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• 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

• Temporal Lobe Epilepsy and Retrotransposons

  Idiopathic (cryptogenic) epilepsy is a common, chronic group of brain disorders, affecting 1-2% of the US population, creating a significant public health problem because of the associated morbidity and mortality. One subtype of this complex group of brain disorders, temporal lobe epilepsy (TLE), is particularly burdensome, because a substantial fraction of patients do not respond to anticonvulsant medications. If the seizure focus can be localized by imaging and/or EEG, the TLE patient often elects to have a partial resection of the affected temporal lobe, because they have daily seizures, despite multiple pharmacotherapy regimens. Although genetic risk is thought to play a role in TLE, identification of common risk alleles has had limited success. In the past 5 years, data have accumulated to prove that neuronal embryogenesis is accompanied by activation of LINE1 (L1) retrotransposons (RTPs) to an unexpected degree, such that developing neurons may accumulate de novo L1 insertions. This results in a substantial mosaicism within populations of CNS neurons. While most of these somatic de novo L1s will have little effect on neuronal function (perhaps because they occur in gene deserts or in large introns or in genes not required for that cell's function), some may interfere with normal neuronal activity because they have inserted into a gene needed by that particular neuron for normal function. If one or more functional de novo L1s occur early in CNS development, all the daughter neurons that derive from that neuronal precursor will also carry the L1 insertion, perhaps leading to a dysfunctional population of neurons destined to become an epileptic focus. This study leveraged CNS tissue (obtained at craniotomy) from patients with intractable TLE, who have undergone a therapeutic partial resection of one temporal lobe. Using fluorescence-assisted cell sorting of temporal lobe neuronal nuclei, followed by high-throughput sequencing and alignment to the reference genome, detection of de novo L1s will be done. In this manner, it is expected that de-novo intragenic L1s, contributing to idiopathic TLE, will be discovered.

  Study phs002067

• DAC for study: "Circulating tumour DNA abundance and potential utility in de novo metastatic prostate cancer"

  Dac EGAC00001001099

• 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

• 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

• AfricanNeo WGS aDNA Dataset

  This dataset includes WGS data of 12 ancient individuals (97–688 years BP) from Zambia and South Africa, presented in Fortes-Lima et al. Nature 2023. Further details like C14-dates and archaeological descriptions were reported elsewhere (Meyer et al. Azania 2021; Steyn et al. African Archaeological Review 2022).

  Dataset EGAD00001011320

• Institute of Pathology at the University Hospital of Lausanne CHUV

  Prof Laurence de Leval

  Dac EGAC50000000314

• 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

• De novo mutations in cell-free foetal DNA (cffDNA)

  This project is to develop and validate a method to detect de novo mutations in a foetal genome through deep sequencing of cell-free DNA from the plasma of pregnant women. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000596

• Synthetic genotypes and phenotypes of 500.000 individuals

  The goal of our study is to establish a pipeline for creating synthetic genotype and phenotype data on a Biobank scale. Such data can be used for developing new methodologies of analysis of common and rare diseases without risking de-identifying the underlying samples.

  Study EGAS00001006552

• GWAS results from Danjou et al, Nature Genetics 2015

  GWAS results in epacts format for Danjou et al, Nature Genetics 2015

  Dataset EGAD00010001722

• International Parkinson's Disease Genomics Consortium (IPDGC), NeuroX Dataset

  Expanded replication set based on Nalls et al. 2014.

  Study phs000918

• Multi-focal genomic dissection of synchronous primary and metastatic tissue from de novo metastatic prostate cancer - Data Access Committee

  Dac EGAC00001002905

• DAC for the BCTL

  DAC for submissions from the BCTL (Hopital Jules Bordet, Université LIbre de Bruxelles)

  Dac EGAC50000000323

• Epidemiologic Architecture for Genes Linked to Environment (EAGLE) MetaboChip Study

  The Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study is a study site of the larger Population Architecture using Genomics and Epidemiology (PAGE) I study.  EAGLE accessed two data resources during the course of study: the National Health and Nutrition Examination Surveys (NHANES) and BioVU, the Vanderbilt University Medical Center biorepository linked to de-identified electronic health records.The EAGLE MetaboChip Study, also known as EAGLE BioVU in the literature, is a data resource of Illumina MetaboChip genotypes for ~15,000 DNA samples from African American/Black, Hispanic, and Asian patients in BioVU (PMID: 26201699). Several EAGLE BioVU and PAGE I study phenotypes were extracted using structured and unstructured data available in de-identified electronic health records linked to the DNA samples. 

