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• Dissecting Autoimmune Cellular and Molecular Networks in Vitiligo

  This study consists of suction blister biopsies of primary human skin samples, collected from healthy patients, or patients with vitiligo. Healthy patients had healthy skin sampled. Vitiligo patients had both unaffected (non-lesional) and affected (lesional) skin sampled. The generated data consists of scRNA-seq samples generated following the inDrops method (Klein et al., 2015; PMID: 26000487).

  Study phs002455

• Bulk RNA and ATACseq of 2 XLP patients and 5-6 HD

  The dataset contains five samples from P1, one pre-HSCT and four post-HSCT, one sample from P2 and 5-6 HD. RNAseq reads were processed using the LUMC BIOWDL RNAseq pipeline v5.0.0 (https://github.com/biowdl/RNA-seq). Genes with log2CPM≥1 in at least 10% of all samples were retained for downstream analysis. Differential gene expression analysis was performed using the dgeAnalysis R-Shiny application (https://github.com/LUMC/dgeAnalysis/tree/v1.4.4). ATACseq reads were processed using the LUMC BIOWDL Chipseq pipeline 1.0.0-dev (https://github.com/biowdl/ChIP-seq).

  Dataset EGAD50000002072

• Long-read whole-genome sequencing-based concurrent haplotype phasing and aneuploidy profiling of single cells

  This dataset contains long-read whole-genome sequencing (lrWGS) data from 14 samples. Five lrWGS data are from single-cell (sc, sc_2, sc_3), multi-cell (mc, 10 cells), and bulk samples of HG002. The remaining nine lrWGS data are from two preimplantation genetic testing (PGT) families, including four from blood bulk DNA of the parental pairs and five from trophectoderm biopsies of two embryos from one family and three embryos from another family. The data are provided in raw FASTQ format and were generated using the PromethION device from Oxford Nanopore Technologies.

  Dataset EGAD50000000787

• WGS data from NEN patient derived tumor organoids (PDTOs) and matched parental tumors - UMCU/NKI

  The dataset includes cram files from WGS of 6 NEN tumors or metastases and matched PDTOs. For all tumors, cram files from WGS of either matched normal tissue or matched blood from the corresponding patients are included. Analysis VCF files are also included in the dataset. The sequencing was done with a NovaSeq 6000 instrument.

  Dataset EGAD00001009989

• Swarm Learning to identify COVID-19, tuberculosis and leukemia patients based on blood transcriptomes

  Identification of patients with life-threatening diseases including leukemias or infections such as tuberculosis or COVID-19 is an important goal of modern precision medicine. However, there is an increasing divide between what is technically possible and what is allowed because of privacy legislation. We have recently illustrated that classical machine learning can identify leukemia patients based on their blood transcriptomes. To facilitate integration of any omics data from any data owner world-wide without violating privacy laws, we here introduce Swarm Learning (SL), a decentralized machine learning approach uniting edge computing, artificial intelligence (AI), blockchain and privacy protection without the need for a central coordinator thereby going beyond federated learning. To illustrate its feasibility, using more than 12,000 transcriptomes from peripheral blood mononuclear cells and more than 2,000 peripheral blood transcriptomes we demonstrate that SL of omics data distributed across different individual sites leads to disease classifiers that outperform those developed at individual sites. Yet, SL completely protects local privacy regulations by design. We propose this approach to noticeably accelerate the introduction of precision medicine.

  Dataset EGAD00001006231

• DAC for study "Single-nucleus brain transcriptomics reveals microglia dysfunction in Multiple System Atrophy"

  Dataset containing snRNA-seq samples from MSA or PD patients, and healthy controls. We aimed at identifying molecular processes at the single cell level that could identify common and/or disease-specific differences between healthy controls and patient groups. Frozen tissue samples from healthy controls, and multiple system atrophy or Parkinson's disease patients were excised and single nuclei were isolated following the 10x Genomics Chromium workflow.

  Dac EGAC50000000809

• ATAC-seq for 2 samples

  This dataset contains ATACseq data from ta primary sample and a patient derived model (PDX) of the novel FOXF1/FENDRR ALL subtype. All the 2 samples are in bam file type.

  Dataset EGAD50000001791

• BIONi010-C-8 / SAMEA4454011 WGS data

  The iPSC line BIONi010-C-8 / SAMEA4454011 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-8 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001028

• SIGi001-A-13 / SAMEA104386250 WGS data

  The iPSC line SIGi001-A-13 / SAMEA104386250 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-13 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001031

• BIONi010-C-3 / SAMEA4342740 WGS data

  The iPSC line BIONi010-C-3 / SAMEA4342740 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-3 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001034