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13393 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

Exome-sequencing of two UFM individuals and their Fragile X family members.

Fragile X syndrome (FXS) is a monogenic neurodevelopmental disease often caused by a CGG triplet expansion in the 5’UTR of the FMR1 gene, which results in DNA methylation of the FMR1 promoter and its transcriptional silencing. Exceptional healthy individuals named "unmethylated full mutation (UFM)" have been identified in the families of FX patients. They carry an expanded CGG repeat, but show normal FMR1 epigenetic configuration and expression. In this study we performed exome-sequencing of two UFM individuals and their family members to identify possible genetic mutations responsible for the escape of silencing in the unmethylated full mutation (UFM) phenotype.
Study EGAS00001001737
Population whole-genome bisulfite sequencing across two tissues highlights environment as principal source of human methylome variation

The study includes whole-genome bisulfite sequencing (WGBS) on 34 adipose(7 MZ pairs, 6 DZ pairs and 8 singletons) and 27 blood (7 MZ pairs, 6 DZpairs and 1 singleton) DNA samples derived from a total of 43 female twinsbelonging to the MuTHER/TwinsUK cohort. We generated 11.5 billion 100bppaired-end reads covering 2.3 Tera-basepairs (Tbp) ofsequence using the Illumina HiSeq2000 or 2500 systems. Applying standardalignment methods and filters we obtain a mean genome coverage of 6.3-fold(range: 1.0- to 12.9-fold) for adipose and 8.7-fold (range: 0.7- to29.0-fold) for blood.
Study EGAS00001001569
CONSERTING: integrating copy number analysis with structural variation detection

We developed Copy Number Segmentation by Regression Tree in Next Generation Sequencing (CONSERTING), a novel algorithm for detecting somatic copy number alteration (CNA) using whole-genome sequencing (WGS) data. CONSERTING performs iterative analysis of segmentation by read depth change and localized structural variation detection to achieve high accuracy and sensitivity. Analysis of 43 pediatric and adult cancer genomes revealed novel oncogenic CNAs, complex re-arrangements and subclonal CNAs missed by alternative approaches. This study contains all data for "CONSERTING: an accurate method for detecting somatic DNA copy number alterations in whole genome sequencing data", which was previously split between EGAS00001001202 and EGAS00001001050.
Study EGAS00001001202
Investigating_low_frequency_variants_in_CAD_MI_cases__controls_and_pedigrees_using_whole_exome_sequencing_and_custom_pulldowns

The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.
Study EGAS00001000043
Investigating_low_frequency_variants_in_CAD_MI_cases__controls_and_pedigrees_using_whole_exome_sequencing_and_custom_pulldowns

The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.
Study EGAS00001000050
Combination Therapies for Personalised Cancer Medicine in drug resistant EGFR mutant lung cancer

This study involves mutagenizing a range of different cell lines with ENU to identify those mutations which engender resistance to targeted treatment. In the last decade we have begun to move towards the use of targeted therapeutics in the clinic, often resulting in dramatic response rates in cancer patients. However, clinical experience has demonstrated time and time again that such responses are invariably followed by the development of drug resistance. Identification of the underlying mechanisms may enable us to reverse such resistance. Traditional methods of modelling this resistance in vitro can lead to a plethora of potential resistance mechanisms that can be difficult to decipher.
Study EGAS00001002509
Combination Therapies for Personalised Cancer Medicine in 11-18

This study involves mutagenizing 11-18 with ENU to identify those mutations which engender resistance to targeted treatment. In the last decade we have begun to move towards the use of targeted therapeutics in the clinic, often resulting in dramatic response rates in cancer patients. However, clinical experience has demonstrated time and time again that such responses are invariably followed by the development of drug resistance. Identification of the underlying mechanisms may enable us to reverse such resistance. Traditional methods of modelling this resistance in vitro can lead to a plethora of potential resistance mechanisms that can be difficult to decipher.
Study EGAS00001002579
MutWP5__CRUK_Mutographs_of_Cancer__Lung__PD38234__Targeted_

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.
Study EGAS00001003325
Deciphering Intratumoral Molecular Heterogeneity in Clear Cell Renal Cell Carcinoma with a Radiogenomics Platform

Intratumoral heterogeneity (ITH) challenges the molecular characterization of clear cell renal cell Carcinoma (ccRCC) with percutaneous biopsies and is a confounding factor in selection of molecular-targeted versus immune-based therapy. Magnetic Resonance (MR) Imaging can noninvasively assess the spatial landscape of the entire tumor. To validate MRI for ITH assessment, we implemented a radiogenomic platform through a systematic imaging based co-localization approach for multi region tissue acquisition from single tumors. We investigated if the spatial changes in imaging can predict the molecular changes using transcriptome and histopathological correlatives. Our study confirmed imaging heterogeneity as a predictor of molecular heterogeneity in ccRCC.
Study EGAS00001003846
Rapid response of APC/TP53/KRAS mutated stage IV colorectal cancer under FOLFIRI + Bevacizumab detected by liquid biopsy: a case report

In our non-interventional liquid biopsy study, a male patient in his fifties diagnosed with stage IV colorectal cancer and polytope liver metastases rapidly progressed after completing chemotherapy and deceased 8 months after diagnosis. Retrospective cell free DNA testing showed that the APC/TP53/KRAS major clone responded quickly after 3 cycles of FOLFIRI + Bevacizumab. Retrospective exome sequencing of pre-chemotherapy and post-chemotherapy tissue samples including metastases confirmed that the APC/TP53/KRAS and other major clonal mutations (GPR50, SLC5A, ZIC3, SF3A1 and others) were present in all samples. After the last chemotherapy cycle,
Study EGAS00001004088

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