  Study phs002767

• Prostate Cancer and Normal Adjacent Prostate RNA-seq samples, NGS-ProToCol

  The dataset "Prostate Cancer and Normal Adjacent Prostate RNA-seq samples, NGS-ProToCol" includes 41 Normal Adjacent Prostate and 51 ribo-depleted Prostate Cancer RNA-seq samples. ---- Detection of fusion transcripts and their genomic breakpoints from RNA sequencing data Youri Hoogstrate, Malgorzata A. Komor, René Böttcher, Job van Riet, Harmen J. G. van de Werken, Stef van Lieshout, Ralf Hoffmann, Evert van den Broek, Anne S. Bolijn, Natasja Dits, Daoud Sie, David van der Meer, Floor Pepers, Chris H. Bangma, Geert J. L. H. van Leenders, Marcel Smid, Pim French, John W.M. Martens, Wilbert van Workum, Peter J. van der Spek, Bart Janssen, Eric Caldenhoven, Christian Rausch, Mark de Jong, Andrew P. Stubbs, Gerrit A. Meijer, Remond J.A. Fijneman, Guido Jenster

  Study EGAS00001002816

• PCa-LINES

  PCa-LINES: Ribo-minus RNA-seq of 4 patient samples and 2 PCa cell lines ---- Detection of fusion transcripts and their genomic breakpoints from RNA sequencing data Youri Hoogstrate, Malgorzata A. Komor, René Böttcher, Job van Riet, Harmen J. G. van de Werken, Stef van Lieshout, Ralf Hoffmann, Evert van den Broek, Anne S. Bolijn, Natasja Dits, Daoud Sie, David van der Meer, Floor Pepers, Chris H. Bangma, Geert J. L. H. van Leenders, Marcel Smid, Pim French, John W.M. Martens, Wilbert van Workum, Peter J. van der Spek, Bart Janssen, Eric Caldenhoven, Christian Rausch, Mark de Jong, Andrew P. Stubbs, Gerrit A. Meijer, Remond J.A. Fijneman, Guido Jenster bioRxiv 2021.05.17.441778; doi: https://doi.org/10.1101/2021.05.17.441778 https://www.biorxiv.org/content/10.1101/2021.05.17.441778v1

  Study EGAS00001004613

• Novel de novo pathogenic variant in the GNAI1 as a cause of severe disorders of intellectual development with autistic features

  Dac EGAC00001002145

• Novel de novo pathogenic variant in the GNAI1 as a cause of severe disorders of intellectual development with autistic features

  Dac EGAC00001002151

• Veilleux et al. Human Subsistance - chemosensory genes

  BAM files from capture-sequencing dataset described in Veilleux et al.

  Dataset EGAD00001010918

• SCLC study Peifer et al. - WES dataset

  SCLC - Whole genome sequencing data Publication Peifer et al., 2012, Nature Genetics

  Dataset EGAD00001000703

• Novel de novo pathogenic variant in the GNAI1 as a cause of severe disorders of intellectual development with autistic features

  Study EGAS00001005346

• Novel de novo pathogenic variant in the GNAI1 as a cause of severe disorders of intellectual development with autistic features

  Study EGAS00001005355

• He et al. WGS data

  This dataset are the bam files of WGS data from the paper by He et al.

  Dataset EGAD00001007133

• Somatic Mutational Analysis by Exome Sequencing Endometrial Carcinosarcomas

  The purpose of this study was to identify somatic (tumor-specific) mutations in endometrial carcinosarcoma tumor exomes. The dataset was generated at the NIH Intramural Sequencing Center (NISC) and NHGRI by next generation sequencing the exomes of 14 de-identified primary tumor DNAs and matched non-tumor DNAs.

