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13415 results for ""pdc"+"heritage+language"+census+study"

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Study type

affected sib pairs aggregate genomic data amplicon sequencing atac sequencing cancer genomics case set case-cohort case-control clinical cohort clinical diagnostic testing clinical genetic testing clinical trial cohort collection community control set controlled trial copy number variation (cnv) cross-sectional double-blind electronic medical records epigenetics eqtl exome sequencing extended pedigrees family family linkage forensic or paleo-genomics full transcriptome sequencing gene regulation study genotype genotype/expression genotype/expression array gwas individual-level genomic data interventional longitudinal longitudinal cohort marker discovery mendelian meta-analysis metagenomics metastasis methods development mixed multicenter multiplex families nested case-control nuclear families observational other parent-offspring parent-offspring trios partial factorial randomized phase iii placebo-controlled pooled clone sequencing population population genomics population-based control set probands prospective quantitative cross-sectional randomized randomized controlled clinical trial reference set resequencing rna sequencing rnaseq sequencing sibling cohort single cell analysis single cell rna sequence single cell rna sequencing single patient snp array analysis stem cell lines synthetic genomics targeted capture sequence transcriptome analysis transcriptome sequencing transcriptome sequencing (tumor only) tumor tumor vs. matched-normal twin virus capture sequencing whole genome sequencing whole-genome bisulfite sequencing xenograft

Dataset types

amplicon sequencing chip-seq chromatin accessibility profiling by high-throughput sequencing exome sequencing genomic variant calling genotyping by array histone modification profiling by high-throughput sequencing methylation binding domain sequencing methylation profiling by high-throughput sequencing phenotype information study summary information transcriptome profiling by array transcriptome profiling by high-throughput sequencing whole genome sequencing

Dataset technologies

ab 3730xl genetic analyzer ab 5500xl genetic analyzer ab solid 4 system affy mirna 3.0 array affymetrics axiom snp array 2.0 affymetrix affymetrix 6.0 array affymetrix 6.0; cytoscan affymetrix axiom 850k pmda array affymetrix axiom genome-wide asi 1 array affymetrix axiom genome-wide human origins array affymetrix biobank array affymetrix oncoscan ffpe express affymetrix, thermo fisher scientific agilent human mirna microarray axiom uk biobank array bgiseq-500 clariomâ„¢ d human assay complete genomics coreexome illumina snp chip array dnbseq-g400 dnbseq-t7 epic beadchip hiseq x five hiseq x ten human cardio metabochip human clariom d arrays human genome u219 array plate humanht-12 illumina (epic array) illumina 450k illumina cardio-metabochip illumina genome analyzer illumina genome analyzer ii illumina genome analyzer iix illumina global screening array illumina gsa v1.0 illumina hiseq 1000 illumina hiseq 1500 illumina hiseq 2000 illumina hiseq 2500 illumina hiseq 3000 illumina hiseq 4000 illumina hiseq x illumina human methylation epic beadchip illumina human omni1-quad beadchip. illumina humancoreexome beadchip array illumina humancoreexome-12v1-1_a illumina humancoreexome-24v1-0 illumina humancoreexome-24v1-1 illumina humanmethylation450 illumina humanomni1-quad_v1-0 illumina humanomni1-quad_v1-0, humanomniexpress-12-v1-0, humanomniexpress-24-v1-1, humanomni25-8v1-2_a1 illumina humanomni2.5 illumina humanomni2.5-8 illumina humanomni5-quad and exome sequencing illumina humanomniexpress-12 illumina humanomniexpress-12-v1-0 illumina humanomniexpress-24-v1-1 illumina humanwg-6 illumina humanwg-6 version 3 or illumina humanht-12 expression bead chip, combined on identical nucleotide universal identifiers. illumina infinium epic illumina infinium h3africa (v2) with custom add-ons illumina infinium immunochip illumina infiniumomniexpressexome-8 illumina mega array illumina methylationepic v2.0 illumina miniseq illumina miseq illumina novaseq 6000 illumina novaseq x illumina novaseq x plus illumina omni 2.5 illumina omni 2.5m illumina oncoarray illumina sangerddd_omniexplusv1_15019773 infinium gsa infinium methylationepic array ion genestudio s5 ion torrent pgm ion torrent proton ion torrent s5 xl llumina 2.5-8 minion nextseq 2000 nextseq 500 nextseq 550 nimblegen hg18 cgh 385k omniexpress omniexpress-24 v1.1 pacbio rs ii promethion qexactive plus revio sanger sequencing sequel sequel ii sequel iie sequenom massarray (agena bioscience) somascan 1.3k proteomic assay uk biobank axiomâ„¢ array unspecified

