23040 results for "ega"

in 43.20 milliseconds.

• Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia [WGS]

  This dataset contains low‑pass whole‑genome sequencing data from 203 individuals representing four Indonesian populations: the general urban population of Denpasar and the traditional community of Pedawa Village in Bali, as well as traditional community of Yoboi Village (in Sentani lake) and Sereh Village (individuals from highland Papua residing near Sentani lake) in Papua. Sequencing was performed by Gencove using their low‑coverage whole‑genome platform. The dataset was produced as part of the Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia, a study aimed at characterizing how genetic background and environmental context shape immune cell states across diverse Indonesian communities.

  Dataset EGAD50000002384

• Targeted and exome sequencing data from 24 prostate cancer patients with somatic hypermutation

  This dataset contains all available targeted and exome sequencing paired fastq files from our study, "Identification of hypermutation and defective mismatch repair in ctDNA from metastatic prostate cancer". Patient identifiers are denoted by the first three characters of the sample aliases (e.g. "P01"), and additional information is appended to reflect the panel used (targeted 73 gene panel: "PC", or whole-exome panel: "WXS"), and whether the sample represents cell-free DNA ("cfdna") or paired white-blood cell control ("wbc"). Several patients have multiple serial collections available, and these are denoted by the characters "C1, C2, C3," etc. All samples were sequenced using Illumina technology.

  Dataset EGAD00001005474

• scRNAseq of aplastic anemia and healthy immune cells co-cultured with autologous HSPCs

  This dataset contains 8 batches of bone marrow or peripheral blood cells of patients with aplastic anemia and bone marrow cells of healthy controls. The samples from different experimental conditions have been multiplexed with Totalseq-C antibodies (feature barcoding). To demultiplex the samples, see instructions in 10.5281/zenodo.2590196 and https://github.com/janihuuh/aa_manu. Each sample is analysed with Chromium V(D)J and 5' Gene Expression Platform v2 (10X Genomics). The raw data includes fastq files for Gene expression, feature barcodes and V(D)J Expression. The processed data have been deposited in the ArrayExpress database at EMBL-EBI (www.ebi.ac.uk/arrayexpress).

  Dataset EGAD00001012120

• 76 cancer and normal whole genomes from eleven SI-NET patients

  This dataset comprises of 76 cancer and normal whole genomes obtained from 11 SI-NET patients, in the form of two fastq files (forward and reverse reads) for each genome containing sequences generated by Illumina NovaSeq 6000 system.

  Dataset EGAD00001006161

• Oxford Nanopore targeted RNA-based amplicon data of 12 classical HLA genes

  The dataset consists of Oxford Nanopore targeted RNA-based amplicon data of 12 classical HLA genes (HLA-A, -B, -C, -DRA, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, -DQB1, -DPA1, and DPB1) of 50 healthy individuals. The 12 classical genes were sequenced in two separate gene pools on R9.4 flowcells using MinION sequencer. Per individual, gene pool 1 contains HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, and -DPB1 and gene pool 2 HLA-DRA, -DQA1, -DQB1, and -DPA1. The dataset includes 100 fastq files of Oxford Nanopore 2D reads (50 for gene pool 1 and 50 for gene pool 2).

  Dataset EGAD00001006814

• Dichotomous regulation of lysosomes by MYC and TFEB controls hematopoietic stem cell fate

  We show that lysosomes are antagonistically controlled by TFEB and MYC to balance catabolic and anabolic processes required for activating LT-HSC and guiding their lineage fate. TFEB-mediated induction of the endolysosomal pathway for membrane receptor degradation limits LT-HSC metabolic and mitogenic activation; this promotes quiescence and self-renewal and governs erythroid-myeloid commitment. By contrast, MYC engages biosynthetic processes while repressing lysosomal catabolism to drive LT-HSC activation. Collectively, our study identifies lysosomes as a central regulatory hub for proper and coordinated stem cell fate determination.

  Dataset EGAD00001006884

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38233 (WG) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006930

• A108768B

  Whole genome sequencing for single cells for library A108768B 1126 cells; filetype=bam

  Dataset EGAD00001007089

• Organoid Derivation Project - GRCh38 - WGS (2023-06-22)

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients. . This dataset contains all the data available for this study on 2023-06-22.

  Dataset EGAD00001011093

• Type 1 Diabetes Genetics Consortium (T1DGC): Genome-Wide Association Study in Type 1 Diabetes, 2008

  Cases with Type 1 Diabetes (T1D) in the UK, were part of the Wellcome Trust Case Control Consortium (WTCCC) - http://www.wtccc.org.uk - that first reported in 2007: Wellcome Trust Case Control Consortium (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447, 661-678. [PubMed: 17554300] In this genome-wide association study (GWAS), funded by the NIH and JDRF, and sponsored by the Type 1 Diabetes Genetics Consortium (T1DGC), we were able to extend the case and control groups used in the WTCCC, with the intention of performing a well-powered meta-analysis. The study is written up as: Barrett, J.C., Clayton, D.G., Concannon, P., Akolkar, B., Cooper, J.D., Erlich, H.A., Julier, C., Morahan, G., Nerup, J., Nierras, C., Plagnol, V., Pociot, F., Schuilenburg, H., Smyth, D.J., Stevens, H., Todd, J.A., Walker, N.M., Rich, S.S. and The Type 1 Diabetes Genetics Consortium Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nature Genetics, PMID: 19430480. Resources - data: * Case data from this study is deposited here (i.e. in dbGaP) * Control data from this experiment - with subjects from the 1958 British Birth Cohort - is deposited with the European Genotype Archive (EGA): http://www.ebi.ac.uk/ega/ from where the WTCCC data is also available. * A complete description of how to request all components of the meta-analysis is available at: http://www.t1dbase.org/page/PosterView/display/poster_id/324 * Additional genetic data on the same case subjects, including some HLA types, are available from the Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory (JDRF/WT-DIL): http://www-gene.cimr.cam.ac.uk/todd/ Resources - samples: Case and control DNA samples are also available: * Case DNA samples are available from the JDRF/WT-DIL, as above, and will be available from the NIDDK Genetics Repository at Rutgers: https://www.niddkrepository.org * Control DNA samples are available from the 1958 British Birth Cohort (aka National Child Development Study): http://www.cls.ioe.ac.uk/studies.asp?section=000100020003 Use restrictions: There are access limitations to both data and samples, in order to keep their use in line with subjects' consent.

  Study phs000180