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• Association Between Telomere Length and Falciparum Malaria Endemicity in Sub-Saharan Africans

  The goal of this study was to identify the genetic and environmental drivers of telomere length variation in an ethnically diverse African cohort. It comprises 1,818 participants from Cameroon, Tanzania, Ethiopia, and Botswana. For each participant, leukocyte telomere length was measured using the Southern blotting of the terminal restriction fragment methodology. 1,758 of the individuals with phenotype data also had genetic data, and these individuals were subjected to a genome-wide association study which accounted for age, sex, and genetic relatedness. Individuals were genotyped on one of two genotyping arrays (Illumina Infinium Omni5 array or Illumina H3Africa consortium array). Genetic datasets were merged, and missing genotypes were imputed for a final genetic dataset of 11,001,107 genetic variants. Correlations between telomere length and a variety of environmental factors, including malaria endemicity, were also examined in this study.

  Study phs003567

• A Phase 2 Study of Tipifarnib in Large Granular Lymphocyte (LGL) Leukemia

  LGL leukemia can be divided into three subsets including the following: αβ or γδT-LGL and NK-LGL leukemia. All three subtypes will be enrolled using a two-stage design. The primary endpoint of the study is assessment of overall clinical response. Correlative laboratory studies will be performed aimed at determining the mechanism of response to treatment. Thirteen participants will be accrued in the first stage at a dose of 300 mg BID administered intermittently every other week (i.e., 7 days on and 7 days off). If there are two or more responders, the protocol will be extended to a second stage of the study and accrual will be extended to 25 evaluable participants. Allowing for 10% rate of ineligibility due to unexpected events and dropout, we will accrue 14 patients in the first stage and 27 patients in total. Participants that withdraw from the study for reason unrelated to toxicity, will be replaced. There are two potential stopping rules for toxicity. If 3 or more participants out of the 13 enrolled in the first stage experiences grade IV neurotoxicity, the study will be stopped due to excessive toxicity. Dose reductions have been incorporated for hematologic toxicity. Treatment of T and NK LGL leukemia with immunosuppressive agents such as low-dose methotrexate generally require from four to six months for a clinical response and sometimes much longer. Therefore, in participants who show clinical improvement with less than grade three toxicity, tipifarnib treatment will be continued for as many as four additional months (12 months total). After the first 8 months, response will be assessed. The protocol treatment will be discontinued in participants with progression of disease. A long-term follow up will be performed for five years in patients that receive a complete clinical response. The long-term follow up will consist of vital signs, weight, CBCs, serum chemistries, and physical examination at six month intervals.

  Study phs000594

• Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

  ChIP-Seq - CEBPE - REH. The ETV6/RUNX1 translocated acute lymphoblastic leukaemia cell line REH was used to perform ChIP-Seq using a CEBPE antibody. Cells were fixed in 1% formaldehyde for 10mins, prior to preparation of chromatin using Active Motif Express ChIP-IT. 2ug of antibody (anti CEBPE Atlas Antibodies HPA002928)was added to 25ug of chromatin O/N at 4C with rotation. Duplicate reactions were pooled and purified. 10ng of ChIPd and input DNA used for Illumina NGS preparation (NEBNext ChIP-Seq Library kit; New England Biolabs), CEBPE and Input DNA ChIP samples were sequenced on a MiSeq using 150bp Kit v3 paired end and a HiSeq 2500 using 2x101 version 4 paired end (Illumina) respectively. Reactions performed in duplicate. shCEBPE RNA-Seq - REH. REH cells were lentivirally transduced with a pTRIPZ shRNA vector for transcriptional profiling of CEBPE. Two controls (empty and non-targeting) and two CEBPE shRNAs (V3THS_150517(A13), V3THS_404312(G3) Dharmacon, GE) were transduced into REH cells. Cells were treated with 1ug/ml doxycyclin for 144hrs and total RNA purified. Libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kit and sequenced on an Illuimna HiSeq 2500 using 2x101 version 4 paired end chemistry. 3 biological replicates of each samples were prepared.

  Study EGAS00001002877

• Count Me In (CMI): The Angiosarcoma (ASC) Project (CMI-ASCproject)

  Count Me In - The Angiosarcoma Project: A Patient-Partnered Research Initiative to Accelerate Research in a Rare Sarcoma The Angiosarcoma Project (ASCproject) is a research study that directly engages angiosarcoma patients online and empowers them to accelerate cancer research by sharing medical information and clinical samples. Angiosarcoma is an exceedingly rare soft tissue sarcoma with an incidence of ~300 newly diagnosed cases per year in the United States. This low incidence has impeded large-scale research efforts in this disease that are strongly needed to catalyze research and improve clinical outcomes. The Angiosarcoma Project, launched in March 2017, has demonstrated the feasibility of directly engaging geographically dispersed patients to democratize research and establish a large patient cohort to characterize the genomic and clinical landscape of a rare disease. Angiosarcoma patients living in the US or Canada can access the study and consent online through an online portal (ASCproject.org). Enrolled patients are mailed saliva and blood draw kits, which can be used to extract germline DNA and cell-free DNA (cfDNA), respectively. The study team contacts participants' healthcare institutions to obtain medical records and a portion of archived tumor samples. All received tumor samples are subjected to centralized histological re-review by an expert pathologist to confirm a diagnosis of angiosarcoma. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing is performed on tumor RNA. De-identified data, including linked genomic, clinical, and patient-reported data, are shared via public databases on a recurring pre-publication basis. Participants are regularly provided updates on the study.

