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• The Scientific ethical comittee capital region of Denmark (De videnskabs etiske komiteer region hovedstaden)

  Dac EGAC00001001063

• Expanding the neurodevelopmental phenotypes of individuals with de novo KMT2A variants Data Access Committee

  Dac EGAC00001001147

• Magdalena_de_Cao_Peru

  Samples from Magdalena de Cao, Peru

  Dataset EGAD00010001934

• Germline

  This study is part of the 'First 1,000 Days of Life and Beyond' study at the Inova Translational Medicine Institute. Whole-genome sequencing data from 1,291 parent-offspring trios was used to study the properties of clustered de novo mutations. The maternal clusters were found to be enriched in regions with accelerated maternal mutation rate and show distinct mutational signatures. For additional details, please refer to: "Germline de novo mutation clusters arise during oocyte aging in genomic regions with increased double-strand break incidence". Jakob M. Goldmann, Vladimir B. Seplyarskiy, Wendy S.W. Wong, Thierry Vilboux, Pieter B. Neerincx, Dale L. Bodian, Benjamin D. Solomon, Joris A. Veltman, John F. Deeken, Christian Gilissen, John E. Niederhuber. Nature Genetics.

  Study phs001522

• Diagnostic Exome Sequencing in Persons with Severe Intellectual Disability

  Intellectual disability is a common condition that carries lifelong severe medical and developmental consequences. The causes of intellectual disability (ID) remain unknown for the majority of patients due to the extensive clinical and genetic heterogeneity of this disorder. De novo mutations may play an important role in ID as most individuals with ID present as isolated cases without family history and/or clear syndromic indication. In addition, the involvement of such mutations have recently been demonstrated in a small number of individuals with ID. Here we evaluate the diagnostic potential and role of de novo mutations in a cohort of 100 patients with ID of unknown cause using family-based exome sequencing.

  Study EGAS00001000287

• ICGC Prostate Cancer Whole Genome Sequencing

  To characterize the subclonal genomic architecture of androgen-deprived metastatic prostate cancer, we performed whole-genome sequencing (WGS) of 51 tumours from 10 patients to an average sequencing depth of 55x, including multiple metastases from different anatomic sites in each patient and, in five cases, the prostate tumour. Noncancerous DNA from blood or other tissue is used as reference comparison for each patient. The patients are part of PELICAN (Project to ELIminate Lethal Cancer) rapid autopsy study led by G. Steven Bova at Johns Hopkins University (USA) and Tampere University (Finland). As of September 2020, some of the studies using these data include: Gundem et al, Nature 2015 (PMID: 25830880). Additional EGAD00001000891 sample metadata is contained in Supplementary Information in this report.Tubio et al, Science 2014 (PMID: 25082706) Behjati et al, Nature Comm 2015 (PMID: 27615322) Wedge et al, Nature Genetics 2018 (PMID: 29662167)Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)Rodriguez-Martin et al, Nature Genetics 2020 (PMID: 32024998)Woodcock et al, Nature Comm 2020 (In Press)

  Dataset EGAD00001000891

• SweGen genetic variation from the Swedish Twin Registry

  The dataset contains files with single nucleotide variants in VCF format for a total of 942 DNA samples, selected to represent a cross-section of the Swedish population. The samples originate from the Swedish Twin Registry (STR) and have been obtained from different geographical regions. For each of the 942 individuals, DNA was extracted from a blood sample and subject to whole genome sequencing (WGS). The WGS was performed using 2x150 bp paired-end chemistry on Illumina HiSeq X Ten instrumentation at the SciLifeLab National Genomics Infrastructure (NGI) in Stockholm and Uppsala. FASTQ files generated by WGS were analyzed using the nf-core pipeline Sarek, which includes pre-processing, alignment to the human GRCh38 reference genome, and germline variant calling. All participants gave their written informed consent and the TwinGene study was approved by the regional ethics committee (Regionala Etikprövningsnämnden, Stockholm, dnr 2007-644-31, dnr 2014/521-32). Access to phenotypic information can be requested from the Swedish Twin Registry (http://ki.se/en/research/the-swedish-twin-registry).

  Dataset EGAD50000001323

• SweGen whole-genome sequencing from the Swedish Twin Registry

  The dataset contains whole-genome sequencing data (aligned read files) in CRAM-format (lossless compression) for a total of 942 DNA samples, selected to represent a cross-section of the Swedish population. The samples originate from the Swedish Twin Registry (STR) and have been obtained from different geographical regions. For each of the 942 individuals, DNA was extracted from a blood sample and subject to whole genome sequencing (WGS). The WGS was performed using 2x150 bp paired-end chemistry on Illumina HiSeq X Ten instrumentation at the SciLifeLab National Genomics Infrastructure (NGI) in Stockholm and Uppsala. FASTQ files generated by WGS were analyzed using the nf-core pipeline Sarek, which includes pre-processing, alignment to the human GRCh38 reference genome, and germline variant calling. All participants gave their written informed consent and the TwinGene study was approved by the regional ethics committee (Regionala Etikprövningsnämnden, Stockholm, dnr 2007-644-31, dnr 2014/521-32). Access to phenotypic information can be requested from the Swedish Twin Registry (http://ki.se/en/research/the-swedish-twin-registry).

  Dataset EGAD50000001326

• Woodcock et al TenMenDeep Study EGA Dataset B

  Woodcock et al TenMenDeep EGA Dataset B. These are Illumina based deep sequencing data based on bait capture sequencing. See Woodcock et al methods for more detail. Note: the Amplicon sequencing data type is selected because the EGA Website currently has no option to select Bait Capture Sequencing or similar.

  Dataset EGAD00001005382

• Woodcock et al TenMenDeep Study EGA Dataset A

  Woodcock et al TenMenDeep EGA Dataset A. These are Illumina based deep sequencing data based on bait capture sequencing. See Woodcock et al methods for more detail. Note: the Amplicon sequencing data type is selected because the EGA Website currently has no option to select Bait Capture Sequencing or similar.

  Dataset EGAD00001005381