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• Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC)

  In 2016 we established the Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC) funded by the Ice Bucket Challenge Grant administered by the Motor Neurone Disease Research Institute of Australia. The goals of the SALSA-SGC are to collect biological samples from clinics across Australia with matched in depth clinical and self-report phenotypes and to generate multiple levels of genetic and genomic data. In this first data generation exercise of the SALSA-SGC the majority of the samples were collected prior to the formal establishment of SALSA-SGC from clinics across Australia.Briefly, the cohort includes the University of Sydney’s Australian Motor Neuron Disease DNA Bank (MND Bank) cohort recruited April 2000 to June 2011), with study protocol approved by the Sydney South West Area Health Service Human Research Ethics Committee (HREC). Cases were recruited from around Australia via state-based MND associations with diagnosis verified by a neurologist. The remainder of the cases were recruited from clinics across Australia between 2015 and 2017 under HREC approvals from Royal Brisbane and Women’s Hospital, Macquarie University Multidisciplinary Motor Neurone Disease Clinic,  Calvary Health Care Bethlehem in Melbourne , Fiona Stanley Hospital in Perth, and from 2016 under HREC approvals at each site for the sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC). The ALS cases were diagnosed with definite or probable ALS according to the revised El Escorial criteria. Some controls were recruited as either partners or friends of patients, healthy individuals free of neuromuscular diseases. We are providing GWAS and MWAS data in this dataset. Individual level GWAS data were generated using Illumina Infinium CoreExome-24 version 1.1 chips for N= 846 cases and N=665 controls. Individual MWAS data was generated using the Illumina Human methylation 450K array for N=782 cases and N=613 controls. There 1315 individuals where GWAS and MWAS data has been generated and is available. Further information on these data sets can be found: Paper 1: Restuadi, R, Garton, FC, Benyamin, B, Lin, T, et al. Amyotrophic Lateral Sclerosis Genetic Correlation with Cognitive Performance, educational attainment and schizophrenia: evidence from polygenic risk score analysis. (submitted) Paper 2: Nabais, MF, Lin, T, Benyamin, B et al. Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis. 2020. NPJ genomic medicine. 5(10). Files provided in this submission include: GWAS: This folder contains QCed genotype for the Australian ALS case-control cohort. Contains PLINK files for genotyping data (not imputed yet). The individuals selected here have: good consistency on phenotype data ethics approval registered as part of sporadic ALS studies unrelated by GRM cut-off 0.05 No ancestry QC yet MWAS: This folder contains the IDAT and post-QC normalized DNAm (beta) for the Australian ALS case-control cohort. 2019_AUS_ALS_PCTG_DNAm.tar.gz - IDATS for 1315 individuals analyzed in the MWAS study normalized_beta_values - Binary files (created with the OSCA software) containing information on the individuals, probes and the DNAm (beta) values obtained after QC phenotype_file - contains all the covariates analysed in the MWAS including: case-control status, coded 0 = Control and 1 = ALS, predicted age, predicted cell-type proportions, predicted smoking scores, slide and chip position and sex Important Notes: The DNAm data were normalized together with samples that were not part of this ALS case/control study and thus, the normalization procedure may not be 100% reproducible using only the IDAT files uploaded here. Summary data has been made publicly available and can be accessed directly: Data collection and sample processing were performed at several clinics across Australia. Genotyping and DNA methylation arrays were performed by the Human Studies Unit, at the Institute for Molecular Bioscience (University of Queensland). Quality control of the genotypic, phenotypic and DNA methylation data was done by the Program of Complex Traits Genomics, at the Institute for Molecular Bioscience (University of Queensland).

  Study phs002068

• Single-cell RNA sequencing of SI-NET

  Small intestinal neuroendocrine tumors (SI-NETs) arise from hormone-producing cells in the gut, yet the molecular changes driving malignant transformation remain poorly understood. Bulk tissue-based analyses make it challenging to distinguish signals derived from normal cells from those of normal hormone-producing cells. In this study, we analyzed SI-NETs at single-cell resolution and directly compared tumor cells with their corresponding normal hormone-producing counterparts using single-cell RNA sequencing. Tissue samples were obtained from two patients undergoing tumor resection surgery. Cells from corresponding normal intestinal mucosa and SI-NET tumors were isolated using specific markers and analyzed for direct comparison.

  Study EGAS50000001584

• LifeLines-DEEP population multi-omix cohort from the noth of the Netherlands.

  The LifeLines-DEEP cohort is a sub-cohort of the LifeLines cohort (167,729 participants) that employs a broad range of investigative procedures to assess the biomedical, socio-demographic, behavioral, physical and psychological factors that contribute to health and disease in the general Dutch population, (Scholtens 2015). A subset of approximately 1,500 participants also took part in LifeLines-DEEP. For these participants, additional biological materials were collected, including analysis of the gut microbiome composition. The phenotyping and processing of LifeLines-DEEP has been described in Tigchelaar (2015).

