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• Hi-C for Junvenile Pilocytic Astrocytomas

  5 Hi-C datasets (4 JPA and 1 LGG). Hi-C data for the remaining 5 JPAs used in our paper as well as all controls have been uploaded to EGA under EGAS00001005476.

  Dataset EGAD00001009044

• Haukeland University Hospital Data Access Committee for ParkOme-1 datasets archvied in Federated EGA Norway

  Data Access Committee appointed by Haukeland University Hospital for omics datasets for Parkinson's disease and related disorders, generated in studies under the ParkOme project. Omics datasets of different types are generated from fresh frozen brain tissue from individuals with neurodegenerative parkinsonisms and neurologically healthy controls.

  Dac EGAC50000000193

• ChIP-seq fastq and alignment files

  ChIP-seq experiments: fastq files; both ChIP and Input for each sample. Illumina HiSeq 2500. ChIP-seq alignment files for trimmed, mapping q20 and nonredundant reads; both ChIP and Input for each sample. Software: Trim Galore v0.3.7; Bowtie 2 v2.1.0; samtools v1.7

  Dataset EGAD00001006279

• FASTQ file for paper titled "Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression"

  This data set includes 27 full-length transcript sequence generated from PacBio IsoSeq that were used for verify the cancer-specific exons identified in three genes: FN1, COL6A3 and TNC. The data were generated from PDX models of osteosarcoma patients.

  Dataset EGAD00001015356

• CpG methylation changes associated with hyperglycemia in type 1 diabetes occur at angiogenic glomerular and retinal gene loci.

  Retinal and glomerular microangiopathy, and cardiovascular disease, contribute to the morbidity and mortality observed in adults with type 1 diabetes (T1D). While the level and duration of hyperglycemia are primary factors influencing these complications, the underlying molecular mechanisms behind glucose-induced organ damage remain poorly understood. In this study, blood samples from young T1D patients at diagnosis and three years later in average were analyzed for DNA methylation using whole-genome bisulfite sequencing. Significant DNA methylation changes in critical angiogenic gene loci were associated with HbA1c, a direct hallmark of chronic hyperglycemia. This finding may offer novel epigenetic insights for a better understanding of T1D complications.

  Study EGAS50000000370

• WES analysis in identifying additive genetic factors that may contribute to the occurrence of moyamoya in neurofibromatosis type 1

  Moyamoya is a progressive cerebral vasculopathy, for which genetic susceptibility factors were mainly identified in Asian populations. When associated with other medical conditions, such as neurofibromatosis type 1 (NF1), this vasculopathy is frequently reported as Moyamoya syndrome (MMS). Intriguingly, most cases of MMS-complicated NF1 have been described in Caucasians, inverting the population ratio for moyamoya vasculopathy observed in Asians, despite NF1 prevalence being constant worldwide. This study aims to investigate whether, among Caucasians, additive genetic factors may contribute to the occurrence of MMS in NF1. WES analysis has been carried out on an Italian family with co-occurrence of NF1 and MMS, as well as other cerebral vasculopathies.

  Study EGAS00001003053

• PETAL Repository of Electronic Data COVID-19 Observational Study (RED CORAL)

  To describe characteristics, treatment, and outcomes among patients hospitalized with COVID-19 early in the pandemic, 1480 consecutive adult inpatients with laboratory-confirmed, symptomatic SARS-CoV-2 infection admitted to 57 US hospitals from March 1 to April 1, 2020 were studied.It was found that in a geographically diverse early-pandemic COVID-19 cohort with complete hospital folllow-up, hospital mortality was associated with older age, comorbidity burden, and male sex. Intensive care unit admissions occurred early and were associated with protracted hospital stays. Survivors often required new health care services or respiratory support at discharge.The PETAL Network central institutional review board at Vanderbilt University and the institutional review boards at each participating hospital approved the study or determined that the study was exempt from review. Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.

  Study phs002363

• Plasma cell‐Free transcriptome profiling in chronic liver disease

  Chronic liver disease (CLD) encompasses a wide range of hepatic disorders that progressively compromise liver function. In order to support the development of non-invasive diagnostic tools and improve patient stratification, we generated a high-throughput extracellular RNA sequencing dataset from blood plasma samples collected from patients at various stages of liver disease. Samples were obtained from two independent cohorts of 112 (cohort 1) and 489 (cohort 2) patients using standardized collection and processing protocols, and profiled using total RNA sequencing (SMARTer Stranded Total RNA-Seq Kit v3 - Pico Input Mammalian), resulting in 112 and 820 extracellular transcriptomic profiles for cohort 1 and 2, respectively. This dataset is provided with full documentation of the preprocessing analysis pipeline and accompanying metadata, enabling its use as an independent validation cohort for biomarker discovery and as a complementary resource for integrative multi-omics studies, even in cases with incomplete data modalities. The publicly available resource is intended to facilitate reproducibility and foster further research in the field of liver disease diagnostics

  Study EGAS50000000545

• eMERGE: Northwestern (NUgene) WGS

  The NUgene Project is a biorepository with longitudinal medical information from participating patients at Northwestern Medicine affiliated hospitals and outpatient clinics. Participants' DNA samples are coupled with data from a self-reported questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 3 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated enterprise data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. The electronic MedicalRecords and Genomics (eMERGE) Network is a consortium of 9 clinical sites with EMR linked DNA biobanks, including Northwestern University and its NUgene biobank, funded by the NHGRI (National Human Genome Research Institute) to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 100,000 individuals using EMR-derived phenotypes and DNA from linked biorepositories. Using electronic phenotyping methods, the consortium has been and is using DNA samples from all participating sites to explore the genetic determinants of approximately 80 phenotypes, including both diseases and traits, for which the electronic phenotyping algorithms have or are being published on PheKB.org. Thus, for the eMERGE network, ~900 NUgene subjects were selected, as described in the study inclusion/exclusion criteria section below, to be genotyped using whole genome sequencing (WGS), for use in the eMERGE network as eMERGE subjects. The criteria used below were selected so that these subjects will likely meet the criteria to be cases and/or controls, of diverse races and/or ethnicities, for at least 1 of the ~80 phenotypes being studied within eMERGE, and could be recontacted for future research if needed.

  Study phs001191

• Single cell sequencing in D425

  Single cell sequencing aligned BAM files for the D425 cell line

  Dataset EGAD50000002304