Phenotypes

CHEBI:33699 CL:0000037 CL:0000084 CL:0000094 CL:0000235 CL:0000576 CL:0000837 CL:0000863 CL:0000890 CL:0002057 EFO:0000094 EFO:0000209 EFO:0000211 EFO:0000220 EFO:0000222 EFO:0000272 EFO:0000275 EFO:0000280 EFO:0000285 EFO:0000309 EFO:0000322 EFO:0000330 EFO:0000339 EFO:0000349 EFO:0000403 EFO:0000478 EFO:0000519 EFO:0000565 EFO:0000574 EFO:0000586 EFO:0000609 EFO:0000632 EFO:0000637 EFO:0000693 EFO:0000980 EFO:0001461 EFO:0001663 EFO:0001905 EFO:0002001 EFO:0002002 EFO:0002422 EFO:0002499 EFO:0002508 EFO:0002539 EFO:0002759 EFO:0002939 EFO:0002966 EFO:0003025 EFO:0003094 EFO:0003885 EFO:0003897 EFO:0003940 EFO:0004281 EFO:0005023 EFO:0005543 EFO:0005699 EFO:0005704 EFO:0005705 EFO:0005706 EFO:0005707 EFO:0005708 EFO:0005709 EFO:0005710 EFO:0005711 EFO:0005712 EFO:0005740 EFO:0005922 EFO:0006545 EFO:0009119 EFO:0009121 EFO:0009443 EFO:0010064 EFO:1000028 EFO:1000042 EFO:1000068 EFO:1000069 EFO:1000177 EFO:1000180 EFO:1000231 EFO:1000238 EFO:1000327 EFO:1000490 EFO:1001480 EFO:1001514 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Duo

0000001 0000004 0000005 0000006 0000007 0000011 0000012 0000014 0000015 0000016 0000017 0000018 0000019 0000020 0000021 0000022 0000024 0000025 0000026 0000027 0000028 0000029 0000042 0000043 0000044 0000045 0000046

Clear

Sequencing component for the whole genome methylation analysis in PBMCs and cell subsets (pilot study)

DNA methylation has been shown to play a major role in determining cellular phenotype by regulating gene expression. Moreover, dysregulation of differentially methylated genes has been implicated in disease pathogenesis of various conditions including cancer development as well as autoimmune diseases such as systemic Lupus erythematosus and rheumatoid arthritis. Evidence is rapidly accumulating for a role of DNA methylation in regulating immune responses in health and disease. However, the exact mechanisms remain unknown. The overall aim of the project is to investigate the role of epigenetic mechanisms in regulating immunity and their impact on autoimmune disease pathogenesis.The aim of this pilot study is to perform whole genome methylation analysis in peripheral blood mononuclear cells (PBMCs) and cell subsets (CD4, CD8, CD14, CD19, CD16 and whole PBMCs) obtained from 6 healthy volunteers. Whole genome methylation analysis will be performed using two methodological approaches, the Infinium Methylation Bead Array K450 (Illumina) and MeDIP-seq. mRNA expression arrays will also be performed in order to correlate DNA methylation with gene expression as well as genotyping on the Illumina OmniExpress chip
Dataset EGAD00001000394
FinHer Breast Cancer Study

The purpose of this study is to sequence 500 known cancer genes in 960 newly diagnosed high risk breast cancer patients treated with current standard of care therapies and trastuzumab, for somatic alteration and copy number changes. We will be using next gen sequencing technology to determine the prognostic relevance of these somatic genetic alterations and of teh low frequency events to determine if they are associated with trastuzumab benefit or HER2 positive breast cancer, i.e. treatment interaction. The samples will be analysed adn correlated with clinical variables including outcome.
Dataset EGAD00001000871
Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis

This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.
Dataset EGAD00001001090
MutWP5: CRUK Mutographs of Cancer: Breast: Cancer Mastectomy (WG) (2020-01-29)

Sequencing of LCM-derived microbiopsies from 40 women who underwent mastectomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2020-01-29.
Dataset EGAD00001005922
MutWP5: CRUK Mutographs of Cancer: Lung: PD38234 (Targeted) (2020-01-29)

Sequencing of LCM-derived microbiopsies from explanted lung from pulmonary fibrosis patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-01-29.
Dataset EGAD00001005925
PopCol 16S gut microbiome sequencing

PopCol is a cohort study in Stockholm, Sweden that includes a data-rich set of individuals with data available from bowel symptoms questionnaires, gastroenterology visits and biospecimens (genotype and 16S sequencing from blood and stool samples, respectively). Genotyping was carried out using the Illumina HumanOmniExpressExome-8v1 arrays at the SciLifeLab NGI facility in Uppsala, Sweden. Fecal DNA was extracted from samples kept at -80°C using Qiagen 5 QIAamp DNA Stool Mini Kits and analyzed using 16S rRNA gene amplicon sequencing (in the V1-V2 hypervariable region). This was performed on the Illumina MiSeq platform at the Institute of Clinical Molecular Biology (IKMB) in Kiel, Germany. Of these, six PopCol participants were PPI users and 12 used antibiotics. The study was approved by the local Committee of Research Ethics (Forskningskommitté Syd) at Karolinska Institutet, Stockholm, in November 2001. Written informed consent was obtained from all participants
Dataset EGAD00001007071
MutWP5: CRUK Mutographs of Cancer: BRCA Carriers (WG)(Novaseq)

Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastecomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.
Dataset EGAD00001010112
MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (Exome)

Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.
Dataset EGAD00001010110
MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (WG)(Novaseq)

Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.
Dataset EGAD00001010113
MutWP5: CRUK Mutographs of Cancer: BRCA Carriers (Exome)(Novaseq)

Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastecomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.
Dataset EGAD00001010115

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