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• ATAC data for Glioblastoma (EGAS00001003953, H016)

  ATAC-seq data for 2 glioblastoma cell lines (LN229, ZH487), NT and SOX10KD.

  Dataset EGAD00001006544

• DAC for study Population Structure and Genetic Diversity in Argentinean populations

  Dac EGAC00001000426

• DAC for study Treg in breast cancer and healthy individuals

  Dac EGAC00001000638

• JKU and MUI Data Access Committee for targeted NGS panel data

  Dac EGAC00001000669

• VariantMedium: Sensitive and generalizable somatic point mutation calling with 3D DenseNets trained and evaluated on experimental confirmation data

  This study contains whole-exome sequencing (WES) and results of targeted deep-sequencing data of three matched tumor and normal cell lines, with two technical WES replicates each. The calls by Mutect2, Strelka2, and VariantMedium were confirmed using targeted deep sequencing on Illumina Miseq The targeted deep sequencing was performed in three runs and the results are summarized under VCF files.

  Study EGAS50000001661

• Myocardial Infarction Genetics Exome Sequencing Consortium: U. of Leicester

  MI cases were ascertained from two studies: (i) the British Heart Foundation Family Heart Study and (ii) the BRICCS Study. Control subjects were ascertained from the control subjects being recruited as part of the UK Aneurysm Growth Study (UKAGS). All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Illumina's ICE Capture reagent and sequencing was performed on an Illumina HiSeq 2000 or 2500.

  Study phs001000

• Lung_Cell_Atlas__Paediatric_RNA

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets

  Study EGAS00001008299

• Lung_Cell_Atlas__Paediatric_Spatial

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets

  Study EGAS00001008300

• Whole exome sequencing data of germline and two independent primary leukemias of five patients

  The contribution of genetic predisposing factors to the development of pediatric acute lymphoblastic leukemia (ALL), the most frequently diagnosed cancer in childhood, has not been fully elucidated. Children presenting with multiple de novo leukemias are more likely to suffer from genetic predisposition. Here, we selected five of these patients and analyzed the mutational spectrum of normal and malignant tissues. In two patients, we identified germline mutations in TYK2, a member of the JAK tyrosine kinase family. These mutations were located in two adjacent codons of the pseudokinase domain (p.Pro760Leu and p.Gly761Val). In silico modeling revealed that both mutations affect the conformation of this auto-regulatory domain. Consistent with this notion, both germline mutations promote TYK2 autophosphorylation and activate downstream STAT family members, which could be blocked with the JAK kinase inhibitor I. These data indicate that germline activating TYK2 mutations predispose to the development of ALL.

  Study EGAS00001001889

• Makrani_SNP_genotyping

  Genome-wide SNP genotyping data for 102 Pakistani individuals by Illumina HumanOmni2.5-8 array, used in the EGAS00001002558 study

  Dataset EGAD00010001452