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• WGS of high grade serous ovarian tumours and matched blood normals

  FASTQ reads for 81 matched tumour-normal WGS pairs for high grade serous ovarian cancer patients. Scottish HGSOC samples were collected via local Bioresource facilities at Edinburgh, Glasgow, Dundee and Aberdeen and stored in liquid Nitrogen until required. HGSOC patients were determined from pathology records and were included in the study where there was matched tumour and whole blood samples. Tumour samples were divided into two for DNA and RNA extraction and slivers of tissue were taken, fixed in formalin and embedded in paraffin wax (FFPE). Samples were only included if they were confirmed as HGSOC and there was greater than 40% tumour cellularity throughout the tumour, determined using H&E staining of the FFPE sections and pathology review. Somatic DNA was extracted from the tumour and germline DNA was extracted from whole blood. Somatic DNA was extracted using the Qiagen DNeasy Blood and tissue kit (cat no 69504). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including RNase digestion step). Germline DNA was extracted from 1-3ml whole blood using the Qiagen FlexiGene kit (cat no 51206) following the manufacturers recommended protocol. The resulting DNA underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as surrogate measures of DNA purity. A260/280 had to be 1.8 or greater and A260/230 had to be 2.0 or greater. Then, DNA was quantified using LifeTechnologies Qubit dsDNA BR kit (cat no Q32850) and we required a minimum of 50ul at 25ng/ul for WGS. Thirdly, DNA was diluted to 25ng/ul and a representative sample was loaded onto a 0.8% TAE gel, ran at 100v for 60mins and then imaged using a BioRad ChemiDoc imaging system to visualise the DNA quality.

  Dataset EGAD00001009049

• WGS of high grade serous ovarian tumours and matched blood normals

  FASTQ reads for 34 matched tumour-normal WGS pairs for high grade serous ovarian cancer patients. Scottish HGSOC samples were collected via local Bioresource facilities at Edinburgh, Glasgow, Dundee and Aberdeen and stored in liquid Nitrogen until required. HGSOC patients were determined from pathology records and were included in the study where there was matched tumour and whole blood samples. Tumour samples were divided into two for DNA and RNA extraction and slivers of tissue were taken, fixed in formalin and embedded in paraffin wax (FFPE). Samples were only included if they were confirmed as HGSOC and there was greater than 40% tumour cellularity throughout the tumour, determined using H&sE staining of the FFPE sections and pathology review. Somatic DNA was extracted from the tumour and germline DNA was extracted from whole blood. Somatic DNA was extracted using the Qiagen DNeasy Blood and tissue kit (cat no 69504). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including RNase digestion step). Germline DNA was extracted from 1-3ml whole blood using the Qiagen FlexiGene kit (cat no 51206) following the manufacturers recommended protocol. The resulting DNA underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as surrogate measures of DNA purity. A260/280 had to be 1.8 or greater and A260/230 had to be 2.0 or greater. Then, DNA was quantified using LifeTechnologies Qubit dsDNA BR kit (cat no Q32850) and we required a minimum of 50ul at 25ng/ul for WGS. Thirdly, DNA was diluted to 25ng/ul and a representative sample was loaded onto a 0.8% TAE gel, ran at 100v for 60mins and then imaged using a BioRad ChemiDoc imaging system to visualise the DNA quality.

  Dataset EGAD00001010135

• DAC for the "Study on the proliferation history of colorectal adenomas"

  Dac EGAC00001000209

• Olink Explore Protein Expression

  Serum samples (DC, CRSsNP, CRSwNP, N-ERD, n=20 each) were subjected to the Olink Explore 3072 analysis including the following panels: Olink Explore 384 Cardiometabolic and Cardiometabolic II, Olink Explore 384 Inflammation and Inflammation II, Olink Explore 384 Neurology and Neurology II, Olink Explore Oncology and Oncology II. The latter had 4 failed samples. From the originally 2925 unique proteins determined, 84 proteins had missing values in all samples and were removed. Further 164 proteins had >50% of values below LOD across all four groups and were removed with remaining values below threshold adjusted to LOD. This data cleaning left 2695 unique assays (2677 unique proteins) in serum to be analysed. Additionally, six assays (LMOD1, IDO1, SCRIB, CXCL8, IL6, TNF) were measured four times each in different panel.

  Dataset EGAD50000001327

• Hybrid untargeted and targeted RNA sequencing facilitates genotype-phenotype associations at single-cell resolution

  Raw sequencing data for the manuscript "Hybrid untargeted and targeted RNA sequencing facilitates genotype-phenotype associations at single-cell resolution". It includes PacBio long-read scRNA-seq, illumina short-read scRNA-seq and Twist-based targeted scRNA-seq datasets for two adrenal samples.

  Study EGAS50000001537

• RNAseq of 12q-amplified osteosarcomas

  RNA-seq of 12q-amplified osteosarcomas for detection of gene fusions and gene expression analysis. RNA-seq was used to look for novel gene fusions and promoter swapping events, and study the expression levels of identified 3' partners. Additionally, global gene expression patterns were used to separate cases into clusters.