  Study phs001931

• UQCCR/QCMG brain metastasis sequence analysis

  The present study, conducted by the UQCCR and QCMG at the University of Queensland, investigated the genomic landscape of brain metastases from 36 patients (with matched normal samples) that originated from a range of primary tumour sites (including breast (11), lung (18), melanoma (6) and oesophageal (1)) utilizing Illumina 2500 HiSeq Exome sequencing. Somatic substitutions were identified using a dual qSNP/GATK calling strategy. The Pindel tool was used to determined short insertions and deletions. Key biological pathways were investigated using pathway analysis tools. It is envisaged that the current work may provide important biological insights into the genomic characterization and evolution of brain metastasis and additionally identify druggable targets of clinical relevance.

  Study EGAS00001000722

• Kids First: The Genomic Architecture of Hirschsprung Disease (HSCR)

  Hirschsprung disease (HSCR) is a male biased developmental disorder associated with a lack of innervation of the gastrointestinal tract. Genetic studies have been instrumental in understanding its multifactorial inheritance, high heritability, syndromic associations, and genetic heterogeneity with variable penetrance and expressivity. At least 24 genes and 9 loci with pathogenic alleles (PAs) are known to underlie HSCR pathogenesis and explain 62% of its population attributable risk (PAR). Despite this heterogeneity, there is functional unity in HSCR: ~53% of HSCR PAs disrupt RET and EDNRB signaling in the developing enteric nervous system (ENS) in which 11 genes comprising a gene regulatory network control RET and EDNRB gene expression. We propose to identify the remaining 30% PAR by studying 857 unrelated HSCR cases, their 125 affected and 1,446 unaffected firstdegree relatives by whole genome sequencing to increase statistical power of gene discovery through improved detection of all types of coding and regulatory PAs. HSCR arises from cell autonomous defects in enteric neural crest cell precursors (ENCCs) affecting their proliferation, differentiation and migration in the ENS, functional studies that will guide our detection of novel genes.

  Study phs003662

• Disease-Linked Regulatory DNA Variants and Homeostatic Transcription Factors in Epidermis

  The role of non-coding variants in polygenic skin disease and their connection to homeostatic transcription factors (TFs) in epidermis was investigated. Homeostatic TFs were identified by perturb-seq in differentiating keratinocytes, using either 10x or split-pool approaches to sequencing, with follow-up validation by siRNA and RNA-seq. TF binding events were profiled by population sampling Cleavage Under Targets & Release Using Nuclease (CUT&RUN), in which a random population of neonatal foreskin keratinocytes were assayed by CUT&RUN for homeostatic TFs under progenitor growth and differentiation conditions. Heterozygous alleles were identified from the TF binding data and examined for allele specific binding events (ASBs). ASBs were then compared with non-coding variants linked to skin disease. Variants with potentially pathogenic effects were identified. Promoters and high TF occupancy genomic regions were found to be "buffered" against variants causing ASBs.

  Study phs003977

• University of Miami Study on Genetics of Autism and Related Disorders (AutismDisorders)

  Autism spectrum disorders (ASD) are neurodevelopmental in origin and characterized by impairments in reciprocal social interaction and communication accompanied by restricted and repetitive patterns of interest or behavior. With improved surveillance and a broadening of the diagnostic criteria, the most recent prevalence studies suggest that ASD may affect as many as 1/166 children in the US. Treatments are limited resulting in little impact on the profound morbidity. Little is known about the etiology of ASD, but there is a strong genetic component. Genetic studies over the past decade have failed to identify definitive ASD genes, but have clearly shown that the underlying genetics are more complex than anticipated with the likelihood that multiple genes are acting independently and/or interactively. With this realization the field of ASD genetics is at a critical juncture. To move forward we must embrace new and creative paradigms to successfully dissect the genetic etiology of this disease. Specifically the current study will: Extend our ascertainment to the full range of ASD. We will increase our ASD dataset by collecting 600 families who meet clinical diagnostic criteria for the three most common ASDs: autism (AUT), Asperger disorder (ASP) and Pervasive Developmental Disorder-NOS (PDD-NOS). Phenotype assessment will be expanded to include the Social Responsiveness Scale (SRS) and detailed seizure data. Ascertainment will focus on parent-child trios. Further characterize the ASD-associated variations in the Gamma-Aminobutyric Acid (GABA) receptor (GABR) subunits. We will complete our GABR subunit variant analysis, including coding, UTR, regulatory, and conserved intronic sequence, concentrating on GABRA4 and GABRB1. We will also investigate the role of variation in other GABR subunits. All AUT specific findings will be examined in the entire ASD dataset. Identify the chromosome 19p ASD gene. Multiple genome-wide screens have provided significant evidence for linkage to Chromosome 19p and we have found evidence for significant association in the linked families within an ~3 Mb region. We will genotype 768 SNPs spaced at ~4 kb to refine the candidate region and delineate specific candidate genes for further testing. We will screen the strongest associated candidate genes for additional variants and evaluate evidence for association in the entire ASD dataset (SA5). Develop and apply the Phenotypic Homogeneity Distinction (PHD) algorithm for identification of the phenotypic signature of linkage and/or association signals. The PHD algorithm identifies phenotypic covariates that discriminate a target sample subset (e.g. the positively linked families or families carrying the associated risk allele) from its complement. The resulting PHD discriminators will define a homogeneous subset from our newly-ascertained ASD dataset to use, as a confirmatory dataset and for localization within genes under study in our other aims. Test for gene-gene interactions. To fully explain the spectrum of autism risk, we will test for interactions between genetic variations associated with ASD (such as those in GABR subunit genes). We will build upon our experience using the MDR method and extend our analyses across biological pathways using the entire ASD data set.