  Study phs001152

• Non-coding mutations drive persistence of a founder pre-leukemic clone which initiates late relapse in T-ALL

  T-ALL relapse usually occurs early but can occur much later, which has been suggested to represent a de novo leukemia. However, we conclusively demonstrate late relapse can evolve from a pre-leukemic subclone harbouring a non-coding mutation that evades initial chemotherapy.

  Study EGAS50000000129

• Single cell Transcriptomic Analysis of Cellular Heterogeneity in Human Colorectal Tumors

  1,591 single cells from 11 colorectal cancer patients were profiled using Fluidigm based single cell RNA-seq protocol to characterized cellular heterogeneity of colorectal cancer. 630 single cells from 7 cell lines were profiled similarly to benchmark de novo cell type identification algorithms.

  Study EGAS00001001945

• Tetralogy of Fallot Exome Trios

  Exome sequencing of 30 parent-offspring trios to >50X mean depth, where the offspring has sporadic TOF, to identify potential causal de novo mutations. We will use the exome plus design for pulldown that incorporates ~6.8Mb of additional regulatory sequences in addition to the ~50Mb GENCODE exome.

  Study EGAS00001000071

• SCLC study Peifer et al. - RNAseq dataset

  SCLC - RNA sequencing data Publication Peifer et al., 2012, Nature Genetics

  Dataset EGAD00001001431

• Circulating tumour DNA abundance and potential utility in de novo metastatic prostate cancer

  Several systemic therapeutic options exist for metastatic castration sensitive prostate cancer (mCSPC). Circulating tumour DNA can profile metastatic castration resistant prostate cancer and influence treatment decisions, but remains untested in mCSPC. We set out to determine ctDNA abundance at de novo mCSPC diagnosis and whether ctDNA provides complementary clinically relevant information to a prostate biopsy. We collected and sequenced 77 plasma cell-free DNA samples from 53 newly diagnosed patients with mCSPC. Targeted sequencing was also performed on DNA from 48 diagnostic prostate tissue samples.

  Study EGAS00001003351

• Low-input PCHi-C data in CD4+ T cells

  Low-input PCHi-C data in CD4+ T cells from Malysheva et al.

  Study EGAS50000001316

• Fine Mapping of Eight Psoriasis Susceptibility Loci

  Psoriasis is a common immune-mediate disease identified through scaly patches of the skin. In this study we collected genotype information on 5,067 samples of European ancestry as a follow-up study of our initial GWAS (Nair et al. 2009). We designed an Illumina iSelect custom genotyping array with 2,269 tagging SNPs in the eight known psoriasis susceptibility regions (MHC, IL12B, IL23R, IL23A, TNFAIP3, IL13, RNF114, and TNIP1). The custom array also included 5,463 SNPs outside the eight known susceptibility regions, which were selected based on their association p-values in a meta-analysis of HapMap-imputed genotypes of two published GWAS-CASP (Nair et al. 2009) and (Ellinghaus et al. 2010). After quality control we analyzed 4,806 samples (2,699 cases and 2,107 controls). Please note: The accession number for this dbGaP study was incorrectly listed in the relevant publication (Das et al., 2015, Eur. J. Hum. Genet 23:844-853) as phs000019.v1.p1.

  Study phs001298

• Analysis of Somatic Mutations in Pediatric AML FAB-M7 Subtype by Whole Transcriptome Sequencing

  High resolution analysis of DNA copy number abnormalities and loss-of-heterozygosity on acute myeloblastic leukemia samples utilizing SNP arrays has demonstrated that in contrast to pediatric ALL, de novo AML is characterized by a very low burden of genomic alterations (Radtke, et al., PNAS, 2009). Samples for this study represented a cross-section of the different subtypes of pediatric AML. The only AML subtype that was an outlier from the above observations was acute megakaryocytic leukemia (AML FAB-M7), with the majority of these cases being characterized by complex chromosomal rearrangements and a high number of copy number alterations. To more fully define the genomic landscape of this subtype, we performed transcriptome sequence analysis on 14 pediatric FAB-M7 cases and mutation recurrence screening in a panel of 62 adult and pediatric AML FAB-M7 samples using the Illumina platform. Our results identified chromosomal rearrangements resulting in the expression of novel fusion transcripts in 11/14 cases. Remarkably, in 7/14 cases we detected an inversion on chromosome 16 that results in the juxtaposition of the CBFA2T3 gene next to the GLIS2 gene resulting in a CBFA2T3-GLIS2 chimeric gene that encoded an in frame fusion protein. This fusion led to the acquisition or preservation of self-renewal in colony forming assays, providing functional evidence for a role in leukemogenesis. In addition to novel chimeric transcripts, we found mutations in genes previously identified to play a role in megakaryoblastic leukemia that carry a proliferative advantage to the cell, such as JAK2 and MPL. These data demonstrate that AML FAB-M7 is characterized by cooperating Class I and Class II mutations leading to leukemogenesis.