  Study EGAS50000000494

• January 2018 data update (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  January 2018 data update (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001003962

• Aligned whole genome bisulfite sequencing data for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Aligned whole genome bisulfite sequencing data for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001435

• February 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  February 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001006220

• An Omics View of Asthma through Monozygotic Twins

  The etiology of asthma involves both genetic and non-genetic factors. We performed whole transcriptome sequencing on monozygotic twins discordant or concordant for asthma (with concordant healthy twins as controls), and identified multiple potential transcriptomic profiles associated with the asthma phenotype.

  Study phs000886

• Kids First: Genetics of Kidney and Urinary Tract Malformations

  Congenital defects of the kidney and urinary tract are a common cause of kidney failure in children and adults and elucidation of the genetics of these disorders will provide new opportunities for diagnosis, risk stratification and prevention of complications.

  Study phs002162

• Comprehensive molecular and clinicopathological profiling of desmoid tumors

  Previous studies have not clearly identified a prognostic factor for desmoid tumors (DT). Whole-exome sequencing and/or RNA sequencing were performed in 64 cases of DT to investigate the molecular profiles in combination with the clinicopathological characteristics.

  Study JGAS000270

• 10x Genomics BCR Sequencing

  BCR sequencing done with 10x Genomics V(D)J kit + platform for the paper: Integrated single cell analysis reveals co-evolution of malignant B cells and tumor micro-environment in transformed follicular lymphoma. Dataset contains paired FASTQ files for 35 samples, each was processed with the 10x Genomics V(D)J kit to obtain the sequence of the B-cell receptor sequence.

  Dataset EGAD50000001373

• Low-input RNA-seq libraries from FFPE samples using TaKaRa SMARTer kit

  Using the TaKaRa SMARTer Stranded Total RNA-Seq Kit v2, RNA-seq libraries were generated from 5 ng of RNA extracted from FFPE tissue. A low-input workflow was applied with 5 PCR cycles for the first amplification and 16 for the second. Library quality was assessed by Bioanalyzer and Qubit, and libraries were sequenced (2×150 bp) on the Illumina NextSeq 550 platform.

  Dataset EGAD50000001552

• Evaluation_of_size_selection_on_cancer_specific_sequencing_libraries

  A couple of previously characterized and sequenced libraries will be repeated using a couple of differing size selection criteria and skim sequenced using an Illumina HiSeq. The resulting sequence will be analyzed to determine the optimal DNA library size for our specific downstream analysis.

  Study EGAS00001000293

• GWAS data (Illumina 2.5 M SNPs) in Cuban cohorts of dengue disease

  We will have 274 individuals typed for the Illumina Human Omni 2.5 chip. The individuals are from two locations in Cuba (Havana and Guantanamo) and from four phenotype classes (asymptomatic, control dengue fever and dengue hemorrhagic fever).

  Study EGAS00001002276

• Anaplastic Thyroid Cancer somatic variants (MuTect)

  Sequence was aligned to the GRCH38 reference genome. Aligned sequence was analyzed with GATK/MuTect, to generate somatic variant calls across the SureSelect All Exon V5+UTR target region. Somatic variant calls are in VCF format. In total there are 166 tumour samples, 94 of which have a matched normal. Somatic variants for tumours without a matched normal, were called against a panel of normals. Details for the mutect call can be found in the vcf header.

  Dataset EGAD00001004129

• Whole genome sequencing of Xeroderma Pigmentosum leukemias samples

  In the current study we report for the first time the unique collection of 6 leukemias and two sarcomas from XP-C. Comprehensive WGS-based mutational analysis provides genetic explanation for the increased incidence of leukemia in XP-C and describes an unique mutational process in internal tumors associated with NER deficiency. Raw data are provided in FASTQ format and variant analysis as VCF files.

  Dataset EGAD00001006322

• Skin Microbiome of Monogenic Skin Disorder

  Ichthyosis introduces multiple sources of disturbance to the skin, including the direct biochemical consequences of the genotype, the phenotypic changes in skin physiology, and an altered skin microbiome. The association between changes in the skin microbiome and the disease's genotypic and phenotypic effects are historically obscured. Here we characterize the skin microbiome of healthy participants and ichthyosis patients, before assessing the association between these microbiome features and the ichthyosis genotype and phenotype while adjusting for contextual host covariables.

