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• English Longitudinal Study of Ageing Genome-wide genotyping using the Illumina HumanOmni2.5-8

  These data are for a Genome Wide Association Study (GWAS) in the English Longitudinal Study of Ageing (ELSA, www.ifs.org.uk/elsa), building on the existing ELSA DNA Repository (EDNAR). This will establish a valuable resource for UK and international scientists, giving them access to GWAS genotyping data. Phenotype data, available on request, includes measures of personality, attitudes, behaviours as well as detailed social and economic outcomes; high quality biomarkers and other intermediate phenotypes; a range of more distal phenotypes, such as direct assessments of health (for example, hypertension, diabetes, muscle strength and cognitive function), and the opportunity to analyse existing biological samples for additional biomarkers, including metabolomic studies. Importantly, this resource would be matched with a near identical resource established in the United States for the Health and Retirement Study (HRS), giving the potential for high quality replication studies and comparative analyses.

  Study EGAS00001001036

• Bayesian-Based Noninvasive Prenatal Diagnosis of Single-Gene Disorders

  In the last decade, non-invasive prenatal diagnosis (NIPD) has emerged as an effective procedure for early detection of inherited diseases during pregnancy. This technique is based on using cell-free DNA (cfDNA) and fetal cfDNA (cffDNA) in maternal blood, and hence, has minimal risk for the mother and fetus compared with invasive techniques. NIPD is used today for identifying chromosomal abnormalities (in some instances) and for single-gene disorders (SGDs) of paternal origin. However, for SGDs of maternal origin, sensitivity poses a challenge that limits the testing to one genetic disorder at a time. Here we present a Bayesian method for the NIPD of monogenic diseases that is independent of the mode of inheritance and parental origin. Furthermore, we show that accounting for differences in the fragment length distribution of fetal- and maternal-derived cfDNA results in increased accuracy. Our model is the first to predict inherited insertions-deletions (indels). The method described can serve as a general framework for the NIPD of SGDs; this will facilitate easy integration of further improvements. One such improvement that is presented in the current study is a machine learning model that corrects errors based on patterns found in previously processed data. Overall, we show that next generation sequencing (NGS) can be used for the NIPD of a wide range of monogenic diseases, simultaneously. We believe that our study will lead to the achievement of a comprehensive NIPD for monogenic diseases. (Reprinted from Bayesian-based noninvasive prenatal diagnosis of single-gene disorders, with permission from Genome Research)

  Study phs001659

• Comprehensive assay for the molecular profiling of cancer by target enrichment from formalin-fixed paraffin-embedded specimens

  Tumor molecular profiling is becoming a standard of care for patients with cancer, but the optimal platform for cancer sequencing remains undetermined. We established a comprehensive assay, the Todai OncoPanel (TOP), which consists of DNA and RNA hybridization capture-based next-generation sequencing panels. A novel method for target enrichment, named the junction capture method, was developed for the RNA panel to accurately and cost-effectively detect 365 fusion genes as well as aberrantly spliced transcripts. The TOP RNA panel can also measure the expression profiles of an additional 109 genes. The TOP DNA panel was developed to detect single nucleotide variants and insertions/deletions for 464 genes, to calculate tumor mutation burden and microsatellite instability status, and to infer chromosomal copy number. Clinically relevant somatic mutations were identified in 32.2% (59/183) of patients by prospective TOP testing, signifying the clinical utility of TOP for providing personalized medicine to cancer patients.

  Study JGAS000164

• Feasibility study of enzymatic methylation sequencing of cell-free DNA from cerebrospinal fluid of pediatric brain tumors for classification

  Array-based DNA methylation profiling is the gold standard for molecular classification of brain tumors. However, it relies on significant amount of input DNA extracted from surgical tissue, thus limiting its use for tumors where biopsy is challenging or limited in quantity. Cell-free tumor DNA (cfDNA) in cerebrospinal fluid (CSF) presents alternative opportunities for brain tumor diagnosis and disease monitoring following treatment. Novel enzymatic DNA methylation sequencing (EM-seq) methods may allow us to overcome input DNA limitations and accurately quantify methylation from cfDNA for tumor classification.

  Study EGAS50000000871

• High-resolution analysis for urinary DNA jagged ends

  High-resolution analysis for urinary DNA jagged ends

  Study EGAS00001005603

• Genomic-Enabled Medicine for Recurrent Glioblastoma

  In this prospective study, we performed genome-wide tumor/normal exome sequencing and tumor RNA-sequencing for recurrent glioblastoma patients. A subset of patients had both enhancing tumor and non-enhancing tissue sequenced to investigate spatial heterogeneity of this disease. Together, this information builds our understanding of the genomic underpinnings of glioblastoma, and contributes toward the knowledge base for identifying and developing more effective treatments for patients with glioblastoma.

  Study phs001460

• Kidney Two-Hit Mapping

  Germ-line genetic variants identified thus far generally account for only part of the genetic risk predicted for most cancers. A component of the remaining risk may be explained by functionally consequent genetic variants that are individually very rare (or private to that individual's family). While their identification may be highly informative for cancer etiology and biological knowledge, strategies that allow for agnostic (genome-wide) identification of such genes are not straight forward. This is particularly true for rare cancers where sufficient numbers of patients may simply not be available for appropriate statistically powered studies. In this project we have explored a study design based around the concept of "two-hit mapping" using the co-occurrence of germ-line and somatic mutations in the same gene to assist in the identification of susceptibility genes. The dataset includes 54 kidney cancer patients selected for enrichment of genetic disease, that is patients with: early age of onset and/or family history and/or bilateral disease. Germ-line and somatic (kidney cancer) tumor sequencing was carried out. These data may improve our understanding of kidney cancer.

  Study phs001971

• Chromatin segmentation of myometrium and UL subclasses

  Histone modification ChIP-seq for chromatin state annotations of myometrium and UL subclasses. Altogether 5 analyses and 210 runs. Includes fastq files; both ChIP and Input for each sample. Some Inputs are used for multiple ChIP experiments. ChIP-seq alignment files for trimmed, mapping q20 and nonredundant reads; both ChIP and Input for each sample. Software: Trim Galore v0.6.7; Bowtie 2 v2.5.0; samtools v1.6

  Dataset EGAD50000001443

• Dataset for the manuscript of Scywalker: scalable end-to-end data analysis workflow for nanopore single-cell transcriptome sequencing

  Dataset for the manuscript Scywalker: scalable end-to-end data analysis workflow for nanopore single-cell transcriptome sequencing. Contains fastq files for 4 brain samples obtained from short-read NovaSeq 6000 v1.5 Illumina and long-read Oxford Nanopore PromethION sequencing. Single-cell suspensions were generated using 10x Genomics Chromium Next GEM Single Cell 3'Kit v3.1

  Dataset EGAD50000000768

• MethylScan data from tissue samples

  Raw data (fastq files) for tumor/normal paired samples (378 samples in total; 78, 58, 29, 24 pairs from liver, lung, ovary, and stomach cancer patients, respectively) profiled with the MethylScan assay, a low cost assay for profiling methylation. The MethylScan assay is designed for cfDNA methylome sequencing that enriches for the disease-associated DNA by depleting background signal. For solid tissues, the assay was performed without the MSRE digestion step.

  Dataset EGAD00001015685