22938 results for "ega"

in 27.64 milliseconds.

• : Centromeric cohesion failure invokes a conserved choreography of chromosomal mis-segregations in pancreatic neuroendocrine tumours

  Study EGAS00001004239

• Multiregion Whole-Exome Sequencing Uncovers the Genetic Evolution and Mutational Heterogeneity of Early-Stage Metastatic Melanoma.

  Study EGAS00001004320

• Candidate Gene Case Control Study of Human African Trypanosomiasis in the Democratic Republic of Congo

  Study EGAS00001004365

• Swarm Learning to identify COVID-19, tuberculosis and leukemia patients based on blood transcriptomes

  Study EGAS00001004502

• Evolutionary trajectories and clonal migration underlying tumor progression and lymph node metastasis in resectable lung cancer

  Study EGAS00001005242

• Single-cell genome-wide concurrent haplotyping and copy-number profiling through genotyping-by-sequencing

  Study EGAS00001005401

• SMARCA4/2 loss inhibits chemotherapy-induced apoptosis by restricting IP3R3-mediated Ca2+ flux to mitochondria

  Study EGAS00001005448

• IN UTERO ORIGIN OF MYELOFIBROSIS PRESENTING IN ADULT MONOZYGOTIC TWINS AFTER A PROLONGED DISEASE LATENCY

  Study EGAS00001005744

• S3 Swedish schizophrenia case-control study

  Study EGAS00001006772

• A capture-based next-generation sequencing panel for the molecular characterization of chronic lymphocytic leukemia

  Study EGAS00001006975

• Baseline RNAseq analysis of POETIC Good/Poor Responders to aromatase inhibitors based on change in Ki67

  Study EGAS00001007302

• The genomic echoes of the last Green Sahara on the Fulani and Sahelian people

  Study EGAS00001007499

• Neoantigen Peptides derived from V(D)J-recombined Immunoglobulins Drive Outgrowth of Cytolytic CD8+ T-cells

  Study EGAS00001008229

• Karolinska Institutet - Susanne Schlisio Lab

  DAC for Susanne Schlisio Lab, Department of Oncology-Pathology, Karolinska Institutet, Sweden

  Dac EGAC50000000603

• IRCC

  DACs of Translational Cancer Medicine laboratory of Candiolo IRCC institute

  Dac EGAC50000000068

• Institute of Pathology at the University Hospital of Lausanne CHUV

  Prof Laurence de Leval

  Dac EGAC50000000314

• Transposable elements are co-opted as oncogenic regulatory elements by lineage-specific transcription factors in prostate cancer

  Study EGAS00001007188

• Transcriptome analysis of leiomyosarcoma

  We performed transcriptome analysis of leiomyosarcoma

  Study EGAS50000000594

• Transcriptomic profiling of prostate cancer metastasis xenograft models reveals conservation of bone microenvironment signatures

  Study EGAS00001004770

• BIOCLOCK Study Methylation Data

  Whole blood methylation data measured using Illumina MethylationEPIC v2.0 array

  Dataset EGAD00010002801

• SNParray_BadBRCA

  Tumor and matched normal DNA profiling by SNP array

  Dataset EGAD00010002734

• Epigenetic reprogramming shapes monocytes and heterologous T cell derived cytokine responses in BCG vaccination

  Study EGAS00001007498

• Homologous recombination DNA repair deficiency and activity of PARP inhibition in primary triple negative breast cancer

  Study EGAS00001004190

• Next Generation Sequencing Characterization of Hematopoietic Stem and Progenitors Cells in Human Systemic Lupus Eryhtematosus

  Study EGAS00001003679

• Altered neutrophil and granulopoiesis biology underlie a poor outcome sepsis endotype

  Study EGAS00001006283

• Multi-modal analysis of pediatric pilocytic astrocytomas reveals tumor location-associated cellular and transcriptional heterogeneity

