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• PARK7/DJ-1 deficiency modulates microglial activation in response to LPS-induced inflammation

  Specific microglia responses are thought to contribute to the development and progression of various neurodegenerative diseases, including Parkinson’s disease (PD). However, the phenotypic acquisition of microglial cells and their role during the underlying neuroinflammatory processes remain largely obscure. Here, according to the multiple-hit hypothesis, which stipulates that PD etiology is determined by a combination of genetics and various environmental risk factors, we investigate microglial transcriptional programs and morphological adaptations under PARK7/DJ-1 deficiency, a genetic cause of PD, during lipopolysaccharide (LPS)-induced inflammation.

  Study EGAS50000000202

• Mosaic structural variation sample

  Mosaic Normal-Tumor genomes are generated from real normal-tumor pairs with validated somatic variants. In this case, validated variants from the GRIDSS2 paper. Mosaic genomes were generated using GenomeMosaicMaker, an open-source software tool designed and implemented for this specific purpose. The variants provided in the VCF truth file for each mosaic tumor/normal pair were annotated using funnSV for SVs and VEP for SNVs and indels. All CRAM files are aligned to GRCh37. Please see https://github.com/EUCANCan/oncoliner and https://github.com/Computational-Genomics-BSC/GenomeMosaicMaker for more information.

  Study EGAS50000000460

• Metabolic Biomarkers in Thoracic Cancers

  Here we present RNA sequencing (RNA-Seq) of non-small cell lung cancer (NSCLC) and adjacent lung tissue. These samples were acquired from primarily untreated, surgically resected primary tumors. The first analysis published with this data was to determine the metabolic signatures between primary tumors and adjacent lung tissue.The associated clinical trial (NCT02095808) includes patients with many kinds of thoracic cancers, including NSCLC and other diseases, such as thymoma and esophageal adenocarcinoma. However, the current dbGaP data is focused on the NSCLCs described in the associated paper.

  Study phs003880

• Synthetic - FEGA Sweden Heilsa synthetic dataset December 2023

  Synthetic - This submission contains a subset of a synthetic dataset derived from the project Heilsa Tryggvedottir - a Nordic collaboration on sharing sensitive human data. Heilsa Tryggvedottir is funded by the Nordic e-Infrastructure Collaboration (NeIC), the ELIXIR nodes of Finland, Norway, and Sweden, Computerome in Denmark, and the Estonian Scientific Computing Infrastructure (ETAIS). In the synthetic data creation process, it was attempted to strike a fine balance between the usability of the datasets (e.g. technical FEGA development, testing, user training, and basic bioinformatics) and compliance with GDPR. File names and file content (e.g. headers in fastq) are anonymized. Moreover, the X, Y, and mitochondrial sequences have been discarded from the original data since these data can be used for maternal, paternal, or ethnic origin tracing. The dataset does not follow natural haplotype distribution (inherent to imputation panels). The only inputs derived from real sequence data are variant distribution density per chromosome and learning sequencing error models. The synthetic dataset consists of two fastq files, a cram file, a vcf file, and two index files.

  Dataset EGAD50000000119

• Multi-Omics Study of Lung Cancer in Smokers From EAGLE

  EAGLE (Environment And Genetics in Lung cancer Etiology) is a population-based case-control study examining the full spectrum of lung cancer etiology from smoking initiation, smoking dependency to lung cancer development and outcome. It combines a traditional molecular epidemiology design with more integrative approaches by examining epidemiological, molecular, and clinical data together. To comprehensively investigate the effect of tobacco smoking behaviors on genomic or epigenomic alterations, we performed a multi-omics study including whole-genomic, transcriptomic, and epigenomic profiles in a total of 221 individuals from the EAGLE study.

  Study phs002992

• Single cell transcriptome sequencing of the developing human embryonic meninges

  There are no effective medical therapies for meningiomas, partly due to our limited understanding of their cellular origin and composition For this purpose, we generated data to make a comprehensive reference single cell and spatial transcriptomic atlas of human fetal meninges. Samples of meninges from human embryos of post-conceptional week (PCW) 5.0-13.0 were dissected and subject to 10Xgenomics chromium single cell RNA sequencing with the purpose of identifying cell types and gene expression programs for normal meninges development, Furthermore, this dataset should help discover cells of origin for meningiomas.

  Study EGAS50000000980

• Impact of Genomic Variation on Function (IGVF) Consortium

  The IGVF (Impact of Genomic Variation on Function) Consortium aims to understand how genomic variation affects genome function, which in turn impacts phenotype. The NHGRI is funding this collaborative program that brings together teams of investigators who will use state-of-the-art experimental and computational approaches to model, predict, characterize and map genome function, how genome function shapes phenotype, and how these processes are affected by genomic variation. These joint efforts will produce a catalog of the impact of genomic variants on genome function and phenotypes.

  Study phs003472

• High Resolution Analysis of Spatial Interactions of Hundreds of Promoters in HeLa Cells

  In this study we developed a new hybridisation-based promoter Capture-C protocol that makes use of biotinylated dsDNA probes and allows high-resolution promoter interactome description. Experiments aimed to describe spatial interactions of set of 861 promoters were performed in HeLa cells. We have found that enrichment efficiency and quality of final libraries in our study is on a par with established promoter Capture-C protocols. Meanwhile, our version of the probe preparation protocol is reasonably simple and makes Capture-C experiments more affordable and flexible.

  Study phs002014

• Spatial Transcriptomic Analysis (Xenium in situ) of Large Cell Neuroendocrine Carcinoma

  Lung LCNEC (Large Cell Neuroendocrine Carcinoma) has a poor prognosis, and no effective treatment has yet been established. We have discovered that LCNEC exhibits highly heterogeneous distribution of proteins such as neuroendocrine markers and YAP1 within the tumor. We hypothesize that this heterogeneity may be responsible for the variability in chemotherapy effectiveness and treatment resistance among LCNEC patients. Therefore, by using Xenium to analyze gene expression in greater detail along with tumor morphology, we aim to identify new characteristics of LCNEC and explore potential treatment strategies.

  Study JGAS000733

• NHLBI TOPMed: African American Sarcoidosis Genetics Resource

  This study aims to comprehensively interrogate the genomes of African American sarcoidosis families. Sarcoidosis is characterized by a hyperimmune response resulting in granuloma formation in multiple organs. It affects African Americans (AAs) more frequently and more severely than whites. While previous linkage, admixture, candidate gene and genome-wide association (GWA) studies show statistically compelling effects, causal variants are still unknown and much of sarcoidosis heritability is yet to be explained. This "missing" heritability likely includes effects of both common (minor allele frequency (MAF)>5%) and rare variants (MAF

  Study phs001207