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• BLUEPRINT September 2016, ChIPmentation for conventional dendritic cell from cord blood, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for conventional dendritic cell from cord blood, on Genome GRCh38. 4 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002940

• BLUEPRINT September 2016, ChIPmentation for regulatory T cell from venous blood, on Genome GRCh38

  ChIPmentation data for 2 sample(s) for regulatory T cell from venous blood, on Genome GRCh38. 14 run(s), 9 experiment(s), 9 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002942

• BLUEPRINT September 2016, ChIP-Seq for thymocyte from thymus, on Genome GRCh38

  ChIP-Seq data for 5 sample(s) for thymocyte from thymus, on Genome GRCh38. 17 run(s), 17 experiment(s), 17 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002947

• Genetic data of a monozygotic twin pair discordant for ALS

  We performed whole exome sequencing of a monozygotic twin pair discordant for ALS. This dataset contains two VCF files: one of the healthy twin and one of the ALS twin. Library was prepared according to Agilent SureSelectQXT Kit protocol and processed using Illumina NextSeq 550 sequencer). Fastq files were aligned on the reference human genome hg19 (GRCh37) and, for each patient, a list of variations in a VCF format file (Variant Call Format) was produced by GATK software and annotated by wAnnovar.

  Dataset EGAD50000001329

• Contribution of Retrotransposition to Developmental Disorders

  Variants and WGS data for Gardner et al. 2018 (biorxiv 471375). One VCF each for Alu, L1, and SVA. Flat text file and WGS for processed pseudogenes.

  Dataset EGAD00001004586

• RNA Sequencing datasets - Project "Multi-omics analysis of Parkinson’s disease midbrains"

  The dataset contains FASTQ files referring to the study "Multi-omics analysis of Parkinson’s disease midbrains". For this project, RNA was isolated from human postmortem midbrain tissue (PD and Control samples). Libraries were prepared with the TruSeq Small RNA library prep (Small RNA Seq) and the TruSeq Stranded Total RNA Kit (for transcriptomics), both from Illumina. Sequencing for both experimental setups was conducted in the Illumina HiSeq4000.

  Dataset EGAD00001006883

• 300BCG study ATAC-seq data: human population variation of trained immunity

  ATAC-seq dataset for the paper: Title Multi-omics analysis of human population variation in immune function and in vivo response to BCG vaccination Abstract Immune responses are tightly regulated, yet highly variable between individuals. To investigate human population variation of trained immunity, we immunized healthy individuals with Bacillus Calmette-Guérin (BCG). This live attenuated vaccine induces not only an adaptive immune response against tu-berculosis, but also triggers innate immune activation and memory. We established personal immune profiles and chromatin accessibility maps over a time course of BCG vaccination in 323 individuals. This large resource uncovered genetic and epigenetic predictors of baseline immunity and BCG vaccine response. We found that BCG vaccination enhances the innate immune response only in individuals with dormant immune states at baseline, suggesting that exogeneous induction of trained immunity is not a universal booster of innate immunity, but specifically elevates weak innate immune responses. This study advances our understanding of BCG’s heterologous immune-stimulatory effects and trained immunity in humans. Moreover, our results highlight the value of epigenetic cell states as an “endo-phenotype” that connects immune function with genotype and the environment.

  Dataset EGAD50000000123

• Somatic mutation and clonal evolution normal breast tissue WGS

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >70 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumour development. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010123

• Neuroblastoma patient Total RNA Seq data

  Tumor Total RNA Seq data of primary neuroblastomas. This is an update of the „Berlin Neuroblastoma Dataset” (EGAS00001004022). This data was used for the analysis of circular RNA expression and regulation in neuroblastoma.

  Dataset EGAD00001008124

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006641