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NBS

ABSTRACT: WTCCC2 project samples from National Blood Donors (NBS) Cohort

PROVIDER: EGAD00000000023 | EGA |

REPOSITORIES: EGA

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Identity-by-descent mapping in a Scandinavian multiple sclerosis cohort.

Westerlind Helga H Imrell Kerstin K Ramanujam Ryan R Myhr Kjell-Morten KM Celius Elisabeth Gulowsen EG Harbo Hanne F HF Oturai Annette Bang AB Hamsten Anders A Alfredsson Lars L Olsson Tomas T Kockum Ingrid I Koski Timo T Hillert Jan J

European journal of human genetics : EJHG 20140827 5

In an attempt to map chromosomal regions carrying rare gene variants contributing to the risk of multiple sclerosis (MS), we identified segments shared identical-by-descent (IBD) using the software BEAGLE 4.0's refined IBD analysis. IBD mapping aims at identifying segments inherited from a common ancestor and shared more frequently in case-case pairs. A total of 2106 MS patients of Nordic origin and 624 matched controls were genotyped on Illumina Human Quad 660 chip and an additional 1352 ethnic ...[more]

PMID: 25159868

Publication: 1/7

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Project description:WTCCC2 project controls - 1958 British Birth Cohort and National Blood Service

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Project description:New techniques for single-cell analysis have led to insights into hematopoiesis and the immune system, but the ability of these techniques to cross-validate and reproducibly identify the biological variation in diverse human samples is currently unproven. We therefore performed a comprehensive assessment of human bone marrow cells using both single-cell RNA sequencing and multiparameter flow cytometry from twenty healthy adult human donors across a broad age range. These data characterize variation between healthy donors as well as age-associated changes in cell population frequencies. Direct comparison of techniques revealed discrepancy in the quantification of T lymphocyte and natural killer cell populations. Orthogonal validation of immunophenotyping using mass cytometry demonstrated good correlation with flow cytometry. Technical replicates using single-cell RNA sequencing matched robustly, while biological replicates showed variation. Given the increasing use of single-cell technologies in translational research, this resource serves as an important reference dataset and highlights opportunities for further refinement. [Funding source] Project Number: 1ZIAHL006163-05 Contact PI / Project Leader: HOURIGAN, CHRISTOPHER Title: DETECTION, PREVENTION AND TREATMENT OF ACUTE MYELOID LEUKEMIA (AML) RELAPSE. Awardee Organization: NATIONAL HEART, LUNG, AND BLOOD INSTITUTE

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Affymetrix expression data from GTEx

Project description:The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz)

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Affymetrix expression data from GTEx

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