably, 2/3 siblings demonstrated dosage amplification of these mutations due to acquired uniparental disomy of chromosomes 9p and 12q (encompassing JAK2 and SH2B3, respectively). All 4 siblings were heterozygous for the 46/1 JAK2 haplotype associated with predisposition to sporadic V617F myeloproliferative disorders, which likely influenced the acquisition of JAK2 mutations. Our findings provide further evidence that relatives with shared germline mutations may acquire somatic mutations in a non-random manner leading to convergent patterns of disease evolution.

  Study EGAS00001001862

• Genomics of enteropathy associated T cell lymphoma (EATL)

  Enteropathy-associated T cell lymphoma (EATL) is a lethal and the most common neoplastic complication of celiac disease. In this study, we applied whole exome sequencing in 69 EATL tumors to define the genetic landscape of EATLs. The most frequently mutated gene in EATL was SETD2 (32% of cases), with loss of function mutations comprising a large proportion (41%) of those mutations. The JAK-STAT pathway was the most frequently mutated signaling pathway, with mutations in STAT5B being the most common, followed by JAK1, JAK3, STAT3, and the negative regulator of the pathway, SOCS1. We also identified mutations in NRAS and KRAS, as well as TP53 and TERT. Interestingly, the two types of EATL had highly overlapping genetic alterations indicating shared mechanisms underlying their pathogenesis. Gene expression analysis of the two types of EATL identify robust differences in transcriptional profiles. We further modeled the effects of SETD2 loss in vivo by developing a T cell specific knockout mouse model. These mice manifested an expansion of γδ T cells that identify novel roles for SETD2 in T cell development and lymphomagenesis. Together, our data render the most comprehensive genetic portrait yet of this uncommon but lethal disease, and may inform future classification schemes.

  Study EGAS00001001954

• Comprehensive genomic profiles of small cell lung cancer

  We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. We found bi-allelic inactivation of TP53 and RB1 in nearly all the tumors analyzed, sometimes by complex genomic rearrangements. Two tumors with wild-type RB1 had evidence of chromothripsis leading to overexpression of Cyclin D1, revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumor suppressors TP53 and RB1 is obligatory in SCLC. We further discovered somatic genomic rearrangements of TP73 that create an oncogenic version of this gene, TP73Δex2/3. In few cases, SCLC tumors exhibited kinase gene mutations, providing a possible therapeutic opportunity for individual patients. Finally, we observed inactivating mutations in NOTCH family genes in 25% of human SCLC. Accordingly, activation of Notch signaling in a pre-clinical SCLC mouse model dramatically reduced the number of tumors and extended the survival of the mutant mice. Furthermore, neuroendocrine gene expression was abrogated by Notch activity in SCLC cells. This first comprehensive study of somatic genome alterations in SCLC uncovers several key biological processes and identifies candidate therapeutic targets in this highly lethal form of cancer.

  Study EGAS00001000925

• The_Genomic_Advances_in_Sepsis__GAinS__RNA_seq

  Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. This cohort comprises a subset of patients enrolled in the Genomic Advances in Sepsis (GAinS) study, an established biobank of adult sepsis patients. Patients with sepsis due to community acquired pneumonia or faecal peritonitis were recruited from 34 hospitals across the UK from 2005-2018, with samples for functional genomics and detailed clinical information collected on the first, third and/or fifth day following ICU admission. RNA was extracted from leukocytes isolated at the bedside using LeukoLOCK kits. We have previously identified sepsis response signatures (SRSs), transcriptomic endotypes that are associated with differential early mortality (Davenport et al, Lancet Respir Med, 2016; Burnham et al, AJRCCM, 2017) and response to treatment in a clinical trial (Antcliffe et al, AJRCCM, 2018). We generated RNA sequencing data on 903 samples, including 134 samples repeated from our previously released microarray data. Libraries were prepared using NEB Ultra II Library Prep kits (Illumina) and sequenced on a NovaSeq 6000. Reads were aligned to the reference genome (GRCh38) using STAR and gene counts quantified using featureCounts (annotation Ensembl v99). Counts were TMM-normalised and log-transformed. Following QC, processed data were available on 864 samples from 667 unique patients.