  Study phs000413

• HELIUS cohort

  The gut microbiota composition is unique to every individual but is shaped by common factors including diet, lifestyle, medication use, early-life determinants, living environment or genetics. Most of these factors may be influenced by ethnicity. This study explored variations in fecal microbiota composition in 6048 individuals with different ethnic backgrounds living in the same geographical area (Amsterdam, the Netherlands). The HELIUS data are owned by the Amsterdam University Medical Centers, location AMC in Amsterdam, The Netherlands. To allow sharing of microbiome data collected in HELIUS with (inter)national researchers, 16s rRNA sequence analysis has been stored at the European genome-phenome archive (EGA; accession code EGAD00001004106). This requires that access needs to be granted, also because the HELIUS data are stored with relevant phenotypical variables. Access is granted to all researchers affiliated with an internationally recognized research institution who request to use the HELIUS data within the EGA context, after having signed the data transfer agreement. Any researcher can request the data by submitting a proposal to the HELIUS Executive Board as outlined at http://www.heliusstudy.nl/en/researchers/collaboration, by email: heliuscoordinator at amsterdamumc dot nl. The HELIUS Executive Board will check proposals if they do not conflict with ethical approvals and informed consent forms of the HELIUS study.

  Study EGAS00001002969

• Exome_trios_in_patients_with_gastroschisis

  Gastroschisis (MIM 230750) is a herniation of the intestines through a defect of the abdominal wall lateral to the umbilicus (usually on the right side), and it is not covered by a membrane [Ledbetter, 2012]. Gastroschisis is a congenital anomaly with increasing incidence, easy prenatal diagnosis and extremely variable postnatal outcomes. On the basis of clinical manifestations, epidemiologic charateristics, and the presence and type of additional malformations, gastroschisis could be considered a heterogeneous condition with no gene/s discovered yet. This congenital anomaly affects approximately 1-3 infancts per 10,000 live births [Calzolari et al.1995;Parker et al.,2010] Current knowledge about causative mutations/variants. To date, no single gene has been linked to gastroschisis. Some publications have tried to link this malformation to variants in genes (such as AEBP1 (adipocyte enhancer binding protein) gene [Feldkamp et al,. 2012] or the VEGF-NOS3 pathway [Lammer et al., 2008]. Previously, a Scribble mutant mouse model (circletail) was reported to exhibit gastroschisis, however recent studies demonstrated that the Scribble knockout fetus exhibits exomphalos phenotype of gastroschisis [Carnagham et al., 2013]. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002664

• VALCAP files for Ma et al. (2019) SCMC Hybrid

  VALCAP files for Ma et al. (2019) Genome Biology (accepted) titled “Analysis of error profiles in deep next-generation sequencing data"

  Dataset EGAD00001004595

• MMR (DNA mismatch repair) pathway in human samples

  This data are related to the manuscript by Germano et al. Ms2016-04-06029

  Study EGAS00001002694

• Genome-wide Association Study for Non-syndromic Clefts in the African Population: CIDR

