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• Human genomic and phenotypic synthetic data for the study of rare diseases

  The purpose of this dataset is to facilitate development of technical implementations for rare disease data integration, analysis, discovery, and federated access. This synthetic dataset includes clinical and genomic data from 6 rare disease cases. It consists of 18 whole genomes (6 index cases with their parents) which have genetic background based on public human data sequenced in the context of the Illumina Platinum initiative (Eberle, MA et al. (2017)) and made available by the HapMap project (https://www.genome.gov/10001688/international-hapmap-project). In each of the cases, real causative variants correlating with the phenotypic data provided were spiked-in. The cases included in this synthetic dataset correspond to the following type of disorders: CASE 1- Congenital myasthenic syndrome (Autosomal Dominant -de novo variant) CASE 2- Macular dystrophy (Autosomal Dominant) CASE 3- Muscular dystrophy (Autosomal Recessive-compound heterozygous variants) CASE 4- Mitochondrial disorder (Autosomal Recessive-consanguineous case - homozygous variant) CASE 5- Breast cancer (Autosomal Dominant) CASE 6- Similar as case 1 for patient matchmaking tests: Congenital myasthenic syndrome (Autosomal Dominant-de novo variant) For each case you will be able to download the following data: clinical information (phenopackets per individual and pedigree per family), raw genomic data (FASTQ and BAMs) and processed genomic data (vcfs). When using the data, the following should be acknowledged: the RD-Connect GPAP (https://platform.rd-connect.eu/), EC H2020 project EJP-RD (grant # 825575), EC H2020 project B1MG (grant # 951724) and Generalitat de Catalunya VEIS project (grant # 001-P-001647).

  Study EGAS00001005702

• RNA-Seq Brest Patient-derived Tumor Organoids

  This dataset includes 14 RNASeq samples from 8 patients. For some patients, organoids at different passages have been profiled. They can be identified by their alias, composed of the following structure: <subjectId>_O<organoid_number>_<passage>_RNA. For example, ICSBCS002_O1_1_RNA indicates the earlier passage of organoid 1 for subject ICSBCS002, and ICSBCS002_O1_2_RNA indicates the later passage. Additionally, WCM2137_O1_RNA and WCM2137_O2_RNA indicate two organoids (O1 and O2) derived from different tissues. More information about the passages and tissues can be found in the sample information table.

  Dataset EGAD50000000960

• Human breast transcriptome analysis

  Obesity is a risk factor for the development of post-menopausal breast cancer and is associated with a worse breast cancer prognosis. Here we carried out transcriptome profiling on nontumorous breast tissue to define the molecular changes that occur related to excess body fat and adipose inflammation. A second goal was to determine if blood biomarkers reflect molecular changes in the breast. Increases in a variety of pathways linked to tumor development and progression were found. Moreover, increased expression of several drug targets including aromatase, the rate-limiting enzyme for estrogen biosynthesis, and PD-1 was observed. Various blood biomarkers that are associated with either elevated risk of breast cancer or worse prognosis were altered and correlated with molecular changes in the breast. Collectively, this study helps to explain both the link between obesity and breast cancer and the utility of blood biomarkers for determining risk and prognosis.

  Study EGAS00001004665

• WGS of 11 MPNSTs, 7 ANNUBPs and 7 blood and normal tissue controls

  Whole-genome sequencing (WGS) of 11 MPNSTs, 7 ANNUBPs and 7 controls (6 blood and 1 normal tissue) sequenced for Magallon-Lorenz, 2026. Sequenced at BGI with DNBseq technology (2x150bp) following standard protocols. Raw fastq files provided.

  Dataset EGAD50000002492

• H3Africa ACEGID Array Phenotype

  Phenotype data for Lassa Fever cases and population controls from Nigeria and Sierra Leone associated with genotype data generated using Illumina H3Africa array version 1.

  Dataset EGAD00001010923

• CancerSEEK ctDNA FASTQ files

  Sequencing data from 1,005 cancer patients and 812 healthy controls. All samples prepared using Safe-SeqS technology and sequenced on an Illumina MiSeq and/or HiSeq instrument. Paired FASTQ files for correspond to read 1 and the index read present (R and I respectively).

  Dataset EGAD00001003931

• SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

  SNV calls generated using the SomaticSniper-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

  Dataset EGAD00001004431

• SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

  SNV calls generated using the SomaticSniper-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

  Dataset EGAD00001004432

• SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

  SNV calls generated using the MuTect-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

  Dataset EGAD00001004433

• SNV vcf files for CPCG Subclonal Heterogeneity in multiple and single regions

  SNV calls generated using the MuTect-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study using single and multiple regions

  Dataset EGAD00001004434