  Study EGAS00001003772

• THE GENOMIC LANDSCAPE OF ACTINIC KERATOSIS

  Actinic keratoses (AK) are lesions of epidermal keratinocyte dysplasia and are pre-cursor lesions to invasive cutaneous squamous cell carcinoma (cSCC). Identifying the specific genomic alterations driving the progression of normal skin to AK and invasive cSCC is challenging due to the massive, ultraviolet radiation-induced mutational burden characteristic to these lesions. Here, we present the largest whole exome sequencing study to date on AK with matched cSCC and demonstrate that AK and cSCC are almost indistinguishable at the genomic level, in terms of mutational burden, patterns of driver gene mutations and copy number alterations. We identified 44 significantly mutated AK driver genes through our established bioinformatics pipeline and demonstrate these genes are similarly mutated in cSCC. We also identified mutational signature-32 exclusively in AK from patients exposed to azathioprine, providing further, compelling evidence for this drug’s role in keratinocyte carcinogenesis, likely through its blocking of transcription coupled repair. We demonstrated that cSCC had higher levels of intra-sample heterogeneity than AK and that several signaling pathways, including immune-related signaling and TGF-beta signaling were significantly more mutated in cSCC. Integrating our findings with independent gene expression data confirms that dysregulated TGF-beta signaling may represent the critical pathway in the progression from AK to cSCC.

  Study EGAS00001004243

• Single-cell RNA sequencing reveals the mesangial identity and species diversity of glomerular cell transcriptomes

  Molecular characterization of the individual cell types in human kidney as well as model organisms are critical in defining organ function and understanding translational aspects of biomedical research. Previous studies have uncovered gene expression profiles of several kidney glomerular cell types, however, important cells, including mesangial (MCs) and glomerular parietal epithelial cells (PECs), were missing or incompletely described, and a systematic comparison between mouse and human kidney is lacking. To this end, we used Smart-seq2 to profile 4332 individual glomerulus-associated cells isolated from human living donor renal biopsies and mouse kidney. The analysis revealed genetic programs for all four glomerular cell types (podocytes, glomerular endothelial cells, MCs and PECs) as well as rare glomerulus-associated macula densa cells (MDCs). Importantly, we detected heterogeneity in glomerulus-associated Pdgfrb-expressing cells, including bona fide intraglomerular MCs with the functionally active phagocytic molecular machinery, as well as a unique mural cell type located in the central stalk region of the glomerulus tuft. Furthermore, we observed remarkable species differences in the individual gene expression profiles of defined glomerular cell types that highlight translational challenges in the field and provide a guide to design translational studies.

  Study EGAS00001004943

• Human leukocyte antigen alleles associate with COVID-19 vaccine immunogenicity and risk of breakthrough infection

  SARS-CoV-2 vaccine immunogenicity varies between individuals, and immune responses correlate with vaccine efficacy. Using data from 1,076 participants enrolled in ChAdOx1 nCov-19 vaccine efficacy trials in the United Kingdom, we find that inter-individual variation in normalised antibody responses against SARS-CoV-2 spike (S) and its receptor binding domain (RBD) at 28 days following first vaccination shows genome-wide significant association with major histocompatibility complex (MHC) class II alleles. The most statistically significant association with higher levels of anti-RBD antibody was HLA-DQB1*06 (P=3.2 x 10-9), which we replicate in 1,677 additional vaccinees. Individuals carrying HLA-DQB1*06 alleles were less likely to experience PCR-confirmed breakthrough infection during the Wuhan and Alpha-variant waves compared to non-carriers (HR 0.63, 0.42-0.93, P=0.02). We identify a distinct S-derived peptide that is predicted to bind effectively to HLA-DQB1*06 compared to other equivalent alleles, and find evidence of increased spike-specific memory B-cell responses in HLA-DQB1*06 carriers at 84 days post first vaccination. Our results demonstrate association of HLA type with COVID-19 vaccine antibody response and risk of breakthrough infection, with implications for future vaccine design and implementation.

