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• WES

  Genomic DNA was extracted from PBMCs and whole blood using the Chemagic Prime DNA Blood 4k kit. DNA quality and integrity were assessed by Qubit and Tapestation, and only samples with sufficient quantity, DIN > 6, and confirmed sex were used. Whole-exome libraries were prepared with the SureSelect XT Human All Exon V8 kit (Agilent), covering all human protein-coding regions. DNA was fragmented, adapter-ligated, captured, and amplified following the manufacturer’s protocol. Libraries were quantified, pooled (95 samples), and sequenced on an Illumina NovaSeq 6000 using S4 flow cells, generating up to 12 billion paired-end reads per run.

  Dataset EGAD50000002037

• Research for biological features by gene expression analysis and biomarkers at diagnosis/therapeutics in lung cancer

  WGS, WES, ATAC-seq and methylation analysis with DNA harvested from lung cancer organoids established from surgery, biopsy, pleural effusion, sputum and blood samples of patients. RNA-seq analysis with RNA harvested from lung cancer organoids established from surgery, biopsy, pleural effusion, sputum and blood samples of patients.

  Study JGAS000610

• Research for biological features by gene expression analysis and biomarkers at diagnosis/therapeutics in lung cancer

  WGS, WES, ATAC-seq and methylation analysis with DNA harvested from lung cancer organoids established from surgery, biopsy, pleural effusion, sputum and blood samples of patients. RNA-seq analysis with RNA harvested from lung cancer organoids established from surgery, biopsy, pleural effusion, sputum and blood samples of patients.

  Study JGAS000609

• Research for biological features by gene expression analysis and biomarkers at diagnosis/therapeutics in lung cancer

  WGS, WES, ATAC-seq and methylation analysis with DNA harvested from lung cancer organoids established from surgery, biopsy, pleural effusion, sputum and blood samples of patients. RNA-seq analysis with RNA harvested from lung cancer organoids established from surgery, biopsy, pleural effusion, sputum and blood samples of patients.

  Study JGAS000557

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015710

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015717

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015719

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015711

• Lung Cell Atlas: Paediatric RNA (2025-10-02)

  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 . This dataset contains all the data available for this study on 2025-10-02.

  Dataset EGAD00001015722

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015715