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• Whole genome sequencing in prime-edited human organoids

  We performed whole genome sequencing to detect possible off-target mutations induced by prime editing. Liver organoids, derived from a healthy control, were transfected with either control (GFP) plasmids or prime editing plasmids (GFP+PE2+pegRNA+nickRNA) to induce a 6-bp deletion in CTNNB1. One control and two prime-edited organoid lines were clonally expanded from single cells. High-throughput sequencing was performed on the complete genomic DNA isolated from these clonal lines, as well as the starting culture (bulk). After correction for germline mutations in the starting culture, new mutations in the control and prime-edited lines were compared. The same approach was followed in small intestinal organoids, derived from a patient with disease-causing 3-bp deletion in DGAT1. In these small intestinal organoids, prime editing was used to insert the 3 missing nucleotides. Two corrected clones were compared to one control clone.

  Dataset EGAD00001006352

• Single nuclei RNA-Seq from 5 regions of the human fetal brain

  Data generated through single nuclei RNA sequencing on 5 regions of the brain (frontal cortex, ganglionic eminence, hippocampus, thalamus and cerebellum) from 3 fetuses (two of 14 and one of 15 post-conception weeks, all female). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) with ethical approval. snRNA-seq libraries were prepared from ∼10,000 nuclei from each sample using Chromium Single Cell 3ʹ (v3) 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 865 million (median = 1.01 billion) read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Biological Psychiatry 2022, https://doi.org/10.1016/j.biopsych.2022.06.033.

  Dataset EGAD00001009303

• 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 EGAD00001015713

• OSTEOMICS_RNA

  RNA sequencing of 79 libraries were prepared, from sample of Osteosarcoma tumors biopsied at diagnosis, with TruSeq Stranded mRNA kit following recommendations: the key steps consist of PolyA mRNA capture with oligo dT beads using 1µg total RNA, fragmentation to approximately 400pb, DNA double strand synthesis, and ligation of Illumina adaptors amplification of the library by PCR for sequencing. Libraries sequencing was performed using Illumina sequencers (NextSeq 500 or Hiseq 2000/2500/4000) in 75 bp paired-end mode.

  Dataset EGAD00001008213

• Spatial multi-omic map of human myocardial infarction

  We applied an integrative single-cell genomics strategy with single nucleus RNA sequencing (snRNA-seq) and single nucleus Assay for Transposase-Accessible Chromatin sequencing (snATAC-seq) together with spatial transcriptomics from the same tissue mapping human cardiac cells in homeostasis and after myocardial infarction (MI) at unprecedented spatial and molecular resolution. We profiled in total 31 samples from 23 patients including four non-transplanted donor hearts as controls and samples from tissues with necrotic tissue areas (ischemic zone, IZ), border zone (BZ), and the non-affected left ventricular myocardium (remote zone, RZ) of patients with acute MI.

  Dataset EGAD00001008952

• Methylation and nucleosome occupancy studies on cell-free DNA using enzymatic cytosine conversion

  Raw sequencing data (PE, fastq.gz) from NovaSeq 6000 sequencing runs of: 1. Blood-derived cell-free DNA from six healthy controls, enzymatic cytosine conversion (between 1 and 3 replicates each) 2. Urine-derived cell-free DNA from three healthy controls, enzymatic cytosine conversion (between 1 and 3 replicates each) 3. Blood-derived cell-free DNA from six patients with acute or chronic kidney disease with/without other relevant organ dysfunction, enzymatic cytosine conversion (between 1 and 3 replicates each) 4. Urine-derived cell-free DNA from three patients with acute kidney disease, enzymatic cytosine conversion (between 1 and 3 replicates each) 5. Blood-derived cell-free DNA from three healthy controls, bisulfite cytosine conversion (single datasets) 6. Conventional whole-genome sequencing on genomic DNA of two healthy kidney donors for two of the studied patients (single datasets).

  Dataset EGAD00001006072

• cfMethyl-Seq

  cfMethyl-Seq libraries were generated for 479 cfDNA samples and were sequenced with 150 bp paired-end reads.

  Dataset EGAD00001009003

• Roche Alzheimer's dataset

  The Roche Alzheimer’s disease dataset (Roche_AD) consists of 80 samples from 40 unique individuals (one sample from the temporal cortex and one from deep white matter for each individual, 12 cases, 25 controls, 3 dementia). A total of 12,000 estimated cells from each sample were loaded on the 10x Single Cell Next GEM G Chip. cDNA libraries were prepared using the Chromium Single Cell 3’ Library and Gel Bead v3 kit according to the manufacturer’s instructions. cDNA libraries were sequenced using the Illumina NovaSeq 6000 System and NovaSeq 6000 S2 Reagent Kit v1.5 (100 cycles), aiming at a sequencing depth of minimum 30K reads/nucleus.

  Dataset EGAD00001009166

• Single-cell RNA sequencing of SarBC-01 treated with Dexamethasone vs DMSO, with or without Matrigel.

  This dataset contains raw FASTQ files from single cell RNA sequencing of SarBC-01 cells treated with Dexamethasone vs DMSO, with or without Matrigel, processed with MULTI-seq. Cells from 4 different culture conditions (+Mat/Dex, +Mat/DMSO, -Mat/Dex, -Mat/DMSO) were harvested, processed for multiplexing using the MULTI-seq protocol and loaded in a Chromium Single Cell 3ʹ GEM Library and Gel Bead Kit v3 (10x Genomics). Gene expression (cDNA) and MULTI-seq libraries were prepared according to the manufacturers’ protocol of Chromium Next GEM Single Cell 3’ reagents Kits v3.1 (Dual Index). Finally, cDNA and MULTI-seq libraries were analyzed using an Agilent Bioanalyzer (DNA High Sensitivity kit) and sequenced on a NovaSeq6000 (S2 flow cell) platform. MULTISEQ BARCODES: TTAGCCAG => Matrigel/DMSO CCACAATG => Matrigel/Dexamethasone GCACACGC => noMatrigel/DMSO AGAGAGAG => noMatrigel/Dexamethasone

  Dataset EGAD00001011155

• Garvan/St Vincent’s Prostate Cancer Tissue and Data

  The cohort (n=53) consists of prostate cancer patients from Australia. For each patient, a pair of blood and tumour samples were collected. The sequencing data was mapped to hg38 reference. Blood BAMs are named with “-B” as suffix and tumour BAMs are named with “-T” as suffix.

  Dataset EGAD00001009066