  Study EGAS00001006909

• Targeting TRIP13 in Wilms Tumor with Nuclear Export Inhibitors

  Wilms tumor (WT) is the most common renal malignancy of childhood. Despite improvements in the overall survival, relapse occurs in ~15% of patients with favorable histology WT (FHWT). Half of these patients will succumb to their disease. Identifying novel targeted therapies in a systematic manner remains challenging in part due to the lack of faithful preclinical in vitro models. We established ten short-term patient-derived WT cell lines and characterized these models using low-coverage whole genome sequencing, whole exome sequencing and RNA-sequencing, which demonstrated that these ex-vivo models faithfully recapitulate WT biology. We then performed targeted RNAi and CRISPR-Cas9 loss-of-function screens and identified the nuclear export genes (XPO1 and KPNB1) as strong vulnerabilities. We observed that these models are sensitive to nuclear export inhibition using the FDA approved therapeutic agent, selinexor (KPT-330). Selinexor treatment of FHWT suppressed TRIP13 expression, which was required for survival. We further identified in vitro and in vivo synergy between selinexor and doxorubicin, a chemotherapy used in high risk FHWT. Taken together, we identified XPO1 inhibition with selinexor as a potential therapeutic option to treat FHWTs and in combination with doxorubicin, leads to durable remissions in vivo.

  Study EGAS00001007389

• Multiple_Malignancy_Familial_Comparison

  Patient (who has had multiple malignancies) has previously been found to harbour a pathogenic p53 variant which is probably mosaic. This finding is based on exome sequencing performed elsewhere. In this study we will resequence the locus in question to ascertain whether the variant is indeed mosaic.

  Study EGAS00001000333

• Compilation of Aggregate Genomic Data for General Research Use

  This study contains all authorized aggregate genomic data from datasets currently in dbGaP that are approved for general research use (GRU) and have no further limitations beyond those outlined in model Data Use Certification Agreement. Access to this study will be granted for one year and any additional authorized aggregate GRU datasets that become available during this one-year period. This study does not include individual-level data.

  Study phs000501

• Meta-analysis of Genome-Wide-Association Sudies for plasma Factor XI

  Coagulation factor XI (FXI) has become increasingly interesting for its role in pathogenesis of thrombosis. We performed a genome-wide association study (GWAS) for plasma FXI levels, using novel data imputed to the 1000 Genomes reference panel. Individual GWAS analyses, including a total of 16,169 European individuals from the ARIC, GHS, MARTHA and PROCARDIS studies, were meta-analyzed, and results are presented here.

  Study EGAS00001002123

• University of Michigan Clinical Sequencing Exploratory Research (CSER)

  Overview. The personalization of therapy for cancer will require molecular characterization of unique and shared genetic aberrations. In particular, patients who have a sarcoma or other rare cancers and are candidates for clinical trials could potentially benefit by identifying eligibility for "targeted" drugs based on the "actionable" genes in their specific tumor. Growing technological advances in genomic sequencing has now made it possible to consider the use of sequence data in a clinical setting. For instance, comprehensive testing that includes whole exome and transcriptome sequencing may identify biomarkers for predictive or prognostic purposes and thereby inform treatment choices and prevention strategies. Thus, the translation of high throughput next generation sequencing would support a "personalized" strategy for cancer. However, the translation of clinical sequencing bears unique challenges including identifying patients who could benefit, developing informed consent and human subjects protections, outlining measurable outcomes, interpreting what results should be reported and validated, and how results should be reported. In addition, we know very little about how patients and clinicians will respond to the potentially confusing and overwhelming amount of information generated by genomic sequencing, and we lack model processes for clinically evaluating and presenting these data. For the promise of our innovative biotechnologies to be realized, "translational genomics" research that evaluates genomic applications within real-world clinical settings will be required. This proposal brings together expertise at the University of Michigan including clinical oncology, cancer genetics, genomic science/bioinformatics, clinical pathology, social and behavioral sciences, and bioethics in order to implement this clinical cancer sequencing project. Three integrated Projects have the following themes: Project 1) "Clinical Genomic Study" will identify patients with a rare cancer (i.e., 15 out of 100,000 individuals per year) who are eligible for clinical trials, consent them to the study, obtain biospecimens (tumor tissue, germline tissue), store clinical data, and assemble a multi-disciplinary Sequencing Tumor Board to deliberate on return of actionable or incidental genomic results; Project 2) "Sequencing & Analysis" will process biospecimens and perform comprehensive sequencing and analysis of tumors to identify point mutations, copy number changes, rearrangements/gene fusions, and aberrant gene expression; Project 3) "Ethics & Psychosocial Analysis" will observe the expert review process for evaluating sequence results and will examine the clinician and patient response to the informed consent process, delivery of genomic sequence results, and use of genomic results.

