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• Malawi_GWAS-2.5M_b37

  Genome-wide study of resistance to severe malaria in eleven worldwide populations:Malawi

  Dataset EGAD00010000903

• Gambia_GWAS-2.5M_b37

  Genome-wide study of resistance to severe malaria in eleven worldwide populations:Gambia

  Dataset EGAD00010000902

• postQC Genotypes

  postQC genotype data from the Affymetrix AxiomTM HGCoV2 1 array in plink binary format. QC was carried out using PLINK v1.9

  Dataset EGAD00010002436

• GLASS-NL Transcriptomic data

  This dataset contains RNA-sequencing data of 169 IDH-mutant astrocytoma samples included in the GLASS-NL cohort

  Dataset EGAD50000000408

• ECL_onc_biology_DAC

  This DAC can be used by biology members of the oncology-related domain and function of ECL when depositing data. (DAA was reviewed by the legal department in March 2024.)

  Dac EGAC50000000275

• University of Hull

  Tumour Regulatory Molecules in Early Pancreatic Cancer Detection (TEM-PAC) and EARLY DIAgnosis of PAncreatic Cancer by combined proteomics and genomics testing of pancreatic cyst fluid (DIA-PAC) studies.

  Dac EGAC50000000402

• Rucaparib in patients presenting a metastatic breast cancer with Homologous Recombination Deficiency, without germline BRCA1/2 mutation, pronostic value of high LOH genomic score and predictive value of HRDetect (WGS)

  Study EGAS00001004756

• WES

  Whole Exome Sequencing data from Lauss et al Nat Comm 2024. Molecular patterns of resistance to immune checkpoint blockade in melanoma.

  Dataset EGAD50000000380

• RNAseq sample

  RNAseq sample used in study titled "Immune-awakening revealed by peripheral T cell dynamics after one cycle of immunotherapy".

  Dataset EGAD00001005747

• Cord blood sequencing data

  SmMIP libraries using cord blood DNA were generated in replicates and were sequenced on the NovaSeq SP platform (Illumina)

  Dataset EGAD00001007789

• CTCF-ChIP-Seq of cohesin-mutated and wildtype adult AMLs

  ChIP-Seq targeting CTCF in cohesin-mutated (STAG2 or RAD21 mutations) and wildtype adult AMLs (CTRL-AMLs).

  Dataset EGAD00001011200

• Swedish schizophrenia control individuals

  Genomic DNA from Swedish control individuals was pooled. Then the genomic sequence of brain expressed miRNA genes was determined in the pools.

  Dataset EGAD00001001850

• Pancreatic organoid - case samples

  This dataset contains 31 pancreatic organoid samples used in the 'organoid data of pancreatic cancers ' study

  Dataset EGAD00001004528

• Belgian epilepsy control individuals

  Genomic DNA from Belgian control individuals was pooled. Then the genomic sequence of brain expressed miRNA genes was determined in the pools.

  Dataset EGAD00001001852

• BAP1 sequence of uveal melanoma and mesothelioma samples

  Detection of BAP1 mutations in DNA from uveal melanoma and mesothelioma samples.

  Dataset EGAD00001002229

• Cryptic translocations in double hit signature DLBCL genomes

  18 DLBCL genomes

  Dataset EGAD00001006087

• NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (Lung Health Study of Chronic Obstructive Pulmonary Disease)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The Lung Health Study I was a randomized multicenter clinical trial with 5887 participants carried out from October 1986 to April 1994, designed to test the effectiveness of smoking cessation and bronchodilator administration in smokers aged 35 to 60 with mild lung function impairment. Participants were randomly assigned to one of three groups: usual care, who received no intervention smoking intervention with the inhaled bronchodilator ipratroprium bromide smoking intervention with an inhaled placebo The effect of intervention was evaluated by the rate of decline of forced expiratory volume in one second (FEV1).

  Study phs000291

• Genetics of Disorders Affecting Tooth Structure, Number, Morphology and Eruption

  The long-term objective of this research project is to discover the complete spectrum of genes that contribute to the etiologies of genetic disorders of dentition. Inherited tooth defects can be isolated (the only symptom) or syndromic (having additional symptoms), and can be caused by mutations in many different genes. Clinically, it can be difficult to distinguish among the diverse forms. Making an accurate diagnosis would be greatly improved if reliable tests could identify the specific genetic defect that causes the disease in each case. Current technology can identify the numerous sequence variations throughout a patient's exome, but the disease-causing variation among them cannot be identified unless it is already on the list of genes that potentially cause the disease. A diagnosis based upon the genetic defect that causes the disorder distinguishes between isolated and syndromic tooth defects. A precise diagnosis permits formulation of a more accurate prognosis, which informs treatment decisions. The benefits of accomplishing our aims are to 1) enable genetic testing to achieve a precise and accurate diagnosis, and thereby optimize treatment, and 2) improve our understanding of normal and pathological tooth formation, leading to future improvements in treatment and eventually cures. Our short-term objectives are to 1) recruit kindreds with inherited disorders affecting their dentition, characterize their dental phenotype (and non-dental phenotypes when applicable) and the distribution of the disorder throughout the family, and 2) determine the genetic etiology of their disorders.

