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• SUM-seq data for spontaneous differentiation of iPSCs upon perturbation of GATA2, NR4A2 or SOX17

  We combined SUM-seq with arrayed CRISPR screening, modulating the expression of key lineage transcription factors (TFs) (GATA2 - mesoderm, SOX17 - endoderm, and NR4A2 - neuroectoderm) in hiPSCs via CRISPR interference (CRISPRi) or activation (CRISPRa) over a time course of spontaneous differentiation (days cultured in vitro: 0, 4, 12, and 18). This totalled to 54 samples (4 day/time points x 3 target TFs x 2-3 gRNAs per target x CRISPRi/a). Single-cell chromatin accessibility and gene expression data is provided as demultiplexed fastq files.

  Dataset EGAD50000001205

• A single-cell atlas of the early COPD lung

  Single cell atlas of the human airways from 10 patients suffering of early stage Chronic Obstructive Pulmonary Disease and 12 healthy age matched volunteers. This dataset was sequenced by 10X Genomics 3’ RNA-seq profiling. It is composed of more than 400 000 cells coming from 119 samples total. Sampling was performed by brushings and biopsies from the nose to the 6 th division of the airways.

  Dataset EGAD50000001001

• scRNA-seq dataset, RCC

  scRNA-seq dataset for the study "Surgery in combination with immune checkpoint therapy as an effective treatment for patients with metastatic cancer." The dataset comprises 38 samples from 19 patients, with each pair includes a baseline (BL) sample and a post-biopsy or post-surgery sample. Each sample corresponds to an R1 (read 1) and an R2 (read 2) files (.fastq.gz) for paired reads. Beside procedure (biopsy or surgery), another important phenotype is response (PR and PD in this case, no SD for these patients), included in the description of the samples. The sequencing was performed using Illumina NovaSeq 6000 platform., as seen in the experiment description.

  Dataset EGAD50000000566

• Single cell whole genome sequencing of luminal breast epithelial cells from wildtype and BRCA mutation carriers

  Single cell whole genome sequencing was done using DLP+ (https://doi.org/10.1016/j.cell.2019.10.026) on luminal breast epithelial cells from wildtype and BRCA mutation carriers. Each BAM file is a merged BAM from single cells from a single sample, and the cells can be uniquely identified by their @RG group. Only high quality cells were kept, thus there are large differences in BAM sizes. The same sample/patient can be found across multiple BAM files to accumulate more cells, sometimes the same patient will have multiple FACS sorted cell types also split by BAMs.

  Dataset EGAD50000000883

• LLDeep DAG2+ scRNA-seq in PBMCs

  Single cell transcriptomics of PBMCs of 47 donors from the Lifelines Deep cohort (general population, Northern part of the Netherlands). Cells of five or six different donors were pooled together in one sample pool, resulting in eight different sample pools. In total, 28.855 cells were captured and their transcriptomes were sequenced to an average depth of 74k. Genotype data was available for each donor, which allowed us to use the Demuxlet method that uses variable SNPs between the pooled individuals to determine which cell belongs to which individual. Since genotype information is lacking of 2 individuals, the transcriptome of only 45 individuals could be retrieved.

  Dataset EGAD00010001315

• Whole-exome sequencing of 20 samples of actinic keratosis (10s) and cutaneous squamous cell carcinoma (10s)

  Whole-exome sequencing of 20 samples of actinic keratosis (10) and cutaneous squamous cell carcinoma (10) was performed to investigate a potential relationship between DNA methylation-based subtypes and genetic mutation patterns. 7 samples were shown to belong to the stem cell-like subclass (4 AK and 2 SCC), 12 - to the keratinocyte-like subtype (6 AK and 6 SCC) and one SCC sample is unclassified (was not included in the methylation analysis). Exome regions were captured using Agilent Low Input Exome-Seq Human v5 kit and sequenced on Illumina Hiseq4000 with paired-end 100-nucleotide reads.

  Dataset EGAD00001003765

• Detection of clinically relevant genetic and transcriptomic landscape in DLBCL uniformly treated by R-CHOP

  Recent studies using next-generation sequencing strategies have described the landscape of genetic alterations in diffuse large B-cell lymphoma (DLBCL). However, little is known about the clinical relevance of recurrent mutations and copy number alterations and their transcriptional footprints. This study examines the frequency, interaction and clinical impact of recurrent genetic aberrations in DLBCL using high-resolution technologies in a large population-based cohort.

  Dataset EGAD00001003783

• The British Autozygosity Populations BioResource (2018-06-06)

  This data set contains whole exome sequences of individuals with self-stated parental relatedness from the East London Genes & Health cohort. Rare frequency functional variants in these healthy individuals will be studied with respect to the genetic health of the participants and loss-of-function analysis of human genes. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2018-06-06.

  Dataset EGAD00001004150

• Adeno-associated virus in the liver: natural history and consequences in tumor development

  Adeno-associated virus (AAV) is a defective mono-stranded DNA virus, endemic in human population (35-80%). Recurrent clonal AAV2 insertions are associated with the pathogenesis of rare human hepatocellular carcinoma (HCC) developed on normal liver. This study aimed to characterize the natural history of AAV infection in the liver and its consequence in tumor development. In silico analyses using viral capture data explored viral variants and new clonal insertions. Clonal AAV insertions were positive selected during HCC development on non-cirrhotic liver challenging the notion of AAV as a non-pathogenic virus.

  Dataset EGAD00001004484

• Chordoma Sequencing Project Whole Genome

  This is a continuation of the Chordoma Sequencing Project. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. RNA Sequencing/Methylation and SNP6 and an additional sequencing of three cancer cell lines will be added to this work.

  Dataset EGAD00001000721