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• Bulk RNAseq FASTQ files of three PDAC organoid lines treated with LGK974 or DMSO for 24h

  This dataset contains raw FASTQ files from bulk RNA sequencing of three patient-derived pancreatic ductal adenocarcinoma (PDAC) organoid lines (P28, P40, P47). Each organoid line was treated with either the WNT secretion inhibitor LGK974 or DMSO for 24 hours, with three biological replicates per treatment condition. RNA was extracted using the Qiagen QiaSymphony SP system, and libraries were prepared with the Illumina Truseq stranded polyA kit. Sequencing was performed on an Illumina NextSeq2000 platform using single-end 50bp reads. Quality control was conducted with FastQC, and reads were trimmed with TrimGalore as appropriate. Data are controlled-access and intended for transcriptomic analysis of WNT pathway perturbation in PDAC organoid models.

  Dataset EGAD50000002219

• scMethylation data of 5 regionally sampled GBM tissue for 2 patients

  This dataset contains snRNA-seq data of 5 regionally sampled GBM tissue (peritumoral region, tumor edge, and tumor core). Regionally sampled GBM patient tissue was dissociated and nuclei were processed in an unbiased manner without any sorting procedure. Nuclei dissociation was performed following the nuclei isolation for single-cell ATAC-seq (10x Genomics; CG000169) with matched peri-tumoral and tumor core samples. Subsequent single-cell methylation sample preparation followed Scale Biosciences single-cell methylation kit protocol v1.0. mplification adaptors through ligation and adding a second barcode though indexed PCR reaction following Scale Biosciences single-cell methylation kit protocol v1.0. We employed the TWIST human methylome panel for targeted enrichment of informative methylation sites.

  Dataset EGAD50000001837

• Developing somatic copy number and mutation calling tools for a bespoke sequencing platform

  We previously developed a linked-read sequencing platform (DigiPico) for analysing whole cancer genomes from picogram quantities of tumour DNA. The aim of this study was to develop and evaluate the specialised computational approaches required to obtain clinically useful results from the raw data. To this end, we performed matched DigiPico, bulk tumour and germline WGS on samples from four patients.

  Study EGAS00001007195

• Detection of cancer cell transcriptomes

  Single cell transcriptomes, generated using chromium 10X 3' sequencing, for two tumour types (AT/RT, and Ewing's sarcoma). For each individual, tumour and normal whole genome sequencing was also obtained using Illumina short read sequencing to an average depth of 30X. These data were used to validate the accuracy of a method for identifying cancer cell transcriptomes based on the allelic shift produced by copy number changes.

  Dataset EGAD00001009005

• Whole exome and genome sequencing for normal endometrial glands

  The raw fastq files for 30 whole exome and 30 whole genome sequencing for normal endometrial glands. The paired-end sequencing data sets (R1 and R2) are deposited.

  Dataset EGAD00001008377

• Exome sequencing of a Novel Primary T Cell Immunodeficiency Kindred (2019-08-19)

  Primary T cell immunodeficiency disorders have a heterogeneous genetic basis. This study will focus on one case characterised by severe T cell lymphopenia in the index case. We aim to sequence the complete exomes of this individual, her three unaffected siblings and parents in an effort to identify the causative genetic mutation responsible for this disorder. We will perform exome capture using Agilent SureSelect system, followed by sequencing on the HiSeq platform. Our study has the potential to uncover genes important for T cell development and novel therapeutic strategies to treat T cell immunodeficiencies. . This dataset contains all the data available for this study on 2019-08-19.

  Dataset EGAD00001005263

• MYOSEQ

  The MYOSEQ project focuses on the application of next generation sequencing, in particular whole exome sequencing (WES), in a large cohort of patients with unexplained limb‐girdle weakness (LGW). Focusing on undiagnosed patients with a clearly defined clinical phenotype enables increased diagnostic rates for known genes (in particular Pompe disease, GNE related pathologies and other known LGMD subtypes) in this cohort, while the use of WES provides scope both for new gene discovery and for additional research into disease modifiers and genotype‐phenotype correlation with substantial cost effectiveness. The LGW patient cohort was collated by Newcastle University in collaboration with clinical centers across Europe. The sequencing was performed at the Broad Institute and jointly analyzed with Newcastle University.

  Dataset EGAD00001006158

• DAC for achalasia risk consortium (arc)

  Dac EGAC00001000394

• DAC for aflatoxin project Qidong patient samples

  Dac EGAC00001000679

• DAC for the cfSort study (tissue deconvolution)

  Dac EGAC00001003222