  Study phs000436

• Mayo Clinic Adult Diffuse Glioma Illumina OncoArray SNP Data

  These data are from adult diffuse glioma subjects genotyped on the Illumina OncoArray. Data from this study were used for case control association studies and developing polygenic risk scores. Variants in D2HGDH and near FAM20C were identified that were associated with glioma subtypes (PMID: 32386320). Mutation and copy number data are included for select genes and chromosomes. IDH mutation and 1p/19q co-deletion are used in glioma diagnosis and are also prognostic markers. Data for additional prognostic genes and chromosomes are also included. RNA-seq and CHIP-seq data are available for select subjects from this cohort in GEO (GSE167806).

  Study phs003041

• Bleomycin Induced Pneumonitis WGS dataset

  This is whole genome sequencing data from a cohort of 18 patients with germ cell tumours or Hodgkin Lymphoma, who developed clinically significant bleomycin-induced pneumonitis despite low clinical risk. DNA was extracted from whole blood, and 150-base paired-end reads were generated on an Illumina NovaSeq 6000 instrument to a minimum 30x depth. Sequence reads were aligned to the GRCh38 reference with BWA MEM, and germline variants were called following GATK best practice procedures. The dataset comprises per-sample read alignment files in BAM format, and a joint-called germline variant file in VCF format.

  Dataset EGAD50000002221

• Inherited genetic predisposition to childhood acute lymphoblastic leukemia investigated using a genome wide association study.

  This series consists of summary data generated from a genome-wide association study (GWAS) investigating inherited genetic risk to childhood acute lymphoblastic leukemia (ALL). The GWAS comprised 784 cases recruited to the Medical Research Council UK ALL-2003 and ALL-97/99 trials and 7,385 controls. The data describe SNPtest association statistics from the case-control analysis.

  Study EGAS00001002809

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_cytoscan)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005584

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_oncoscan)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005586

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_agilent)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005587

• Download Metadata

  Metadata Distribution Welcome to the realm of Metadata Distribution within the EGA ecosystem! Our Metadata REST API empowers you to effortlessly retrieve metadata from the expansive landscape of EGA. By utilising this API, you gain access to publicly available insights across various EGA domains, including studies, samples, experiments, runs, analyses, policies, DACs, and datasets. Furthermore, this API facilitates cross-referencing of objects, enabling you to gather, for example, all the datasets associated with a specific DAC, seamlessly. In addition, we have added the ability to query private data using the metadata API. If you possess the necessary permissions, you can access behind-the-login private data for a specified list of datasets. Metadata Distribution Index Identifiers Dataset Mappings Website Download Metadata API - Private Identifiers At the core of EGA's organisational structure are unique accessions that serve as essential tags for our diverse objects. Here's a quick overview of the accessions and their corresponding object types: EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID For further information check our metadata schema documentation. Dataset Mappings For authorised datasets, comprehensive mappings reveal meaningful connections: Sample_file: This file presents information about the linkage between samples and files available in the dataset. Study_experiment_run_sample: This file presents information about the linkage between studies, experiments, runs, and samples within the dataset. Study_analysis_sample: This file presents information about the linkage between studies, analyses, and samples contained within the dataset. Run_sample: This file presents information about the linkage between runs and samples within the dataset. Analysis_sample: This file presents information about the linkage between analyses and samples within the dataset. An empty file indicates the absence of corresponding information. Website Download Our website serves as your gateway to downloading metadata. Simply navigate to the dataset page, and you'll find a blue Metadata button. Once authenticated, you can click this button for authorised datasets. If you lack permissions for a particular dataset, request access by clicking the 'Request Access' button. For authorised datasets, choose your preferred metadata format: CSV, TSV, or JSON. Metadata API - Private Leverage the power of programmatic metadata downloads! Start by authenticating yourself with your credentials to obtain an access token. With this token, programmatically query private information. Queries mirror the structure of the Public Metadata API. However, behind the login, you can delve into specific mapping information (as mentioned above in dataset mappings) alongside object-level exploration. Authentication An active session is required to work with the API. Each time you log in with your credentials a new session is started, which is identified by an access_token. Below an example on how to obtain one using curl: curl https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token \ -d 'client_id=metadata-api' \ -d 'username=...' \ --data-urlencode 'password=...' \ -d 'grant_type=password' All responses from the API are in JSON format. A successful response should include a new token to be used for the session: {"access_token":"eyJhbGciOiJSUzI1NiIsInR5cCIgOiA...TNw", "expires_in":300, "refresh_expires_in":1800, "refresh_token":"eyJhbGciOiJIUzI1NiIsInR5cCIgOiA...pTX10", "token_type":"Bearer", ... } Save the access_token value and include it in the API call headers. Example query usage Below you can find some example of queries available behing authentication and authorisation. Querying study-experiment-run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_experiment_run_sample \ -H 'Authorization: Bearer access_token' Querying run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/run_sample \ -H 'Authorization: Bearer access_token' Querying study-analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_analysis_sample \ -H 'Authorization: Bearer access_token' Querying analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/analysis_sample \ -H 'Authorization: Bearer access_token' Querying sample-file mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/sample_file \ -H 'Authorization: Bearer access_token' You can get a different output format by adding one of these options to the curl command: -H 'Accept: text/tsv' -H 'Accept: application/json' -H 'Accept: text/csv' For more detailed information, refer to the Metadata API Specification.

  Documentation access/download/metadata

• RNA Sequencing of AD OM cells exposed to traffic-related air pollutants

  Total RNA sequencing of olfactory mucosa (OM) cells derived from individuals diagnosed with Alzheimer's disease exposed to traffic-related ultrafine particles (UFPs) for 24-h and 72-h in submerged cultures. The UFPs used for exposures were: A0, A20 and Euro6. Exposures were compared to the corresponding blank samples.

