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• A human induced pluripotent stem cell toolbox for studying sex chromosome effects -transcriptional landscape

  We use state of the art reprogramming methods to generate panels of isogenic XXY, XX and XY iPSCs from XXY patient fibroblasts. We use CRISPR/Cas9 system to evict Y chromosome from XY cells and generate XO iPSCs. The generation and characterisation of panels of isogenic XXY, XX, XY and XO iPSCs will provide a foundational toolkit to study sex differences in vitro. As iPSCs can be differentiated into any somatic cell type, we can apply the model to any human disease. We have generated bulk RNA-Seq from 12 autosomally isogenic hiPSCs to investigate transcriptional landscape and any differences in those cells in pluripotent state.

  Study EGAS50000000931

• A whole genome analysis of single fetal human stem cells from the liver and the intestine

  Mutations of embryonic and fetal origin have the potential to affect a large proportion of adult cells and may alter cancer predisposition or lead to genetic disease syndromes. We have recently shown that human adult-stem cells progressively acquire approximately 40 novel tissue-specific mutations per year throughout postnatal life. Prenatal mutation rates are as yet unknown. Here we determined genome-wide mutation patterns of single stem cells in human development by sequencing of clonally expanded intestinal and liver organoid cultures of 2nd trimester human foetuses. Our results show that mutation rates in fetal stem cells are significantly higher than in adult stem cells.

  Study EGAS00001002886

• A standardised framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

  Fragmentomic features of cell-free DNA represent promising non-invasive biomarkers for cancer diagnosis. However, a lack of systematic evaluation of biases in feature quantification has hindered the adoption of such applications. We compared features derived from whole-genome sequencing of ten healthy donors using nine library kits and ten data-processing routes, and validated them in 1,182 plasma samples from published studies. Our results clarify the variations resulting from library preparation and feature quantification methods. We designed the Trim Align Pipeline and the cfDNAPro R package as unified interfaces for data pre-processing, feature extraction, and visualisation, aiming to standardise multimodal feature engineering and integration for machine learning.

  Study EGAS00001008051

• Clonal haematopoiesis in patients with AAA (2019-04-03)

  Recent advances in genomics have demonstrated that clonal haemopoiesis driven by leukaemia associated somatic mutations is a relatively common phenomenon that increases in frequency with advancing age. Whilst individuals with clonal haemopoiesis have an increased risk of developing haematological malignancies, they also have an increased mortality from other causes. Additionally, certain mutations are almost exclusively seen in individuals aged 70 years or older, whilst others are seen in individuals with non-haematological cancers including breast and ovarian. Recently, clonal haemopoiesis was found to be associated with a significantly increased risk of atherosclerotic cardiovascular disease. This association is thought to be causative with clonally-derived macrophages showing elevated expression of several chemokine and cytokine genes that contribute to atherosclerosis. Another vascular pathology, abdominal aortic aneurysm (AAA), increases with age and shares risk factors with atherosclerosis (including smoking, male sex, high cholesterol). However, the impact of these risk factors and the overlap between AAA and atherosclerosis is poorly understood. To investigate a possible link between clonal haemopoiesis and AAA, we will study DNA samples from 300 patients with AAA and up to 200 controls for evidence of clonal haemopoiesis. This will be done using target DNA enrichment with biotinylated RNA baits followed by high throughput sequencing. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004895

• TCR- and BCR-sequencing data for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  Each tumor sample was cut into three pieces, yielding two end-pieces for cryovials and a middle portion placed in 10% buffered formalin. End pieces were homogenized manually and with a paddle blender (Stomacher). All paraffin-embedded blocks, including formalin-fixed tumor samples and molecular-fixed fallopian tubes, were sectioned and stained with hematoxylin and eosin prior to expert histopathological review to confirm the presence of high grade serous carcinoma. Homogenized end pieces were then flash frozen, and RNA was extracted using the miRNeasy Mini kit. Nanodrop was used to assess quality (260/280) and quantity. Total RNA samples were also QC checked using the Caliper HT RNA HiSens assay. Samples ranging from 60-255ng RNA were re-arrayed into a 96-well plate. 5'-RACE PCR was carried out as described in "The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer" (Zhang et al.). Briefly, this involved first round and nested PCR with TRB (TCR beta chain) and IGH (immunoglobulin heavy chain) gene-specific primers. The indexed libraries were sequenced on the Illumina HiSeq platform with paired-end 250bp reads using v2 chemistry reagents.

  Dataset EGAD00001003985

• Characterization of mutational signatures in human cancer cell lines reveals episodic APOBEC mutagenesis

  Multiple signatures of somatic mutations have been identified in human cancer genomes. To investigate whether mutational signatures continue to be generated, and if so their temporal patterns of activity, subsets of cell lines were cultured in vitro for extended periods and subjected to single cell cloning and whole genome or exome sequencing or directly to single cell whole genome sequencing. As expected, signatures of past exogenous exposures, such as tobacco smoke and ultraviolet light, were not generated in vitro. In contrast, signatures of normal and defective DNA repair and replication continued to be generated at essentially constant mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing activity exhibited a distinctive pattern with substantial fluctuations in mutation rate over time and episodic bursts of mutations. The initiating factors for these bursts are unclear although retrotransposon mobilisation may play a role. This cell line set now constitutes a comprehensive resource of live experimental models of mutational processes of both known and unknown aetiologies potentially retaining the patterns of activity and regulatory influences operative in human cells in vivo.

  Dataset EGAD00001004201

• Star2xml: metadata converter into XML

  Star2xml: metadata converter into XML Welcome to the landing page for star2xml - a tool developed by the European Genome-phenome Archive (EGA) that enables users to convert metadata into XML format that is compliant with EGA's programmatic submission system. For starters, if you are not sure what metadata is in this context, you may want to explore our brief metadata introduction. . Star2xml is useful for users who have already submitted their data to the EGA and want to also submit their metadata programmatically without having to create the XML files manually. The need for these XMLs containing metadata is explained in the EGA's metadata schemas and programmatic submission guidelines. In summary, star2xml allows for users to deposit metadata in a tabular format (e.g. excel spreadsheet) and transform it into a compliant XML format. This saves time in large submissions, where the sheer size of metadata makes it difficult to manage. For smaller submissions, it is recommended to use EGA's Submitter Portal (SP) instead. The installation of the tool is straightforward, and it contains detailed documentation on how to use it in its GitHub repository . While star2xml can help users convert metadata formats, it does not validate the resulting metadata against EGA's schemas. Therefore, after creating your XMLs, you should still validate your metadata before submitting it to EGA, as described in the documentation for programmatic metadata validation.

  Documentation tools/star2xml

• Whole exome sequencing Data from a child with ALPI deficiency and parents

  This dataset contains raw sequences (BAM files) of P1 trio: mother, father and affected child (P1). Whole exome sequencing (WES).

  Dataset EGAD00001004048

• PromethION (and Illumina) WGS and MinION transcriptome for a patient with diffuse large B-cell lymphoma.

  Dataset EGAD00001006204

• Dataset for CD8-Positive lymphocyte samples

  This dataset contains scRNA sequencing data for CD8-Positive lymphocytes samples. Sequencing was performed on a Illumina NextSeq 550. The sequencing was always paired.

  Dataset EGAD50000000092