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• A Genomic Approach to Improved Diagnosis and Treatment of Neuroendocrine Tumors

  These are RNA-Seq samples from patients undergoing surgery for small bowel and pancreatic neuroendocrine tumors. Normal tissue, primary tumors, lymph nodes, and liver metastases were collected at surgery and stored in RNAlater until RNA extraction was carried out for RNA-Seq.

  Study phs001772

• Genomics of acral lentiginous melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010126

• Genetic Association Studies in the Solomon Islanders

  The goal of this study was to determine the genetics underlying blond hair in the Solomon Islands, which has the highest prevalence of blondism outside of Europe. Participants in the study were of self-reported Solomon Islands ancestry and were 6-36 years of age at enrollment. Individuals with blond (N = 43) and dark hair (N = 42) were selected, approximately matched for age, sex and local geography, and spectrophometric measurements of hair pigmentation were made as a single measurement taken from hair at the crown. Individuals with gray, white, thin, bleached or artificially colored hair were excluded from analysis. All 85 participants were evaluated in a genome-wide scan to detected association to hair pigmentation in the Solomon Islands.

  Study phs000493

• Type 1 Diabetes Genetics Consortium (T1DGC): ImmunoChip Study

  The Type 1 Diabetes Genetics Consortium (T1DGC) was formed to address issues of limited sample size and consistency of phenotyping that had limited genetic investigations on risk of type 1 diabetes (T1D). The T1DGC first collected affected sib pair (ASP) families from four geographic networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, T1D cases and controls were ascertained from existing and de novo collections. The T1DGC assembled 2,601 T1D ASP families and 69 Parent-T1D offspring trios, T1D cases from the UK Genetic Resource Investigating Diabetes (UKGRID, N=6,670), and controls from the British 1958 Birth Cohort (B58BC, N=6,523), the UK National Blood Services collection (NBS, N=2,893) and the NIHR Cambridge Biomedical Research Centre BioResource (CBR, N=2,846). All samples included in this series have reported or self-declared European ancestry. All DNA samples were collected after approval from relevant institutional research ethics committees. Genotyping was performed using a custom Illumina Infinium high-density genotyping array, ImmunoChip (Illumina, Inc; CA) according to manufacturer's protocols. The ImmunoChip was designed to densely genotype, using 1000 Genomes and any other available disease specific resequencing data, immune-mediated disease loci identified by common variant GWAS. The ImmunoChip Consortium selected 186 distinct loci containing markers meeting genome wide significance criteria (P<5x10-8) from twelve such diseases (autoimmune thyroid disease, ankylosing spondylitis, Crohn's disease, celiac disease, IgA deficiency, multiple sclerosis, primary biliary cirrhosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, T1D and ulcerative colitis). All 1000 Genomes Project pilot phase CEU population variants (Sept 2009 release) within 0.1cM (HapMap3 CEU) recombination blocks around each GWAS region lead marker were submitted for array design. No filtering on correlated variants (linkage disequilibrium) was applied. Additional content included regional resequencing data (submitted by several groups) as well as a small proportion of investigator-specific undisclosed content including intermediate GWAS results. After data cleaning and quality control, a total of 154,939 single nucleotide polymorphisms (SNPs) from 186 loci on ImmunoChip were scored. Case-control and family data were analyzed independently and combined by meta-analysis.

  Study phs000911

• Illumina Omni5 SNP chip genotyping of MacTel cases and unaffected controls for a genome-wide association study

  Macular telangiectasia type 2 (MacTel) is a rare neurovascular degenerative retinal disease. To identify genetic susceptibility loci for MacTel, we performed a genome-wide association study (GWAS). We genotyped 704 samples, of which 678 have consented to be available here. These samples mainly include MacTel cases but also some unaffected controls (often spouses). The samples were collected through the MacTel Project (funded by the Lowy Medical Research Institute), which includes a registry and extensive clinical analysis to confirm the presence of MacTel in affected individuals. Additional controls were obtained from dbGap [phs000429.v1.p1]. After QC steps, the GWAS utilised 476 cases and 1733 controls of European ancestry.