  Study EGAS50000000448

• FACS sorting of ploidy populations in an undifferentiated soft tissue sarcoma for RRBS

  Groups of cells belonging to different ploidy populations (based on PI staining) were collected from an undifferentiated soft tissue sarcoma. The different ploidy populations underwent RRBS, after which copy number signatures for the ploidy-sorted populations and the bulk population were extracted.

  Study EGAS00001006143

• Comparison Across Multiple Types of Sleep Deprivation

  This study is designed to assess neurobehavioral performance, as well as molecular and physiological changes associated with variations in timing and quantity of sleep. Gene expression changes associated with neurobehavioral (cognitive) performance were assessed in a time-series among individuals randomly assigned to four separate sleep conditions during a 10-day inpatient study: a well-rested control, sleep restriction with nighttime sleep, sleep restriction with daytime sleep to roughly simulate shiftwork schedules, and total (acute) sleep deprivation.

  Study phs003924

• Profiling the genomic landscape and evolutionary history of polyploid giant cancer cells in undifferentiated pleomorphic sarcomas

  In this study, we characterise PGCCs in ten pleomorphic sarcomas and use topographic single-cell DNA sequencing (scDNA-seq) to investigate their genomic landscape. We selected PGCCs based on their nuclear morphology, including mononucleated or multinucleated bizarre, misshapen nuclei, and analysed them at single-cell resolution. Histopathological analysis showed that PGCCs were often randomly distributed throughout the tumour and did not appear in clusters, suggesting that they arise de novo rather than through clonal expansion. scDNA-seq revealed that PGCCs originate from the dominant tumour population and exhibit extensive copy number heterogeneity, either due to subsequent or ongoing chromosomal instability. Both clonal and subclonal chromothripsis-like events were identified in PGCCs, indicating that chromothripsis is a key driver of heterogeneity in these cells and is linked to multinucleation rather than mononuclear PGCC formation.

  Dataset EGAD50000002084

• Genes___Health_imputed_genotype_dataset

  Genes & Health is a cohort of British Bangladeshi and British Pakistani individuals. In the Feb2020 data freeze, 28,022 individuals were genotyped on the Illumina Infinium Global Screening Array v3 chip (with the additional Multi-Disease variants). Imputation was performed using the Michigan Imputation Server with the GenomeAsia pilot reference panel, which contains 1,739 genomes and 642 from them are from South Asian groups. This dataset contains imputed SNPs with imputation accuracy >0.3 and MAF >0.1%.

  Study EGAS00001005373

• Integration of genomics and metabolomics in acute myeloid leukemia

  Although targeting of cell metabolism is a promising therapeutic strategy in acute myeloid leukemia (AML), metabolic dependencies are largely unexplored. We aimed to classify AML patients based on their metabolic landscape and map connections between metabolic and genomic profiles. The intracellular metabolome distinguished three AML clusters, correlating with distinct genomic profiles: NPM1-mutated(mut), chromatin/spliceosome-mut and TP53-mut/aneuploid AML that were confirmed by biofluid analysis.

  Study EGAS00001005422

• Pre-diagnostic saliva microbiota of Finnish children with autoimmune diseases

  Pre-diagnostic saliva microbiota samples of Finnish children (aged 11/12 years). This is a case-control study, where case refers to the children who developed Type 1 DM or IBD later in life and control refers to the children who were free from these diseases. The aim of the study was to find biomarkers in saliva microbiota that may help us predict DM or IBD before the onset of these diseases.

  Study EGAS00001006949

• Clonal_selection_after_gene_therapy_in_SCD___Duplex_sequencing

  This study includes the targeted duplex sequencing data relating to this study. A custom targeted panel was used including 29 AML-associated genes, and a set of mutations from driver-containing clones that were sequenced during the WGS tree-building phase of the study. Targeted sequencing is performed on each of 6 individuals included at the study at at least 3 time points per individual: one prior to gene therapy, and two post-therapy time points.

  Study EGAS00001007253

• ESGI - Whole Genome Sequencing of NSPHS samples (2019-08-19)

  Whole genome sequencing of sampels from the NSPHS cohort. The samples are sequenced using the Illumina HiSeq X Ten system. . This dataset contains all the data available for this study on 2019-08-19.

  Dataset EGAD00001005267

• Whole transcriptome sequencing datasets for Low-grade Serous Ovarian Carcinoma

  This dataset includes whole transcriptome sequencing reads from 8 cell lines based on TruSeq stranded mRNA kit (Illumina). They are all 2*75bp reads sequenced using Illumina NextSeq500.

  Dataset EGAD00001006441

• Wilms Tumour organoid sequencing WGS (2019-09-05)

  This study investigates the genomic and transcriptomic characteristics of Wilm's tumour organoids . This dataset contains all the data available for this study on 2019-09-05.

  Dataset EGAD00001005312

• Targeted sequencing of in vitro colonies - bulks (2020-05-05)

  In this study we will perform targeted sequencing on the bulk samples of in vitro colonies. This dataset contains all the data available for this study on 2020-05-05.