  Study EGAS00001008187

• Anaplastic_Meningioma_V3__cancer_gene_panel

  Investigation into causal genes underlying anaplastic meningioma

  Study EGAS00001001155

• ATRT ATACSeq

  ATRT ATACSeq

  Dataset EGAD00001004847

• PAGE2 Dataset Nov 2017 (Ref: PAGE2 GIM 2018)

  PAGE2 Dataset Nov 2017 (Ref: PAGE2 GIM 2018)

  Dataset EGAD00001004843

• snv calls

  single nucleotide variant calls from somatic sniper, vcf format

  Dataset EGAD00001003752

• JMML targeted sequencing of candidate genes

  JMML targeted sequencing of candidate genes

  Dataset EGAD00001001451

• WGS data from Yemen

  High-coverage sequencing data from 47 Yemenis samples

  Dataset EGAD00001003097

• Cell line exome sequencing

  Cell line exome sequencing

  Dataset EGAD00001003550

• PAGE2 Dataset Nov 2017 (Ref: PAGE2 GIM 2018)

  PAGE2 Dataset Nov 2017 (Ref: PAGE2 GIM 2018)

  Dataset EGAD00001004844

• Multisample2 WES

  Whole Exome Sequencing Data from paediatric solid tumors

  Dataset EGAD00001004014

• HIPO-P002 Whole genome

  WGS from EGAS00001001857

  Dataset EGAD00001002528

• WES of TGA

  Whole exome sequencing data for 381 TGA probands

  Dataset EGAD00001005809

• Schwannomatosis lcWGS data

  Low-coverage whole genome sequencing of sporadic schwannomatosis patients

  Dataset EGAD00001000964

• DATA FILES FOR SJCPC-WGS

  DATA FILES FOR SJCPC-WGS

  Dataset EGAD00001001065

• WGS minibam files for SJLIFE

  WGS minibam files for SJLIFE

  Dataset EGAD00001003396

• ATRT whole exome sequencing

  ATRT whole exome sequencing

  Dataset EGAD00001004576

• Orolova hIPSC data access policy

  DAC associated with the hiPSC cell lines generated by the Orlova lab.

  Dac EGAC50000000744

• KUI7051

  Nanopore pericentromere normal methylation

  Dataset EGAD00001009885

• Bulk RNAseq of mCRC organoids

  Transcriptomic profiles of 6 mCRC organoids

  Study EGAS00001006727

• Second hit rare genetic variants in families with seemingly GBA gene associated Parkinson’s disease

  Study EGAS00001004777

• RNA-seq SE

  Transcriptomics of single-end RNA-seq data

  Study EGAS00001006521

• RNA-seq PE

  Transcriptomics of paired-end RNA-seq data

  Study EGAS00001006522

• Transcriptome

  16 CRC patients transcriptome data

  Dataset EGAD00001009091

• pacbio dataset 3

  This dataset consists of 1 sample

  Dataset EGAD00001008747

• Genomic Sequencing of Triple Negative Breast Cancer - CUTseq data

  CUTseq data for study EGAS00001008261

  Dataset EGAD00001015684

• Transcriptome

  Transcriptome from EGAS00001001846

  Dataset EGAD00001002163

• PAGE Dataset Apr 2018 (Ref: PAGE Lancet 2019)

  PAGE Dataset Apr 2018 (Ref: PAGE Lancet 2019)

  Dataset EGAD00001004839

• PAGE Dataset Apr 2018 (Ref: PAGE Lancet 2019)

  PAGE Dataset Apr 2018 (Ref: PAGE Lancet 2019)

  Dataset EGAD00001004840

• PAGE Dataset Apr 2018 (Ref: PAGE Lancet 2019)

  PAGE Dataset Apr 2018 (Ref: PAGE Lancet 2019)

  Dataset EGAD00001004841

• PAGE2 Dataset Nov 2017 (Ref: PAGE2 GIM 2018)

  PAGE2 Dataset Nov 2017 (Ref: PAGE2 GIM 2018)

  Dataset EGAD00001004842

• Oncolytic virotherapy mediated anti-tumor response in primary cutaneous B-cell lymphoma: a single-cell perspective

