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• Ribosome profiling shows variable sensitivity to detect open reading frames for conventional and different types of cryptic T cell antigens

  The aim of the study was to explore the sensitivity of ribosomal profiling to detect ORFs for cryptic antigens targeted by T cells in immune responses. Ribosomal profiling was performed for six EBV-LCLs. Detection of conventional and cryptic MiHA-encoding ORFs was compared. The data showed that open reading frames (ORFs) for conventional MiHAs as well as cryptic MiHAs in upstream ORFs were frequently detected with similar sensitivity. However, only a limited number of MiHAs in in reading frames alternative to protein-coding sequences and no ORFs derived from long non-coding RNAs were detected. In conclusion, Ribo-seq for identification of antigen-encoding ORFs is useful to screen for cryptic antigens in upstream ORFs as potential targets for immunotherapy.

  Study EGAS50000000322

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP)

  Cohort Description The Severe Asthma Research Program (SARP) has been investigating the clinical, physiologic and molecular phenotypes of asthma since 2000. It is currently following ~400 deeply phenotyped asthma patients. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 375 SARP participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 289 SARP participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 290 SARP participants in C4R.Derived data includes 43 variables for up to 463 SARP participants in C4R.Phenotype data includes 113 variables for up to 463 SARP participants in C4R.

  Study phs002913

• DAC for "Uncovering the potential of circulating tumor DNA for pediatric precision oncology"

  Dac for "Uncovering the potential of circulating tumor DNA for pediatric precision oncology" with Stefan Pfister (s.pfister@kitz-heidelberg.de) and Kendra Maass (k.maass@kitz-heidelberg.de)

  Dac EGAC50000000269

• Epigenetic Landscape of Human Parathyroids

  The goal of this study is to produce a comprehensive map of the chromatin landscape of human parathyroids. Data from 20 subjects with parathyroid adenoma causing primary hyperparathyroidism were used. For the sequencing platform, Illumina HiSeq 2000 with V3 high-output kits were used. For the data processing pipeline, reads were aligned to hg19 using Bowtie or BWA. For RNA-seq data, transcript levels were estimated per gene to RPKM using Cufflink. For ChIP-seq and ATAC-seq data, enrichment peaks were estimated compared to inputs or background using MACS2 after merging reads from replicates. For DNase-seq, significant peaks compared to background distribution were computed using Hotspot. For Hi-C data, significant interactions were detected using Juicer HiCCUPS and 5 kb resolution for the merged data from replicates. Chromatin states for parathyroids were computed using ChromHMM based on ChIP-seq profiles in parathyroids of H3K4me3, H3K4me1, H3K27ac, H3K36me3, H3K27me3 and H3K9me3 and the emission matrix from 18 states pre-trained in the Roadmap Epigenomics. Gene expression, binding positions of transcription factor, open chromatin regions, 3D-chromatin interaction, and chromatin states are submitted.

  Study phs003302

• The brain neurovascular epigenome and its association with dementia

  Cerebral small vessel disease (SVD) is frequently comorbid with Alzheimer’s disease (AD) and vascular brain endothelial cells (BECs) are enriched for the expression of genes associated with AD genetic risk. However, the gene regulatory landscapes of neurovascular cells and their intersection with genetic risk for disease remains unexplored. Here we have generated gene regulomes for human BECs, mural cells and other brain cell types to show that AD heritability is primarily immune-related and that it shows modest enrichment in BECs. By contrast, genetic risk for SVD is enriched across cells of the neurovascular unit, including astrocytes. Enhancer-to-gene interactomes implicate amyloid processes in both AD and SVD, though the risk genes are mostly distinct for the two disorders. Motifs for putative partners of lineage transcription factors in microglia and BECs were enriched for AD and SVD variants at genes linked to disease pathways. Gene prioritization and enrichment analyses further identified potential repurposable drugs for AD. Our findings highlight novel regulatory mechanisms and therapeutic targets within the neurovascular system.

  Study EGAS50000001160

• COVID-19 Severity of First Wave of Infection for Severe Patients in Madrid

  Through thorough exclusion criteria and deep phenotypic characterisation for a Madrid-based population we intend to find enrichment of gene mutations associated to severity. In addition we will look for statistically overrepresented annotation of particular phenotypes (a controlled vocabulary specifically developed for this project) that associate them to affected genes in our patient sample.

  Study EGAS00001005931

• March 2017 data update (bam/fastq) (containing H3K27ac for CEMT_87, RNA-Seq for CEMT_141, CEMT_142, CEMT_145, CEMT_146, H3K27me3, H3K9me3, H3K4me3, H3K4me1, ChIP-Seq Input for CEMT_88, CEMT_90 and CEMT_91) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  March 2017 data update (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001003272

• dbGaP Collection: Compilation of Individual-Level Genomic Data for General Research Use

  This dbGaP Collection contains all authorized individual-level genomic datasets currently in dbGaP that are approved for General Research Use (GRU) and have no further limitations beyond those outlined in the model Data Use Certification Agreement. Access to this study will include any additional authorized individual-level GRU datasets that become available. Renewal of this study is required annually. Data Included in this Study Individual-level genomic data designated for general research use with no further use limitations or restrictions, that is, Data use does not require approval by an Institutional Review Board for secondary analyses Data have no publication embargo Data have no other use limitations (e.g., requirement for collaboration or publication; restricted for use by academic or not-for-profit organizations; restricted to health, medical, and/or biomedical research) In response to requests from the scientific community, the NIH implemented a change in the procedures for accessing individual-level GRU genomic data. Under the modified procedures, interested investigators can request GRU individual-level genomic datasets with a single application. However, please note that these data have not been harmonized. Additionally, to help expedite the processing of requests for individual-level GRU genomic datasets, the requests will be reviewed by a single, central Data Access Committee. The process for requesting these datasets is identical to the request process for non-GRU individual-level, controlled-access data, such as the expectation that investigators will abide by the NIH Policy for Sharing of Data Obtained in NIH Supported or Conducted Genome-Wide Association Studies and Data Use Certification Agreement. Effective April 24, 2018, the Data Use Limitations (DUL) for the Genes and Blood Clotting Study (GABC) (phs000304) was updated to Health/Medical/Biomedical, Not-for-profit Use Only (HMB-NPU). Additionally, the submitting institutions have requested the removal of the National Heart, Lung, and Blood Institute (NHLBI) "Grand Opportunity" Exome Sequencing Project (GO-ESP) Lung Cohorts Exome Sequencing Project: Genetic modifiers of Pseudomonas aeruginosa (Pa) lung infection acquisition in cystic fibrosis (phs000254) from the dbGaP Compilation of Individual-Level Genomic Data for General Research Use (dbGaP Compilation) (phs000688). As such, data from studies phs000304 and phs000254 are no longer available as part of the dbGaP Compilation (phs000688). Investigators must submit separate Data Access Requests (DARs) for the two studies and be approved by the NHLBI Data Access Committee.

  Study phs000688

• Data Access Committee for TIX Data

  Data Access Committee for the sequence data for TIX

  Dac EGAC50000000206

• Hypothesis Testing for Predictive Variables

  Hypothesis Testing for Predictive Variables

  Study EGAS00001007763