  Dataset EGAD00001006118

• WES raw data for study "Molecular and functional profiling of plasmablastic lymphoma"

  1 cell line and 123 patient samples including 38 normal (22 paired normal and 16 unpaired), 85 tumor-initial, FASTQ file types, Agilent SureSelect Human All Exon V6 Kit

  Dataset EGAD00001006400

• The mutational landscape of normal human endometrial epithelium - Additional Samples

  All normal somatic cells are thought to acquire mutations but understanding of the rates, patterns, causes and consequences of somatic mutation in normal cells is limited. Uterine endometrium adopts multiple physiological states over a lifetime and is lined by a gland-forming epithelium. Whole genome sequencing of normal endometrial glands from women aged 19 to 81 years showed them to be clonal cell populations derived from recent common ancestors, with total mutation burdens that increase with age at ~29 base substitutions/year and which are many-fold lower than endometrial cancers. Normal endometrial glands frequently carry driver mutations in cancer genes. Driver mutation burdens increase with age and correlate negatively with parity. Phylogenetic trees of normal endometrial glands constructed using whole genome sequences indicated that clones with drivers often originate during the first decades and spread to colonise the endometrial epithelial lining. The results show that driver mutation landscapes differ between normal cell types, perhaps shaped by differences in normal tissue physiology, and suggest that the procession of neoplastic changes leading to endometrial cancer is initiated early in life.

  Dataset EGAD00001005214

• Geisinger Health System - MyCode, eMERGE III Exome Chip

  DNA samples were obtained from participants of the Geisinger MyCode biobank. Phenotype data to determine case or control status for abdominal aortic aneurysm or extreme obesity were derived from Geisinger electronic medical record data through an enterprise data warehouse. Samples were genotyped using the Illumina Human CoreExome-12 v1.0 Array. Genotype data were filtered using standard quality control measures.

  Study phs000957

• NanoSring of PBMC from bladder cancer and RCC patients

  PBMCs from patients were isolated using 50 mL Leucosep™ tubes (Greiner Bio-One International, Germany) and Ficoll-Paque™ PLUS (GE Healthcare, Sweden). Whole blood drawn into sodium heparin blood collection tubes were diluted 3x with phosphate-buffered saline (PBS) without calcium or magnesium (Lonza, Walkersville, MD). Diluted cell suspensions were carefully layered on Leucosep tubes and centrifuged for 15 minutes at 800 x g at room temperature (RT). Interphase containing PBMCs were harvested and washed with PBS and subsequently centrifuged for 10 minutes at 250 x g at RT before further processing.

  Study EGAS00001004229

• GATA2 Deficiency

  The aim of this study is to identify somatic mutations that contribute to the progression of GATA2 Deficiency patients from bone marrow failure to myelodysplastic syndrome (MDS) to acute myeloid leukemia (AML) or chronic myelomonocytic leukemia (CMML). We investigated somatic mutations in >100 patients by whole exome and myeloid malignancy targeted array sequencing to identify acquired mutations associated with myeloid malignancies. MDS was the most common diagnosis (~45%), followed by GATA2 Bone Marrow Immunodeficiency Disorder (G2BMID) (~35%). Approximately ten percent of our cohort were unaffected "carrier" family members with no disease manifestations. In contrast, about ten percent had progressed to a proliferative leukemia. There were no correlations with GATA2 mutation, patient age or gender and disease progression or survival. Somatic Recurrent somatic mutations were uncommon in cancer associated genes, and virtually absent in asymptomatic patients. However, mutations in the cohesin gene STAG2 and chromatin remodeling gene ASXL1 were detected in ~20% of patients. Patients with ASXL1 mutations had a lower survival. ASXL1 mutations were ~10-times more prevalent in female patients than males. Other recurrent mutations were in the DNMT3A, BCOR, and SETBP1 genes. There was a conspicuous absence of the most commonly mutated genes associated with myeloid malignancies, including TET2, RUNX, IDH1/2 and splicing factor genes. 

  Study phs002311

• Table of gene-level RNA counts from newborn screening dried blood spot samples

  Table of gene-level RNA counts from 21 newborn screening dried blood spot (DBS) samples. These DBS samples were obtained from extremely low gestional age newborns, where 10 of them were affected by a fetal inflammatory response (FIR) before birth, and 11 were unaffected. Total RNA was sequenced using an Illumina NextSeq-500 instrument. The sample preparation protocol included the depletion of rRNA and globin mRNA using the Globin Zero Gold rRNA Removal Kit from Illumina. Libraries were prepared using the NebNext Ultra TM II Directionl RNA LIbrary Prep Kit (New England Biolabs). Rows correspond to genes and columns to samples, where there is an additional column (BS13sub), corresponding to sample BS13, which was downsampled to 1/4 of its original depth.

  Dataset EGAD00010001707

• National Cancer Institute (NCI) Genome Wide Association Study (GWAS) of Lung Cancer in Never Smokers