  Study phs003799

• Search for new loci and low-frequency variants influencing glioma risk by exome-array analysis

  To identify protein altering variants (PAVs) for glioma we analysed Illumina HumanExome BeadChip exome array data on 1,882 glioma cases and 8,079 controls from three independent European populations. In addition to single variant tests we incorporated information on the predicted functional consequences of PAVs and analysed sets of genes with a higher likelihood of having a role in glioma on the basis of the profile of somatic mutations documented by large-scale sequencing initiatives. Globally tThere was a strong relationship between effect size and SNPs predicted to be damaging (P=2.29x10-49); however, these variants which are most likely to impact on risk, are rare (MAF<5%). While no single variant showed an association which was statistically significant at the genomewide threshold a number of represented promising Notable associations - were seen with the BRCA2:c.9976A>T, p.(Lys3326Ter)BRCA2 p.Lys332X variant, which has been shown documented to influence breast and lung cancer risks (OR=2.3, P=4.00x10-4 for glioblastoma [GBM]) and IDH2:c.782G>A, p.(Arg261His)IDH2 p.Arg261His (OR=3.21, P=7.67x10-3, for non-GBM). Additionally, gene burden tests revealed a statistically significant association for HARS2 and risk of GBM (P=2.20x10-6). Genome scans of low frequency PAVs represent a complementary strategy to identify disease-causing variants compared with scans based on tagSNPs. Strategies to lessen the multiple testing burden by restricting analysis to PAVs with higher priors affords an opportunity to maximise study power.

  Study EGAS00001001258

• ARAF Mutations Confer Resistance to RAF Dimer Inhibitor Belvarafenib in NRAS- and BRAF- Mutant Melanoma

  Belvarafenib, a potent and selective RAF dimer (type II) inhibitor, exhibits clinical activity in BRAFV600E- and NRAS-mutant melanoma patients. Here, we report the first-in-human phase I study investigating maximum tolerated dose, assessing safety and preliminary efficacy of belvarafenib in BRAF- and RAS-mutated advanced solid tumors (NCT02405065, NCT03118817). Through generation of belvarafenib resistant NRAS- mutant melanoma cells and analysis of circulating tumor DNA from patients treated with belvarafenib, we identified novel recurrent mutations in ARAF within the kinase domain. ARAF mutants conferred resistance to belvarafenib in both a dimer- and kinase activity- dependent manner. Belvarafenib induced ARAF mutant dimers, and dimers containing mutant ARAF were active in the presence of inhibitor. ARAF mutations may serve as a general resistance mechanism for RAF dimer inhibitors as the mutants exhibit reduced sensitivity to a panel of type II RAF inhibitors. The combination of RAF plus MEK inhibition may be used to delay ARAF-driven resistance and suggests a rational combination for clinical use. Taken together, our findings reveal specific and compensatory functions for the ARAF isoform and implicate ARAF mutations as a driver of resistance to RAF dimer inhibitors.

  Study EGAS00001005086

• Clonal architectures predict clinical outcome in clear cell renal cell carcinoma

  We analyze the clonal architectures of ccRCC patients from three different populations, including TCGA, Japanese and Chinese patients. We characterize the mutational signatures across different populations and evolution stages. The TCGA and Japanese data sets were downloaded from published studies and we also generated the whole genome sequencing data for more than 40 Chinese patients.

  Study EGAS00001003447

• The data access committee for Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer

  Dac EGAC50000000588

• DNA Methylation Analysis of Prostate Cancer Cell Lines and Tissues Using Next Generation Sequencing

  Aberrant DNA methylation changes are known to occur during prostate cancer progression beginning with precursor lesions. Utilizing fifty nanograms of genomic DNA in Methylplex-Next Generation Sequencing (M-NGS) we mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2). Peaks were located from mapped reads obtained in each sequencing run using a Hidden Markov Model (HMM)-based algorithm previously used for Chip-Seq data analysis(http://www.sph.umich.edu/csg/qin/HPeak). The total methylation events in intergenic/intronic regions between benign adjacent and cancer tissues were comparable. Promoter CGI methylation gradually increased from -12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues and approximately 20% of all CpG islands (CGIs) (68,508) were methylated in tissues. We observed distinct patterns in promoter methylation around transcription start sites, where methylation occurred directly on the CGIs, flanking regions and on CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific and several previously studied targets were among them. A novel cancer specific DMR in WFDC2 promoter showed 77% methylation in cancer (17/22), 100% methylation in transformed prostate cell lines (6/6), none in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested a role for DNA methylation in alternate transcription start site utilization. While methylated promoters containing CGIs had mutually exclusive H3K4me3 modification, the histone mark was absent in CGI sparse promoters. Finally, we observed difference in methylation of LINE-1 elements between transcription factor ERG positive and negative cancers. The comprehensive methylome map presented here will further our understanding of epigenetic regulation of the prostate cancer genome. Overall Design: We mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). For replicate analysis in cell lines, a total of 4 runs were completed for PrEC prostate normal cell line, and 5 runs were completed for LNCaP prostate cancer cell line. For tissue samples, 2 benign prostate samples were sequenced twice on Illumina next generation sequencing platform to access overall repeatability of M-NGS.

  Study phs000597

• Dac for "MediMer: A versatile do-it-yourself peptide-receptive MHC class I multimer platform for tumor neoantigen-specific T cell detection"

  Dac for the Study "MediMer: A versatile do-it-yourself peptide-receptive MHC class I multimer platform for tumor neoantigen-specific T cell detection" registered for Frank Momburg, f.momburg@dkfz-heidelberg.de Marten Meyer, marten.meyer@dkfz-heidelberg.de

  Dac EGAC50000000064