  Study EGAS00001004904

• Data Use Ontology (DUO) at EGA

  For those of you that follow the updates of GA4GH you will have seen the unanimous approval of the steering committee for DUO to be included in its suite of technical standards for the sharing of genomic and health related data. DUO has three main features: Each term has been generated by the community and includes a human readable definition that can be expanded where necessary. It is a machine-readable file that encodes how that data can be used and how a researcher intends to use the data. Can be implemented alongside an advanced search algorithm which would allow authenticated users to query and gain access to datasets pertaining to their research. e.g., an industry researcher working on cancer could potentially be matched to any dataset that is allowed for commercial use and for cancer research and offered the opportunity to fetch them automatically. So, what does this mean for EGA? EGA as a driver project has adopted this standard and will be utilizing it for two main purposes in the first instance. i) It will allow EGA users to instantly identify what terms they will need to agree to as part of any Data Access Agreements. This will save valuable time for both applicants and Data Access Committees alike - as you will be able to see if you are likely to be able to access the data based on your research intentions and working background. ii) In the future it will allow users to be able to search for data based on Data Use Ontology terms e.g., you could search for all data that can be used for General Research Use (GRU). As EGA moves forwards submitters will be asked to align their data access policies with DUO so that their dataset(s) can be tagged appropriately on our web pages. If you would like to add DUO to any of your existing datasets, or to any future datasets, do please just let us know.

  Blog data-use-ontology

• Human brain development single cell sequencing additional samples

  69 tissue samples from various parts of the developing human embryo brain were dissociated and single cells were collected and processed without bias for mRNA-seq using 10X chromium 3' protocol. Libraries were sequenced on Illumina NovaSeq and reads aligned against the human GRCh38 genome. This is an addition to EGAD00001006049 Human development single cell sequencing, consisting of samples added after the original submission to EGA, but included in final paper.

  Dataset EGAD50000001295

• Haplotype Reference Consortium Release 1.1

  Haplotype Reference Consortium Release 1.1 - subset for release via the EGA

  Dataset EGAD00001002729

• Out with the Java, in with the Python - new EGA data download client unveiled

  We will shortly be deprecating the Java-based download client also known as API V2. The Java client began its life at the back end of 2014, and during its time has seen many developments that have served our users well. During its tenure, the Java client enabled distribution of over 6.5 million files totalling nearly 15 petabytes of data to researchers around the globe. Recent increases in genomic and phenotypic data file sizes, the number of datasets archived in the EGA, the number of users downloading data, and the diversity of download locations has meant that at times the Java client struggled to distribute data efficiently. In response, our team of developers have built a new download client with more robust features and better functionality and reliability. Enter stage left our shiny new API V3.1! The new API V3.1 will replace both API V2 and API V3. The download client for the new API V3.1 is written in Python, and the code is openly available on Github. This Python client makes https calls to the EGA AAI (https://ega.ebi.ac.uk:8443/) and to the EGA Data API (https://ega.ebi.ac.uk:8052), both of which must be accessible from the client location. In addition to general updates to improve performance, the API V3.1 has three new features enhancing the EGA distributions services. First, requested data are now downloaded over secure https connections rather than http, meaning that data can be delivered unencrypted. Instead of separately requesting, downloading, and decrypting data using the Java client, data can now be requested and downloaded using a single command without the need for decrypting. The API V3.1 also automatically verifies each file’s unencrypted md5 after download to ensure the file has downloaded correctly. Second, the new API supports segmenting and automatic resuming. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the new resume feature, downloads - both segmented and continuous stream - will automatically resume if they encounter any errors or the connection is interrupted. These features result in both a faster and more reliable download experience. Finally, the new API V3.1 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file saving both time and storage space. The new features of the Python-based API V3.1 represent significant improvements in security, speed, reliability, and flexibility that are sure to provide a better data download experience. To take full advantage of these features, users must update to Python 3.X. Considering the changes in the data structures with the new API, the upgrade to a new version of the Python client is also mandatory. Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 -U We are excited for users to try out the new features and take advantage of the multifariously growing EGA distribution services for human biomedical omics data. If you have any questions or feedback, please email the EGA Helpdesk team. We'd love to hear from you!