  A genomewide study of lung cancer in never smokers Abstract and specific aims In the United States, lung cancer incidence and mortality rates have been steadily declining over the past decade, following decline in the prevalence of tobacco smoking. However, lung cancer remains the leading cause of cancer death, killing more patients than breast, colon, and prostate cancers combined. Although tobacco smoke is the predominant risk factor for development of lung cancer, some patients develop the disease without a history of tobacco smoking. About 10 - 15% of all lung cancers occur in lilfetime never smokers. This figure will increase as the proportion of never smokers increases in the population. Even at present rates, lung cancer in never smokers, if considered a separate disease, is 6th to 8th top cause of cancer death. The growing number of never smokers in the USA and other countries emphasizes the importance of understanding the epidemiology and biology underlying lung cancer in this group. Genetic polymorphisms associated with the risk of lung cancer in never smokers are expected to overlap with those associated with the risk of lung cancer in ever smokers only partially. Epidemiological, molecular and clinical data suggest that molecular mechanisms of LC may differ in smokers and non-smokers, implying that lung cancer in never smokers is a different disease compared to the lung cancer in smokers. One can expect that there should be stronger genetic component in the control lung cancer in never smokers because effects of the genetic factors in never smokers are unmasked by the lack of tobacco smoke exposure. The genetic epidemiology of lung cancer in never smokers has not been well explored, largely because of difficulties in accruing the needed sample size for association studies. We propose a multicenter (total 14 sites from the US and Europe) genomewide association study of lung cancer in never smokers with the following specific aims: Aim 1: To identify candidate SNPs influencing risk for lung cancer in never smokers using Discovery sample. In the Discovery phase we will genotype 1256 Caucasian cases and 1365 age- and gender-matched never smoker controls using the Illumina Human660W-Quad platform. In addition, we will include in the analysis 284 cases and 175 matched controls already genotyped on the 610Quad platform. In this phase we will only include the study sites that have collected blood specimens (MDACC, Mayo Clinic, Karmanos Cancer Institute, The University of Liverpool Cancer research Centre, Institute of Cancer Research in Sutton, and Lunenfeld Research Institute in Toronto, Canada). All the samples will be sent to the independent lab for genotyping, to reduce site-specific technical artifacts. The final sample will consist of 1540 cases and 1540 controls matched by study site. Aim 2: To perform the second phase (validation) analysis of significant SNPs identified in aim 1 using an independent set of cases and controls. SNPs associated with risk at the significance level of 0.01 or below in the discovery set will be included in the replication phase. The proposed threshold guarantees an adequate power to retain SNPs with the typical effect size of 1.3. We plan to carry 6000-7000 SNPs for validation. The independent replication set will include 800 cases and 800 controls, mostly from sites that collected tissue (Mayo Clinic, Karmanos Cancer Institute, UT Southwestern) or buccal specimens (UCLA), but also blood samples (Imperial College London, University of Pennsylvana, German Cancer Research Center, Heidelberg, National Research Center for Environment and Health, Neuherberg, Carmel Medical Center, Haifa). We will then perform a joint analysis to test the significance of the SNPs identified in the first stage using a stringent critical p-value of 10-7. There will be 2340 cases and 2340 controls in the joint set. Based on our experience with GWAS in smokers and assuming that genetic component in lung cancer risk in never smokers can be higher than genetic component in smokers, we expect to identify about 5-10 candidate regions associated with lung cancer risk in never smokers. Aim 3: To identify and explore pathways associated with the risk of lung cancer in never smokers. Results of the number of studies on the molecular mechanisms and drug response suggest that lung cancer in never smokers is a different disease and different pathways will be associated with lung cancer risk in non-smokers and smokers. To identify pathways and molecular functions associated with lung cancer risk in never smokers we will apply Ingenuity and DAVID bioinformatics tools. We will use at least 300 top candidate genes identified in joint and discovery analysis. The reason why we select rather large number of candidate genes for functional annotation is two-fold: 1. Both algorithms are looking for enrichment of pathways and function by most significant genes and they produce statistically robust results only when number of genes is relatively high. 2. Despite the fact that this study will be largest possible for never smokers we still are underpowered to detect SNPs with relatively small effect size. But though those SNPs will not reach genome wide level of significance they will tend to be on the top of the list. In other words genes from the gray zone (significant on individual level and non-significant for genome wide level) are expected to be enriched by true discoveries. True discoveries are likely to be associated with limited number of pathways / functions while false positives are expected to be uniformly distributed across functions and pathways. Therefore significant clustering of the gene to a given function will suggest that that those genes are true discoveries. This is the first GWAS aiming at identifying the genetic control of susceptibility to lung cancer in Caucasian never smokers. We will combine the available resources from the multiple sites to achieve the sample size sufficient for this study. The study will identify genetic architecture of the predisposition to the lung cancer in never smokers.

  Study phs000634

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Tumor infiltration by T cells is paramount for effective anti-cancer immune responses. We hypothesized that the T cell receptor (TCR) repertoire of tumor infiltrating T lymphocytes (TIL/Tc) could determine disease course at different stages in cancer progression. We show that the diversity of the TIL/Tc TCR at baseline is prognostic in various cancers, whereas in metastatic melanoma TIL/Tc TCR clonality at baseline is predictive for activity and efficacy of PD1 blockade immunotherapy.

  Study EGAS00001005201

• Mapping Cells and Interactions in the Thymus Across Development and Aging (2025-07-28)

  Single cell RNA sequencing on thymic cells from children with syndromic diseases such as Trisomy 21 and inflammatory/autoimmune diseases such as myasthenia gravis. Our group has previously performed atlasing of the healthy human thymus using single cell transcriptomics and obtained an unprecedented understanding of human thymus throughout development. In this study, we intend to survey diseased human thymus and compare this to healthy to obtain a better understanding of thymic dysfunction in human diseases. The diseases we will survey include congenital conditions such as Down's syndrome, CHARGE syndrome, DiGeorge syndrome as well as acquired diseases such as myasthenia gravis and thymic hyperplasia. We intend to perform genetic and genomic study on the samples, including expression analysis. This will not only help us to understand the cells and molecular pathways affected in dysfunctional thymus; but may also lead to generalisable understandings in human genetic diseases and inflammatory/autoimmune diseases. 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 2025-07-28.