  Study EGAS00001002249

• Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

  ChIP-Seq - CEBPE - REH. The ETV6/RUNX1 translocated acute lymphoblastic leukaemia cell line. REH was used to perform ChIP-Seq using a CEBPE antibody. Cells were fixed in 1% formaldehyde for 10mins, prior to preparation of chromatin using Active Motif Express ChIP-IT. 2ug of antibody (anti CEBPE Atlas Antibodies HPA002928)was added to 25ug of chromatin O/N at 4C with rotation. Duplicate reactions were pooled and purified. 10ng of ChIP’d and input DNA used for Illumina NGS preparation (NEBNext ChIP-Seq Library kit; New England Biolabs), CEBPE and Input DNA ChIP samples were sequenced on a MiSeq using 150bp Kit v3 paired end and a HiSeq 2500 using 2x101 version 4 paired end (Illumina) respectively. Reactions performed in duplicate. shCEBPE RNA-Seq - REH. REH cells were lentivirally transduced with a pTRIPZ shRNA vector for transcriptional profiling of CEBPE. Two controls (empty and non-targeting) and two CEBPE shRNAs (V3THS_150517(A13), V3THS_404312(G3) Dharmacon, GE) were transduced into REH cells. Cells were treated with 1ug/ml doxycyclin for 144hrs and total RNA purified using Qiagen RNeasy. Knock down of CEBPE was validated by qRT. RNA integrity >7.7 for all samples. Libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kit and sequenced on an Illuimna HiSeq 2500 using 2x101 version 4 paired end chemistry. 3 biological replicates of each samples were prepared.

  Dataset EGAD00001004084

• Exome sequencing of UK Birth Cohorts - Avon Longitudinal Study of Parents and Children

  Birth cohort studies involve repeated surveys of large numbers of individuals from birth and throughout their lives. They collect information useful for a wide range of life course research domains, and biological samples which can be used to derive data from an increasing collection of omic technologies. This rich source of longitudinal data, when combined with genomic data, offers the scientific community valuable insights from population genetics to rare disease associations. Avon Longitudinal Study of Parents and Children (ALSPAC)recruited 14,775 babies of predominantly White ethnicity in the Avon county of south-west England between 1991 and 1992. Born in Bradford (BiB) is similarly focused on a particular local area, the city of Bradford in the north of England, and recruited 13,858 babies between 2007 and 2011, of whom ~41% self-report as white British and ~59% as other ethnicities, predominantly Pakistani. Millennium Cohort Study (MCS) is a national cohort that recruited 18,827 children born between 2000 and 2002, intentionally over-sampling areas with high child poverty, large ethnic minority populations, and smaller UK nations (Wales, Scotland and Northern Ireland) Available here is a subset of exome-sequenced parents and children from these studies (CRAMS and post-QC VCFs) as detailed in https://doi.org/10.12688/wellcomeopenres.22697 [doi.org]. Phenotypic data is also available by submitting an application to the corresponding cohort: https://www.bristol.ac.uk/alspac/researchers/our-data/[bristol.ac.uk]

  Dataset EGAD00001015371

• Genetic Alterations in Benign Breast Biopsies of Subsequent Breast Cancer Patients

  Fibrocystic changes are associated with an increased risk of breast cancer (approximately 1.5-2 times that of the general population). Although the relative risk seems low, because of the high frequency of such changes, the absolute risk is significant. Genetic alterations have been found in fibrocystic changes with or without epithelial changes, suggesting that critical oncogenic events are occurring at an early stage. We investigated a unique collective of 17 breast cancer patients who, prior to the diagnosis of invasive breast cancer, underwent open surgical biopsy showing fibrocystic changes of the breast. Massive parallel sequencing targeting genes frequently mutated in breast cancer was performed on the fibrocystic breast tissue as well as the ensuing cancer tissue.

  Study EGAS00001003563

• Tissue Site

  Tissue site for RNAsequencing data. Tissue site is associated with the clinical biomarker data and be linked to the biomarker data using the SAMPLE and PAT identifiers.

  Dataset EGAD50000000931

• 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