  Study EGAS00001001704

• Small intestinal plasma cells transcriptome profiles

  Objective: Plasma cells (PCs) are terminally differentiated B-lymphocytes that produce antibodies. The lamina propria of the small intestine is particularly rich in PCs. In coeliac disease (CeD) there is infiltration and increased density of PCs in the small intestinal lesion. Many of these PCs produce disease-specific autoantibodies targeting the enzyme transglutaminase 2 (TG2). The plasmacytosis and high numbers of disease-antigen reactive PCs in CeD motivated us to study the transcriptional programme of PCs from coeliac gut lesions. Design: We performed RNASeq analysis of IgA+ PCs of untreated CeD patients being specific or non-specific for TG2 and from healthy controls.

  Study EGAS00001003345

• NIH RECOVER: A Multi-Site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection

  The RECOVER tissue pathology study is a cross-sectional study designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection in a diverse population representative of the general COVID-19 population in the US. The autopsy study will characterize the pathology of PASC in decedents who die more than 60 days after initial onset or after hospital discharge, whether in-hospital or out-of-hospital at time of death, and who meet the working definition of PASC as defined by the recent World Health Organization publication given in Section 5.4. The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of decedents who died between15-60 days from symptom onset. This protocol defines the common set of clinical data elements, autopsy procedures for tissue collection, core measures, pathology protocols, shared pathology tissues, data elements, and methodology. Each investigator site is expected to perform autopsies on the decedents to address the pathophysiology of the potential long-term effects of SARS-CoV-2 infection on human health. The Consortium analysis plan aims to address research questions by incorporating: 1) tissue obtained from autopsies performed at each Phase II participant's site; and 2) tissue available from other pathology investigators/autopsy sites within the Consortium.

  Study phs003768

• Bulk-tissue paired-end RNA-sequencing of anterior cingulate cortex samples derived from Lewy body disease patients

  Profiling of 24 human anterior cingulate cortex samples by bulk-tissue RNA-sequencing. Samples were derived from 5 non-neurological control individuals and 19 individuals with Lewy body disease (Parkinson’s disease = 7 individuals; Parkinson’s disease with dementia = 6 individuals; dementia with Lewy bodies = 6 individuals). Paired-end FASTQ files for each of the human samples are provided and are denoted by the suffixes R1 (read 1) and R3 (read 2). Fastp (v 0.20.0), a fast all-in-one FASTQ pre-processor, was used for adapter trimming, read filtering and base correction. Fastp default settings were used for quality filtering and base correction. Further details on parameters used are available here: https://github.com/RHReynolds/RNAseqProcessing/blob/master/QC/prealignmentQC_fastp_PEadapters.R.

  Dataset EGAD00001007698

• UK renal cancer samples genotyped on Illumina OmniExpress BeadChip

  Renal cell carcinoma (RCC) cases comprised adult patients with histologically proven RCC were collected through two sources within the UK. First, 856 cases from SORCE, a MRC collection of surgically treated RCC cases ascertained through UK clinical oncology centres. Second, 189 RCC cases collected through the ICR and Royal Marsden NHS Hospitals Trust. Cases included 590 clear cell carcinomas (CCCs), 42 papillary carcinomas (PCs), 33 chromophobe carcinomas (CCs) and 19 mixed or other histological subtypes. DNA was extracted from EDTA-venous blood samples using the conventional methods and quantified using PicoGreen (Invitrogen). Cases were genotyped using the Human OmniExpress-12 BeadChip according to the manufacturer's recommendations (Illumina Inc, San Diego, CA, USA). After strict QC, 944 cases were retained. Data provided in plink format. Controls used were data from the Wellcome Trust Case Control Consortium 2 (WTCCC2) 1958 birth cohort and the UK Blood Service Control Group (available as EGAS00000000028).

  Study EGAS00001002336

• WES of der(1;7)(q10;p10)

  This dataset contains the BAM files of WES of 26 myeloid neoplasm patients with der(1;7)(q10;p10)(+) cases. The dataset was used to identify key driver genes in patients with der(1;7)(q10;p10). Already known drivers along with novel driver genes were identified through the use of this WES.

  Dataset EGAD50000000986

• Short-read (RNA-seq)

  The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

  Dataset EGAD00001006596

• BLUEPRINT: RNA-seq of progenitor cells

  Data supporting the paper Transcriptional diversity during lineage commitment of human blood progenitors

  Dataset EGAD00001000745