  Dataset EGAD00001015660

• Primary Prostate Tumor Tissue DNA Methylation Profiles

  The study cohort includes 525 Caucasian and African American prostate cancer (PCa) patients who underwent radical prostatectomy (RP) as primary therapy for clinically localized adenocarcinoma of the prostate. These patients were previously enrolled in one of two population-based studies: 1) men 40-64 years of age, diagnosed between January 1993 and December 1996; and, 2) men 35-74 years of age, diagnosed between January 2002 and December 2005. Gleason grade and sum, diagnostic PSA, and pathological tumor stage were obtained from the SEER cancer registry. Formalin-fixed paraffin-embedded prostate tumor tissue blocks were obtained from RP specimens and used to make hematoxalin and eosin stained slides, which were reviewed by pathologists to confirm the presence/location of adenocarcinoma. For each patient two 1-mm tumor tissue cores from the dominant lesion that were enriched with >=75% tumor cells were taken for DNA purification. The RecoverAll Total Nucleic Acid Isolation Kit (Ambion/Applied Biosciences, Austin, TX) was used to extract DNA, which was then quantified (PicoGreen), aliquoted onto 96-well plates and shipped to Illumina for DNA methylation profiling using the Infinium® HumanMethylation450 BeadChip.

  Study phs001921

• Privacy Notice for Helpdesk service

  Privacy Notice for EGA Helpdesk service This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org , or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from users of the service: Name Email address Job title Date and time when the support request was sent We will use your personal data for the following purposes: To provide uninterrupted user access to the service To better understand the needs of the users and guide future improvements of the service To create anonymous usage statistics 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? There are no personal data transfers to third countries or international organizations. 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-helpdesk

• Genetic Etiology of Heterotaxy

  To understand the genetic etiology of heterotaxy, patients with heterotaxy were consented and recruited, with blood drawn for DNA extraction and exome sequencing. Using the exome sequencing dataset obtained, rare coding sequence variants were identified.

  Study phs001691

• WES of oral-mucosa-derived organoids

  Tumor and matching normal tissues were collected from 8 patients and organoids were derived from each tissue. Whole exome libraries were prepared for tumor tissue, normal tissue, tumor organoids and normal organoids, and paired-end sequencing was performed using Illumina Novaseq 6000 system. Only tumor and matching normal tissues were sequenced for the patients without available organoids.

  Dataset EGAD00001005063

• ATAC-Seq of inflamed and non-inflamed biopsies

  Inflamed and non-inflamed biopsies were digested for 45 minutes at 37ºC with collagenase from Clostridium histolyticum (Sigma). Suspension cells were then stained with an antibody cocktail to sort live CD8-CD4+ T cells. After isolating crude nuclei of two thousand live CD4+ T cells, they were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry.

  Study EGAS00001007344

• Gene Expression and Regulatory Networks in Human Leukocytes - Immunological Variation Consortium

  Profiling of gene expression with microarrays holds great potential for human health, for illuminating disease pathways or providing biomarkers to monitor disease or its resolution. Using high-throughput approaches for genotyping, immunophenotyping and gene expression analysis, the project will examine the basis for the control of gene expression in human immune cells, and how it is influenced by natural genetic variation or aging. In practice, the project will combine several cross-informative approaches: 1) Building on the established sample/data pipelines and robust protocols of the Immunological Genome (ImmGen) project, and on established cohorts of ethnically diverse healthy volunteers at hand, microarray techniques will be used to generate whole-genome expression profiles from purified naive CD4+ lymphocytes and monocytes from 600 healthy volunteers. A dense genetic map will be established for all donors. The results will elucidate how variation in the human genome affects the expression of immune genes, of key importance in understanding gene variants that bring susceptibility to immune or inflammatory disease. Computational analysis of these rich data will allow the reconstruction of regulatory connections between genes, helping to establish general modules and those specific of a given immune cell type. These data will be complemented by an orthogonal data group, generated from a restricted subset of 10 individuals, in which we will profile a larger set of 28 carefully delineated cell populations that exist in human blood. This work will also benefit from powerful interspecies comparison with similar experiments being performed in mice by ImmGen. 2) In addition, RNA from the same set of 28 defined cell populations will be probed with microarrays that explore other aspects of the transcriptome: i) microRNAs and other non-coding RNAs; ii) exon or splice junction arrays that will establish a map of differential splicing in human blood leukocyte. 3) The composition and reactivity of blood cells from the same donors will be established at the time of sample collection using high-throughput flow cytometry, correlating immune phenotypes with gene expression and genetic variation. 4) Genetic variability conditions the baseline levels of gene expression, but also the responsiveness to activating challenges. With samples from the same donors, NanoString technology for transcript counting will be used to analyze the transcriptional response of defined gene sets, representing response signatures of T or dendritic cells, for a fine-grained dissection of responses to different triggers (different bacterial ligands for dendritic cells, different cytokine environment for T cells). In keeping with the resource aspect of this project, all data and interpretations will be made publicly available rapidly upon curation, allowing public querying and browsing of the data, by using and evolving the existing web architectures of the ImmGen project, of the Broad Institute, and of international repositories. RELEVANCE: Exploration with DNA chips of the genome's expression microarrays holds great potential for human health, to better understand disease and to serve as diagnostic tools. Using a combination of high-throughput genomic techniques and computational biology, we will perform a broad exploration of gene expression in human blood cells across groups of African-American, Asian and European ancestry, asking how these profiles are affected by genetic variation or by age. These results will provide an invaluable reference benchmark for the interpretation of genetic and immunological studies. Additionally, over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, in a second study we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution. 15% of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (ATAC-QTLs). ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression, and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression. In another study we analyzed RNA-seq profiles from primary CD4+ T cells of two healthy donors at six time points from 0 to 72 hours after stimulation with bead-bound antibodies against CD3 and CD28.

  Study phs000815

• Whole-exome sequencing and microRNA profiling predicted relapse risk of stage I lung adenocarcinomas for the study and all the datasets.