  Study phs001491

• Enrichment of Lung Microbiome with Supraglottic Taxa which is Associated with Increased Pulmonary Inflammation

  Background: The lung microbiome of healthy individuals frequently harbors oral organisms. Despite evidence that micro-aspiration is commonly associated with smoking-related lung diseases, the effects of lung microbiome enrichment with upper airway taxa on inflammation has not been studied. We hypothesize that the presence of oral microorganisms in the lung microbiome is associated with enhanced pulmonary inflammation. Methods: We sampled bronchoalveolar lavage (BAL) from the lower airways of 29 asymptomatic subjects (9 never-smokers, 14 former-smokers and 6 current-smokers). We quantified, amplified, and sequenced 16S rRNA genes from BAL samples by qPCR and 454 sequencing. Pulmonary inflammation was assessed by exhaled nitric oxide (eNO), BAL lymphocytes and neutrophils. Results: BAL had lower total 16S than supraglottic samples and higher than saline background. Bacterial communities in the lower airway clustered in two distinct groups that we designated as pneumotypes. The rRNA gene concentration and microbial community of the first pneumotype was similar to that of the saline background. The second pneumotype had higher rRNA gene concentration and higher relative abundance of supraglottic-characteristic taxa (SCT), such as Veillonella and Prevotella, and we called it pneumotypeSCT. Smoking had no effect on pneumotype allocation, alpha or beta diversity. PneumotypeSCT was associated with higher BAL lymphocyte-count (p = 0.007), BAL neutrophil-count (p = 0.034) and eNO (p = 0.022). Conclusion: A pneumotype with high relative abundance of supraglottic-characteristic taxa is associated with enhanced subclinical lung inflammation.

  Study phs000633

• Mapping the Human Connectome - Structure, Function, and Heritability: Healthy Young Adults (Age 22-35 Years) Including Twins and their Non-Twin Siblings

  The Human Connectome Project (HCP) has acquired vast amounts of data about the pattern of long-distance connections (wiring) in the brains of large numbers of healthy participants aged 22-35 using cutting-edge MRI and MEG neuroimaging, and extensive behavioral testing. Types of MR data collected included diffusion MRI (dMRI), resting-state functional MRI (r-fMRI), and structural MRI at both 3T and 7T, and task-evoked functional MRI (t-fMRI) at 3T. Following an extensive period of development and optimization of data acquisition and analysis methods, at Washington University in St. Louis we studied 1,206 participants comprising twins and their non-twin siblings. A subset of 184 twins was scanned again at the University of Minnesota using a 7T scanner. A different subset of 95 twins was studied at St. Louis University using combined resting state and/or task-activated MEG. We were able to collect genetic data on 1142 of our 1206 participants, including 149 pairs of genetically-confirmed monozygotic twins (298 participants) and 94 pairs of genetically-confirmed dizygotic twins (188 participants). Overall, there are 457 different families in the study, as determined by genetic analysis. Our rich set of imaging, behavioral and genetic data - available through the Human Connectome database - will enable many types of analysis of brain circuitry, its relationship to behavior, and the contributions of genetic and environmental factors to brain circuits.

  Study phs001364

• Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

  To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

  Dataset EGAD00001007872

• GATCI_Oncoscan_Data

  This dataset contains files generated from Affymetrix Oncoscan Arrays. For each sample there are two paired cel files containing the raw data from AT and GT channels. Raw data has been transfromed to OSCHP signal files also within this dataset.

  Dataset EGAD00010001579

• Oncoscan SNP arrays for study "Molecular and functional profiling of plasmablastic lymphoma"

  1 cell line and 82 Oncoscan SNP tumor initial samples, zipped Affymetrix CEL file types, Oncoscan CNV FFPE Assay Kit, Thermo Fisher Scientific GeneChipTM Scanner 3000 7G

  Dataset EGAD00010001978

• H3Africa ACEGID Omni 2.5M and 5M Genotype

  SNP Genotyping for Lassa Fever cases and population controls from Nigeria and Sierra Leone using Illumina Omni 2.5M and 5M

  Dataset EGAD00010002509

• Tissue Site

  Tissue site for RNAsequencing data. Tissue site is associated with the clinical biomarker data and be linked to the biomarker data using the SAMPLE and PAT identifiers.

  Dataset EGAD50000000931