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• Bulk RNAseq of Neuroblastoma patient's tumors

  This dataset contains 9 bulk RNAseq of neuroblastoma patient's tumors used to compare with derived PDXs and/or single-cell data in the Thirant C et al, Nature Communications, 2023. They were intially produced for the Berlanga P., Cancer Discovery, 2022.

  Dataset EGAD00001010287

• Whole exome sequencing of 27 Greenlanders

  The data contain whole exome sequencing of 27 Greenlanders in nine trios. Data were produced by Agilent SureSelect capture followed by paired-end Illumina HiSeq 2000 sequencing to a depth of 90.1X. More details on processing and analysis can be found in Moltke et al, Nature 2014 (PMID 25043022).

  Dataset EGAD00001003813

• Low-coverage Whole Genome Sequencing, Colorectal advanced adenomas, NKI-AvL TGO COCOS series

  For this tissue dataset, we applied low-pass whole genome sequencing to 96 advanced adenomas. Advanced adenomas were classified as lesions with low-risk or high-risk of progression, according to the presence of specific DNA copy number changes (Carvalho et al, CancerPrevRes, 2018).

  Dataset EGAD00001004078

• ETMR H3K27Ac ChIPSeq

  H3K27Ac ChIP-seq DNA libraries for 5 ETMR samples were prepared using NEBNext ChIP-seq Illumina Sequencing library preparation kit. ChIP-seqlibraries were sequenced using single-end 50 bp reads on the Illumina HiSeq 2000 platform. ChIP-seq peaks analysed was conducted as published previously(Torchia et al. 2016).

  Dataset EGAD00001004809

• eQTL summary statistics

  This dataset contains the eQTL summary statistics (nominal pass, significant eQTLs, best associated variant per gene). eQTL mapping was performed with fastQTL. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity.

  Dataset EGAD00001005041

• PFA ependymoma study -WGS data

  WGS bam file for the 18 samples used in Michealraj et al. Cell 2020. The dataset includes PFA ependymoma tissue, derived line and blood samples of 6 patients WGS data were aligned with BWA to the hg38 human reference genome (igenome) and further processed according to the GATK best practice pipeline.

  Dataset EGAD00001006045

• Center for Common Disease Genomics [CCDG] - Cardiovascular: TexGen

  Cardiovascular disease (CVD), especially coronary heart disease, heart failure and cerebrovascular disease remain the leading causes of death in men and women across all race groups in the United States. Substantial evidence exists for genetic factors underlying CVD risk, and their discovery offers an opportunity to enhance understanding of disease mechanisms, to provide specific diagnostic and prognostic indicators, and to identify novel therapeutic targets. The Centers for Common Disease Genomics (CCDG) are a large-scale genome sequencing effort undertaken as a collaboration to identify rare risk and protective alleles for common chronic diseases, with a current focus on early onset heart disease, hemorrhagic stroke, and autism. In this study, whole genome sequencing (WGS) was performed in 6,146 individuals with any personal or family history of CVD from the TexGen study who were recruited from several institutions in the Texas Medical Center located in Houston, Texas. The participants included patients who were admitted with a variety of diagnoses including acute coronary syndromes, strokes, and transient ischemic attacks, or who underwent percutaneous coronary interventions or coronary artery bypass grafting (CABG) (Virani SS et al. Am J Cardiology 107:1504-1509, 2011). Patients in the TexGen cohort with a confirmed diagnosis of acute coronary syndrome (ACS) or CABG when discharged from the hospital between 2001-2008 were eligible for a follow-up study of recurrent myocardial infarction (Virani SS et al. Circulation J 76:950-956, 2012), while those presenting with ACS beginning in 2007 were recruited for an investigation of the role of depressive symptoms in the risk of major adverse coronary events (Sanner J et al. Biol Res Nurs 20:168-176, 2018). In addition, the initial criterion for enrollment in a third TexGen sub-study undertaken between 2007 and 2013 was the occurrence of premature acute myocardial infarction in men ≤ 50 years and women ≤ 55 years in order to establish a blood sample collection resource with the intention of localizing genes that contribute to disease risk. This definition was later expanded to include individuals with a clinical history of premature coronary heart disease such as CABG or percutaneous coronary interventions.

  Study phs003010

• NIDDK IBD Genetics Consortium Ulcerative Colitis Genome-Wide Association Study

  This dataset contains data for 1,028 white, non-Hispanic, European ancestry individuals with ulcerative colitis who were included in a genome-wide association study published by Silverberg et al. (2009). These individuals were ascertained in North America and selected to have either left-sided or extensive disease (i.e., individuals with proctitis only were excluded). Genotyping was performed using the Illumina HumanHap300v2 (n = 540) and HumanHap550v3 (n = 488) Genotyping BeadChips at the Feinstein Institute for Medical Research. Control data (not included) were obtained from the NIDDK IBD Genetics Consortium's Crohn's Disease GWAS (available from dbGaP) and from studies 64 and 65 deposited in the Illumina iControlDB. Seven hundred eighty individuals in this dataset were taken from the NIDDK IBD Genetics Consortium cell line repository (http://www.niddkrepository.org). These individuals are identified in the file dbGaP_SubjectDS.txt. The subject IDs for these individuals may be used to request corresponding samples for follow-up research through the repository. In addition, complete phenotype data for these individuals are included, collected using the Consortium's forms and phenotyping manual (both included). The remaining 248 individuals were identified from pre-existing collections ascertained by members of the Consortium or their collaborators. For these samples, several of the items in the phenotype file are incomplete. Those who wish to replicate the results in Silverberg et al. should note that 6 individuals with missing genotype rates > 0.07 were excluded from that analysis (leaving 1,022 affected samples total). In addition, the minor allele frequencies (MAFs) reported in the publication were calculated using only those individuals who were included in the allelic association tests (n = 977 for SNPs included in the HumanHap300 and n = 476 for SNPs included only in the HumanHap550). These tests were performed using conditional logistic regression on gender-ancestry strata; individuals who were not placed in a stratum (using the procedure described in the supplementary information for Silverberg et al.) were excluded. The indicator variables hh300 and hh550 in the file dbGaP_PhenotypeDS.txt identify the samples included in the allelic association tests, and may be used to replicate the published MAFs among affected individuals.

  Study phs000345

• RCC_HTA2.0_Buettner2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) related to Buettner et al, Genome Med 2022. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.26.0, R version 3.6.1). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 23).

  Dataset EGAD00010002353

• PDX_HTA2.0_Guergen2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) and RCC metastases related to Guergen et al, Front Oncol 12:2022 889789. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.34.0). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 25).

  Dataset EGAD00010002392