  The focus of this project is to identify genetic variants that are associated with orofacial clefts in African populations in sub-Saharan Africa. Most genetic studies of CLP (including the vast majority of GWAS) have been conducted in populations of European origin with only a few focused on Asian or African populations. We choose to study the genetics of these complex traits in African populations because, African populations have the greatest genetic variation amongst the various populations in the world by virtue of being the primary ancestral population to modern humans (Cavalli-Sforza and Feldman, 2003; Ramsay et al., 2011). Therefore, the potential for finding novel loci for CLP is quite high. To date 6 genome wide association studies (GWAS) for cleft lip with or without cleft palate (CL/P) have been conducted and 18 risk loci identified (Birnbaum et al., 2009; Grant et al., 2009 ; Beaty et al., 2010; Mangold et al., 2010; Ludwig et al., 2012; Sun et al., 2015). All these studies have either been conducted in European populations, Asian populations or both. There is currently no published GWAS for clefts in African populations. African populations represent a novel and richly productive populations for genetic and environmental exposure studies for CL/P. Investigating the presence of genetic variants in diverse population groups can identify novel variants and candidate genes that are population specific. Environmental factors may also increase the risks in certain population groups due to genetic susceptibility and/or specific exposures. Understanding the role these susceptibility genes play in the effects of environmental risk factors can inform strategies designed towards reducing the outcome of these complex traits, e.g. through the modification of the environmental influences. The study population comprises a large number of individuals (3205 individuals) from Africa (Ghana, Ethiopia and Nigeria). There are cases, case triads (nuclear families), as well as controls with no history of OFC nor other developmental defects.

  Study phs001090

• Single Cell Omics Resolves Transcriptional Alterations in Sjogren's Syndrome

  Single cell omics resolves transcriptional alterations in Sjogren's Syndrome. This data compares the single cell transcriptional profiles of the minor salivary glands between Sjogren’s Syndrome patients and non-Sjogren’s Syndrome subjects. Portions of this data were reported in two separate publications: Huang & Perez, et al., 2021 Nature Medicine and Yin, et al., 2021, Frontiers in Immunology . 

  Study phs002446

• Normal brain controls for ICGC PedBrain DNA methylation sequencing

  DNA methylation profiling of 8 control samples from adult (4) and fetal brain (4) used, for example, for the following studies: Mack, Witt, et al. Epigenomic alterations define lethal CIMP-positive ependymomas of infancy. Nature 506(7489):445-450, 2014 (see EGAS00001000443) Hovestadt, et al. Decoding the regulatory landscape of medulloblastoma using DNA methylation sequencing. 510(7506):537-541, 2014 (see EGAS00001000561)

  Study EGAS00001000909

• Second generation noninvasive fetal genome analysis reveals de novo mutations, single-base parental inheritance, and preferred DNA ends

  Dataset EGAD00001003778

• Array data for oesophageal and related samples – Ganguli et al (methylation array)

  Array data for oesophageal and related samples – Ganguli et al (methylation array)

  Dataset EGAD00010002682

• Exome Sequencing of Clear Cell Endometrial Tumors and Paired Non-tumor Samples

  The purpose of this study was to identify somatic (tumor-specific) mutations in clear cell endometrial tumor exomes. The dataset was generated at the NIH Intramural Sequencing Center (NISC) and NHGRI by next generation sequencing the exomes of 16 de-identified primary tumor DNAs and matched non-tumor DNAs.

  Study phs000967

• De novo detection of somatic variants

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. This dataset contains scDNA-seq data for 3 ovarian cancer samples from the Tumor Profiler Study used to validate LongSom. LongSom is a computational workflow leveraging high-quality long-read scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), including in mitochondria (mtSNVs), copy-number alterations (CNAs), and gene fusions, to reconstruct tumor clonal heterogeneity.

  Dataset EGAD50000001292

• SF3B1 splicing signature

  We describe individuals with de novo pathogenic variants in SF3B1. SF3B1 is a core component of the U2 snRNP complex that ensures accurate branchpoint and 3′ splice-site recognition, and its mutations induce aberrant splicing that contributes to tumorigenesis, notably in myelodysplastic syndromes. We aim to study splicing defects associated with constitutional pathogenic variants.

  Study EGAS50000001473

• Intellectual Disability cases with parents (trios) or affected sibs (sibpairs)

  Samples from ID cases negative for CNV through array-CGH were submitted to exome sequencing. Families with one affected individual underwent trio exome sequencing for identification of de novo variants. Families with more than one affected child underwent sibpair sequencing for identificatio of shared recessive or x-linked variants.

  Study EGAS00001003968