  Blog new-ega-data-download-client

• Synthetic modeling reveals HOXB genes are critical for the initiation and maintenance of human leukemia

  Study EGAS00001003627

• Evaluation of protocols for rRNA depletion-based RNA sequencing of nanogram inputs of mammalian total RNA

  Study EGAS00001003849

• DAC - Comparison of sequencing assays for sensitive detection of circulating tumour DNA in stage IA-IV breast cancer

  Dac EGAC00001002549

• Exome Resequencing of Progressive Hearing Loss

  Exome resequencing of progressive hearing loss.

  Study EGAS00001000001

• Data Access Committee for data from EGAS00001002864: Genome analysis of oesophageal cancer and Barretts oesophagus

  Dac EGAC00001000863

• 1000IBD Data Access Committee UMCG

  Dac EGAC00001000791

• Molecular Oncology Group, PICR

  Dac EGAC00001000095

• This DAC is to control access to data contained within dataset EGAS00001001147, for Myeloma XI clinical trial patients.

  Dac EGAC00001000307

• Centre for Genomic Regulation - Beta Cell Genome Regulation Lab

  Dac EGAC00001000853

• DAC for present-day Central Asia genotype data at the Centre for GeoGenetics, Natural History Museum of Denmark.

  Dac EGAC00001000894

• DAC for "The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia"

  Dac EGAC00001001501

• Detection of ctDNA in Plasma of Patients with Clinically Localised Prostate Cancer is Associated with Rapid Disease Progression

  Dac EGAC00001001718

• BCRC-ICGS (Bladder Cancer Research Centre, Institute of Cancer and Genomic Sciences, Univ. of Birmingham) Data Access Committee

  Dac EGAC00001001982

• Division of Molecular Oncology, National Cancer Center Research Institute Data Access Committee

  Dac EGAC00001002007

• RNA-sequencing of tumors from 45 patients with recurrent or metastatic gastric cancer treated with immune checkpoint inhibitors

  Dac EGAC00001002295

• Whole-exome sequencing of 47 microsatellites stable Early-onset sporadic rectal cancer (EOSRC) tumors and corresponding normal samples.

  Dac EGAC00001002502

• DAC for Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer

  Dac EGAC00001002644

• EGAD00000000046

  RNA-SEQ data from 3 recurrent and 1 ovarian primary Granulosa Cell Tumour samples

  Dataset EGAD00000000046

• EGAD00000000047

  Signal data for from 3 recurrent and 1 ovarian primary Granulosa Cell Tumour samples

  Dataset EGAD00000000047

• EGAD00010000662

  Finnish population cohort genotyping

  Dataset EGAD00010000662

• EGAD00010000787

  Epigen-Brasil samples using HumanOmni2.5

  Dataset EGAD00010000787

• EGAD00010000377

  DNA methylation analysis of 6 primary lymphoma samples

  Dataset EGAD00010000377

• EGAD00010000379

  DNA methylation analysis of 2 peripheral blood samples

  Dataset EGAD00010000379

• EGAD00010000570

  Imputation-based meta-analysis of severe malaria in Kenya.

