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• Multiomic profiling of pleomorphic rhabdomyosarcoma

  Rhabdomyosarcoma (RMS) describes rare soft-tissue tumors that exhibit features of skeletal muscle differentiation. The most common subtypes in children are alveolar and embryonal rhabdomyosarcoma, with the alveolar subtype characterized by PAX3/7 fusions. A lesser known and rarer subtype, pleomorphic rhabdomyosarcoma (PRMS), occurs most frequently in adults vetween the ages of 40 and 50. This pleomorphic subtype is often misdiagnosed and little is known about its molecular characterization. Here, we conducted comprehensive genomic, transcriptomic, and methylation profiling of these tumors.

  Study EGAS00001007230

• This study aims to evaluate the relationship between cardiometabolic risk factors and the most common genetic variation (SNPs)

  Comprehensive data on lifestyle-related modifiable factors, sociodemographic, anthropometric, economic, biochemical, and genetic markers related to the occurrence of cardiometabolic diseases as part of the observational cross-sectional survey “2015 Health Survey of Sao Paulo with Focus on Nutrition (2015 ISA-Nutrition)”, a population-based study. Data of 805218 SNPs for 841 individuals was genotyped using the Axiom™ 2.0 Precision Medicine Research Array in the Thermo Fisher Scientific laboratory (Affymetrix Inc, Santa Clara, CA).

  Study EGAS00001007818

• 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

• Transcriptomic predictors of survival for palbociclib + endocrine therapy vs. capecitabine in aromatase inhibitor-resistant breast cancer from GEICAM/2013-02 PEARL

  We examined transcriptomic tumor features associated with survival from GEICAM/2013-02 PEARL, a phase III trial of palbociclib + ET vs. capecitabine in aromatase inhibitor-resistant HR+/HER2- MBC. PAM50 intrinsic subtype predicted PFS differences between palbociclib + ET and capecitabine, and lower B-cell-associated gene expression predicted longer OS with palbociclib + ET vs. capecitabine. These features may help identify HR+/HER2- tumors resistant to further ET-based treatment with CDK4/6 inhibitors.

  Study EGAS00001008177

• Cold Ischemia Study

  This study aimed to evaluate the impact of cold ischemia time on the expression of cancer-related genes, particularly those involved in hypoxia, apoptosis, and epithelial-to-mesenchymal transition (EMT). We performed RNA sequencing on 54 normal colon mucosa samples from nine patients undergoing colorectal cancer surgeries, freezing samples at predefined intervals ranging from 0 to 60 minutes. A total of 44 differentially expressed genes (DEGs) (p < 0.05) were identified when comparing samples frozen immediately (T0) with those frozen after 60 minutes (T5).

  Study EGAS00001008233

• 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

• Single cell RNA sequencing of mononuclear cells from synovial fluid of patients with rheumatoid arthritis

  Mononuclear cells were collected from synovial fluid of anti-citrullinated positive antibodies (ACPA)-positive rheumatoid arthritis patients (n=8) and ACPA-negative RA patients (n=8). Global cell types (i.e., no enrichment) were obtained from these cryopreserved synovial fluid mononuclear cells (SFMC) samples and immediately fixed and processed using the GEM-X Flex Gene Expression Reagent Kits (10x Genomics) according to protocol. Following Gel Bead-in Emulsion (GEM) generation, samples were processed using the standard manufacturer’s protocol. Once sequencing libraries passed standard quality control metrics, libraries were sequenced on an Illumina NextSeq2000 P4 100 cycle reagent kit with the following read structure: R1: 28, R2: 90, I1: 10, I2: 10. Libraries were sequenced to obtain a read depth greater than 10,000 reads/cell for gene-expression (GEX). FASTQ files are made available. More detailed information can be obtained in Argyriou A. et al, Annals of the Rheumatic Disease, 2025.

  Dataset EGAD50000001801

• SweGen whole-genome sequencing from the Northern Sweden Population Health Study

  The dataset contains whole-genome sequencing data (aligned read files) in CRAM-format (lossless compression) for a total of 58 DNA samples originating from the Northern Sweden Population Health Study (NSPHS). For each of the 58 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. The NSPHS study was approved by the local ethics committee at the University of Uppsala (Regionala Etikprövningsnämnden, Uppsala, 2005:325 and 2016-03-09). All participants gave their written informed consent to the study including the examination of environmental and genetic causes of disease in compliance with the Declaration of Helsinki.

  Dataset EGAD50000001325

• SweGen genetic variation from the Northern Sweden Population Health Study

  The dataset contains files with single nucleotide variants in VCF format for a total of 58 DNA samples originating from the Northern Sweden Population Health Study (NSPHS). For each of the 58 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. The NSPHS study was approved by the local ethics committee at the University of Uppsala (Regionala Etikprövningsnämnden, Uppsala, 2005:325 and 2016-03-09). All participants gave their written informed consent to the study including the examination of environmental and genetic causes of disease in compliance with the Declaration of Helsinki.

  Dataset EGAD50000001324

• Single nuclei ATAC-Seq data from the human ganglionic eminences

  Data generated through single nuclei ATAC sequencing on whole ganglionic eminences from 3 human fetuses (two of 16 and one of 17 gestational weeks). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource with ethical approval. snATAC-Seq libraries were prepared from ~8,000 nuclei per sample using Chromium Next GEM Single Cell ATAC (v1.1) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 617 million read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Schizophrenia Bulletin 2024, https://doi.org/10.1093/schbul/sbae083. Please note that 10X generated BAM files, rather than FASTQ files, have been uploded. FASTQ files can be regenerated using the 10X Genomics bamtofastq tool. https://support.10xgenomics.com/docs/bamtofastq

  Dataset EGAD50000000601