  Study phs000673

• DATA FILES FOR SJOS

  DATA FILES FOR SJOS

  Dataset EGAD00001000159

• DATA FILES FOR SJLGG

  DATA FILES FOR SJLGG

  Dataset EGAD00001000161

• Screening for abnormal CGI methylation in primary colorectal tumours

  Screening for abnormal CGI methylation in primary colorectal tumours

  Dataset EGAD00001000213

• DATA FILES FOR SJLGG

  DATA FILES FOR SJLGG

  Dataset EGAD00001000352

• DATA FILES FOR SJLGG

  DATA FILES FOR SJLGG

  Dataset EGAD00001000353

• Saliba Lab Data Access Committee

  DAC for data generated by Saliba Lab at Helmholtz institute for RNA-based Infection Research, Würzburg, Germany

  Dac EGAC50000000152

• RNA-Seq data for Juvenile Pilocytic Astrocytomas

  RNA-Seq data for 9 JPA samples.

  Dataset EGAD00001009043

• WGS and WXS files for Dyer ATRX study

  WGS and WXS files for Dyer ATRX study

  Dataset EGAD00001003389

• Molecular Biomarkers of Obesity and Metformin Response in Endometrial Cancer: Analysis of GOG-0286B

  The primary endpoint for the phase 2 study was progression free survival (PFS), and the primary endpoint for the phase 3 study was overall survival (OS). Data from phase 2 were included in the phase 3 analysis. Tissue was collected from patients with endometrial cancer who participated in the study (NCT02065687). The tissue will be analyzed for genetic data and combined with the clinical data to see if some gene variants are associated with longer PFS or OS, particularly on the metformin arm of the study.

  Study phs002934

• Whole Exome Sequencing in Familial Parkinson Disease

  We have an ongoing study that has recruited families having at least a sibling pair with Parkinson disease (PD). Families have been screened for mutations in known PD causative genes (LRRK2, parkin, etc). Following review of families without a causative mutation, we selected families for whole exome sequencing that had the strongest history of PD and with the most definitive diagnosis. All families have at least 3 affected family members who were evaluated as part of this study. Only affected family members were included for whole exome sequencing.

  Study phs000376

• Reconstitution of Human Brain Cell Diversity in Organoids via Four Protocols [time-course bulkRNAseq]

  Time-course bulk-RNA sequencing of brain organoids grown in four distinct growth protocols designed to generate dorsal (D) and ventral (V) forebrain, midbrain (M) and striatum (S) tissue at days 13 (for dorsal and ventral)/16 (for midbrain and striatum), 25, 40, 80 and 120. Per per cell line-protocol-timepoint combination three organoids (biological replicates) were grown. For reference, also three samples of the pluripotent stem cells across cell lines, not yet exposed to any protocol, were sequenced (day 0, pluripotent).

  Study EGAS50000000663

• ctDNA Quantification in Blood Plasma Using Deep Learning Based Fragle Tool

  The project aims to develop an easy to use software named Fragle that can quantify ctDNA in blood plasma. This can help in cancer screening and progress monitoring from simple blood test without any need for tumor biopsy. We aim to make Fragle usable for both low pass whole genome sequencing and targeted sequencing data of cell free DNA. Fragle can work directly on the raw bam files mapped to hg19/GRCh37. We are uploading the bam files used in this study for Fragle evaluation.

  Study EGAS50000000122

• The_Causes_of_Clonal_Blood_Cell_Disorders_Study___SCOR_Custom

  We took a bone marrow aspirate and peripheral blood samples from a healthy patient aged around 60, and use flow cytometry to isolate 100 HSCs, 50 MEPs, and 50 GMPs. We grew these up into colonies, then whole genome sequenced each colony. Somatic mutations act as a unique barcode for each clone. We have designed a panel for targeted resequencing of the mutations that we find. We are now looking for these mutations in the peripheral blood, to see the dynamics of how HSCs contribute to the peripheral blood in health.

  Study EGAS00001002257

• Osteosarcoma mate-pair and RNA-sequencing

  DNA mate pair and RNA sequencing data of conventional osteosarcomas. Mate pair libraries, with average insert sizes of 2-4 kb, were prepared for sequencing using the Nextera Mate Pair Library Preparation Kit. Paired-end 76 base pair reads were generated using an Illumina NextSeq 500 sequencing instrument. Total RNA was enriched for polyadenylated RNA using magnetic oligo(dT) beads. Enriched RNA was prepared for sequencing using the TruSeq RNA Sample Preparation Kit v2 and paired-end 151 base pair reads were generated from the cDNA libraries using an Illumina NextSeq 500 instrument.