  Dataset EGAD00010000570

• Osteosarcoma Sequencing

  Osteosarcoma Sequencing

  Dataset EGAD00001000007

• Kaposi sarcoma exome

  Kaposi sarcoma exome

  Dataset EGAD00001000071

• MDSMPN Rearrangement Screen

  MDSMPN Rearrangement Screen

  Dataset EGAD00001000073

• Chondrosarcoma Exome

  Chondrosarcoma Exome

  Dataset EGAD00001000125

• Osteosarcoma Whole Genome

  Osteosarcoma Whole Genome

  Dataset EGAD00001000147

• OICR PANCREATIC CANCER DATASET

  OICR PANCREATIC CANCER DATASET

  Dataset EGAD00001000262

• Pulldown cytosine deaminases

  Pulldown cytosine deaminases

  Dataset EGAD00001000245

• Conventional whole genome bisulfite sequencing protocol

  Dataset EGAD00001000601

• Landscape of gene mutations in Down syndrome-related myeloid disorders

  Dataset EGAD00001000628

• MCL bam dataset

  Complete set of bam files associated with study EGAS00001000622

  Dataset EGAD00001000702

• W115 Deep Sequencing

  Dataset EGAD00001000779

• MPNST

  These are only the whole exome sequences

  Dataset EGAD00001001031

• Whole-Genome Bisulfite Sequencing of a paired initial and recurrent glioma

  Dataset EGAD00001001616

• DATA FILES FOR PCGP SJACT WGS

  Dataset EGAD00001001874

• CPCG-BRCA-ARRAY

  Raw Array data from the CPCGene BRCA study

  Dataset EGAD00010001196

• SNP_dataset_1

  Tissue samples using Illumina HumanOmniExpress-FFPE-12 v1.0 BeadChip

  Dataset EGAD00010001179

• papuan-U-1

  Papuan Genotyping

  Dataset EGAD00010001326

• REL-2017-07-1273

  HipSci - Monogenic Diabetes - Genotyping Array - July 2017

  Dataset EGAD00010001334

• REL-2017-07-2005

  HipSci - Hereditary Cerebellar Ataxias - Genotyping Array - July 2017

  Dataset EGAD00010001344

• REL-2017-07-2006

  HipSci - Hereditary Spastic Paraplegia - Genotyping Array - July 2017

  Dataset EGAD00010001346

• REL-2017-07-2012

  HipSci - Primary Immune Deficiency - Genotyping Array - July 2017

  Dataset EGAD00010001358

• UK BioBank Imputed dataset 2018

  UK BioBank Imputed Dataset

  Dataset EGAD00010001474

• ARGO-Larissa GWAS

  The ARGO-Larissa GWAS.

  Dataset EGAD00010000883

• Trachoma_GWAS_Unscarred_Controls

  Gambian specimens with trachomatous scarring WHO grade C2/C3

  Dataset EGAD00010000940

• RHD_FJ_OMNI_Controls

  Healthy volunteers recruited in Fiji with higher density genotyping

  Dataset EGAD00010000958

• MCF10A 24h IL6 classical and trans-signaling

  Gene expression after cell culture, 24h IL6 stimulated

  Dataset EGAD00010001965

• Tumor dataset - Case

  tumor-based gene expression from breast cancer cases

  Dataset EGAD00010001064

• MCF10A 12h IL6 classical signaling

  Gene expression after cell culture, 12h IL6+sgp130-Fc stimulated

  Dataset EGAD00010001970

• phenotype

  2619 individuals with visual contour perception phenotype scores, in the form of averaged accuracy

  Dataset EGAD00010001729

• MCF10A 12h IL6 classical and trans-signaling

  Gene expression after cell culture, 12h IL6 stimulated

  Dataset EGAD00010001967

• MCF10A 24h IL6 classical signaling

  Gene expression after cell culture, 24h IL6+sgp130-Fc stimulated

  Dataset EGAD00010001963

• Genotypes_343_Japanese

  Genotype data for 343 Japanese subjects obtained with Infinium Asian Screening Array.

  Dataset EGAD00010002449

• SNP Array CB1003

  SNP Array from CB1003 using Cytoscan HD, Thermo Fisher Scientific

  Dataset EGAD00010002225

• Cases_HCC

  A total of 87 microarrays from HCC patients treated with anti-PD1 inhibitors

  Dataset EGAD00010002255

• Genotype_cases

  Japanese COVID-19 PLINK file

  Dataset EGAD00010002319

• Genotype

  PLINK file of the Japanese population

  Dataset EGAD00010002427

• BM

  metabolite levels measured by Brainshake Metabolomics/Nightingale Health metabolic platform (log2)

  Dataset EGAD00010002150