  This dataset contains PAIR files and processed somatic copy number alteration value for array CGH of stage I lung adenocarcinomas from Asian patients. In total, there are 111 patients and 222 samples, including 111 tumor samples and 111 adjacent normal samples.

  Dataset EGAD00010001902

• CONSERTING: integrating copy number analysis with structural variation detection

  We developed Copy Number Segmentation by Regression Tree in Next Generation Sequencing (CONSERTING), a novel algorithm for detecting somatic copy number alteration (CNA) using whole-genome sequencing (WGS) data. CONSERTING performs iterative analysis of segmentation by read depth change and localized structural variation detection to achieve high accuracy and sensitivity. Analysis of 43 pediatric and adult cancer genomes revealed novel oncogenic CNAs, complex re-arrangements and subclonal CNAs missed by alternative approaches. This study contains all data for "CONSERTING: an accurate method for detecting somatic DNA copy number alterations in whole genome sequencing data", which was previously split between EGAS00001001202 and EGAS00001001050.

  Study EGAS00001001202

• 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

• Single-cell RNA-seq of immune cells from human tumor fragments after 48 hour culture ex vivo (Kaptein et al., 2024)

  Single-cell RNA-seq profiling of immune cells from human ovarian carcinoma, renal carcinoma and melanoma samples after 48h of ex vivo culture using the patient-derived tumor fragment platform (5 samples total). Samples were cultured in various conditions, including: untreated, CD8-IL2v-treated, CD8-IL2v + LCKi -treated, aPD1-treated, CD8-IL2v + aPD1 -treated, Untargeted IL2-treated, aCD3-treated and aCD3 + CD8-IL2-treated . FASTQ files contain gene expression data, feature barcode antibody capture or TCR data on immune cells from all conditions combined per patient.

  Dataset EGAD50000000377

• Aligned reads from specific genomic locations derived from Illumina HiSeqX and HiSeq2000 whole genome sequence data

  This dataset includes bam files from 3,001 samples. These bam files include all read pairs where at least one of the reads aligns within 1kb of the C9orf72 repeat expansion. Additionally, these bam files also contain reads that are aligned to any of 29 pre-determined off target locations where the aligners are known to mis-align reads associated with this repeat expansion. These samples were sequenced using a combination of 2x100bp reads on an Illumina HiSeq2000 and 2x150bp reads on an Illumina HiSeqX sequencer and aligned using the Isaac aligner.

  Dataset EGAD00001003513

• TRACERx NSCLC, multiregion sequencing of the first 100 tumors

  BACKGROUND TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). METHODS Multiregion high-depth whole-exome sequencing (M-seq) was performed on 100 early stage NSCLC tumors resected prior to systemic therapy. A total of 327 tumor regions were sequenced and analyzed to define evolutionary histories, obtain a census of clonal and subclonal events, and assess the relationship between ITH and recurrence-free survival (RFS). RESULTS Widespread ITH was observed for both somatic copy number alterations (median 48% [0.03-88%]) and mutations (median 30% [0.5-93%]). Driver mutations in EGFR, MET, BRAF and TP53 were almost always clonal. However, heterogeneous driver alterations occurring later in evolution were found in over 75% of tumors and were common in PIK3CA, NF1 and genes involved in chromatin modification and DNA response and repair. Genome doubling and ongoing dynamic chromosomal instability (CIN), illustrated by mirrored subclonal allelic imbalance, were identified as causes of ITH resulting in parallel evolution of driver copy number events, including amplifications of CDK4, FOXA1, and BCL11A. Elevated copy number heterogeneity was associated with shorter RFS (HR=4.9, P=0.00044), which remained significant in a multivariate analysis. CONCLUSIONS ITH mediated through CIN, rather than point mutational heterogeneity, was associated with increased risk of relapse, supporting its value as a prognostic predictor, and the need to target this high-risk phenotype.

  Dataset EGAD00001003206

• WGBS analysis corresponding to representative cases of iBCP-ALL patients

  In this study, we performed whole genome bisulfite sequencing (WGBS) to characterize the methylome of representative iBCP-ALL cases from the Interfant study discovery cohort, including 2 pools of B-cell progenitors from healthy donors, 2 MLL-AF4+, 2 MLL-AF9+ and 2 non-MLLs from iBCP-ALL patients.

  Study EGAS00001003650

• Characterization of the oral and gut microbiome of melanoma patients before initiation of ant-PD-1 therapy, and confirmation of the phenotype in germ-free mice

  The oral and gut microbiomes of melanoma patients were characterized before the initiation of ant-PD1 immunotherapy, and compared to treatment response. Validation studies were performed in germ-free mice using stool from patients who responded/did not respond to ant-PD1 immunotherapy. All baseline oral(n=86) and gut (n=43) microbiome samples were subject to 16S sequencing - V4 region ( merged fastq files have been made available through this portal). Whole genome shotgun sequencing (WGS) was performed on a subset of fecal samples (n=25)- these files are also available( paired end reads). Also available are 16S sequencing results of stool samples from donors (n=2) used in fecal microbiota transplant and murine samples (n=12) from germ-free mice transplanted with stool from responder/non-responder patients. The fastq files associated with this dataset are stored at ENA under the following links: Fecal 16S – PRJEB22894 https://www.ebi.ac.uk/ena/browser/view/PRJEB22894 Oral 16S – PRJEB22874 https://www.ebi.ac.uk/ena/browser/view/PRJEB22874 Murine 16S – PRJEB22895 https://www.ebi.ac.uk/ena/browser/view/PRJEB22895 Fecal WGS – PRJEB22893 https://www.ebi.ac.uk/ena/browser/view/PRJEB22893

  Dataset EGAD00001003943