  Study EGAS00001003842

• KIR gene content imputation from single-nucleotide polymorphisms in the Finnish population

  The killer cell immunoglobulin-like receptor (KIR) gene cluster on chromosome 19 encodes cell surface glycoproteins that bind class I human leukocyte antigen (HLA) molecules as well as some other ligands. KIR gene gene copy number variation associates with the outcome of transplantations and susceptibility to immune-mediated diseases. Here we describe a stand-alone and freely available gene content imputation for 12 KIR genes. The models were trained using 818 Finnish biobank samples genotyped for 5774 KIR-region SNPs and analysed for KIR gene content with targeted sequencing.

  Study EGAS00001005457

• Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia

  In this study we generated single-cell whole transcriptome and surface marker expression data for 24 samples of 19 AML patients as well as one healthy donor. We followed the CITEseq protocol with the 3' 10x Genomics scRNAseq kit version 3.1 To increase the coverage of the mitochondrial genome we generated mitochondrial libraries following a protocol termed Optimized 10x. Based on TAPseq, we generated libraries to increase the coverage of selected nuclear SNVs. Exome sequencing was generated for 15 patients to identify nuclear variants. Bulk ATAC was obtained for 9 samples to facilitate the discovery of mitochondrial SNVs. MutaSeq (modified version of SmartsSeq2) was performed on cells from 3 patients. Targeted DNAseq from single-cell derived colonies was generated for 1 patient.

  Study EGAS00001007078

• Evolutionary landscape of clonal hematopoiesis in 3359 individuals from the general population

  This project contains longitudinal data for processed somatic variant calls and data on core phenotypic variables for 3359 community-based individuals ≥60 years, a sub-cohort of the population-based Lifelines cohort (167,729 participants). Cases with peripheral blood count abnormalities and population-based controls were included. Next-generation sequencing data were generated with a median time period of 43 months between baseline and follow-up visit. For 327 individuals a third visit sample was included. Error-corrected sequencing was performed using single-molecule tagged molecular inversion probes targeting 27 myeloid and lymphoid driver genes. The threshold for variant calling was set at ≥1% VAF and ≥10 consensus variant reads. Details on sample selection, sequencing technique, variant calling procedures and data curation are described (van Zeventer et al. 2023).

  Study EGAS00001007087

• Haukeland University Hospital Data Access Committee for ParkOme-1 datasets archvied in Federated EGA Norway

  Data Access Committee appointed by Haukeland University Hospital for omics datasets for Parkinson's disease and related disorders, generated in studies under the ParkOme-1 project. Omics datasets of different types are generated from fresh frozen brain tissue from individuals with neurodegenerative parkinsonisms and neurologically healthy controls.

  Dac EGAC50000000193

• Genome-wide analysis for non alcoholic fatty liver disease

  Genome-wide association study for the 902 patients of non alcoholic fatty liver disease (NAFLD) including non alcoholic steato hepatitis (NASH) and hepatocellurar carcinoma and 7672 controls.

  Study JGAS000126

• ChIP-seq fastq and alignment files

  ChIP-seq experiments: fastq files; both ChIP and Input for each sample. Illumina HiSeq 2500. ChIP-seq alignment files for trimmed, mapping q20 and nonredundant reads; both ChIP and Input for each sample. Software: Trim Galore v0.3.7; Bowtie 2 v2.1.0; samtools v1.7

  Dataset EGAD00001006279

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002901

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002904

• BLUEPRINT September 2016, ATAC-seq for unswitched memory B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for unswitched memory B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002905

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002906

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002910

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002921

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for germinal center B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002911

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002919

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002900

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from tonsil, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for germinal center B cell from tonsil, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002917

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=6days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=6days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002914

• BLUEPRINT September 2016, ATAC-seq for naive B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for naive B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002902

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002913

• GIS-LUNGTCR1-2016_WES-FASTQ

  This dataset contains FASTQ files for multi-region exome-sequencing of EGFR-mutant lung adenocarcinomas from Asian patient. There are 16 patients and 95 samples in total, including 16 controls and 79 tumors. Multiple runs for each sample, and 368 fastq in total. Please refer to the sample-ID from filename for merging.

  Dataset EGAD00001001978