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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

Non-ADT METs ICGC Prostate UK

To characterize the subclonal genomic architecture of non-androgen-deprived metastatic prostate cancer, we performed whole-genome sequencing (WGS) of pelvic lymph node metastases and matching noncancerous blood from 10 patients to an average sequencing depth of 55x. The patients are part of PELICAN (Project to ELIminate Lethal Cancer) study led by G. Steven Bova at Johns Hopkins University (USA) and Tampere University (Finland). As of September 2020, study using these data is: Wedge et al, Nature Genetics 2018 (PMID: 29662167)
Dataset EGAD00001002002
microRNA-seq of human serum from a longitudinal study of 66 women with no history of cancer

This dataset includes microRNA sequencing data from 198 human serum samples, representing a subset of 66 women with no history of cancer who participated in the UKCTOCS study and with serum samples collected at three timepoints over a period of up to 5 years. Small RNA libraries prepared from the serum samples were sequenced with 50-bp single end reads on an Illumina HiSeq 2000 instrument. Data is provided as FASTQ files.
Dataset EGAD00001004348
PIVUS study - Longitudinal transcriptomics - Advanced aging

We performed RNA sequencing in whole-blood from the same 65 individuals from the PIVUS study at ages 70 and 80 (130 samples) to quantify how gene expression, alternative splicing, and their genetic regulation are altered during this 10-year period of advanced aging. Each individual has four fastq files, two for each age. Consecutive sample IDs refer to the sample individual, e.g. PIVUS003 and PIVUS004 are the age 70 and age 80 samples of the first individual.
Dataset EGAD00001004965
H3Africa Consortium WGS VCF

Joint called VCF for whole genome sequence data from 410 samples described in the paper: PMID:33116287. It includes 314 high coverage (average 30X) samples sequenced on the Illumina X-Ten, also available as individual datasets under the H3Africa Chip study (EGAS00001002976) and 112 medium coverage (average 10X) samples from the TrypanGen study (EGAS00001002602) sequenced on Illumina HiSeq 2500. Supplementary table 3 of the paper describes the geographic breakdown of the samples. 16 samples from the Southern African Human Genome project have been removed from this VCF.
Dataset EGAD00001008577
Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - RNA-Seq

This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.
Dataset EGAD00001011192
Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - Ribo-Seq

This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.
Dataset EGAD00001011193
RNA-seq dataset of A cycling, progenitor-like cell population at the root of atypical teratoid rhabdoid tumor subtype differentiation trajectories

Study describing the differentiation trajectory of atypical teratoid rhabdoid tumors (ATRTs) at single-cell level. This study describes how the differentiation trajectory differs per subtype of ATRTs, and how those findings could contribute to develop so-called "maturation therapy" tailored towards ATRTs.
Dataset EGAD00001015544
Whole-genome sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumoroids data. . This dataset contains all the data available for this study on 2025-09-30.
Dataset EGAD00001015707
Single-cell RNA-sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumouroids data. . This dataset contains all the data available for this study on 2025-09-30.
Dataset EGAD00001015708
Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.
Dataset EGAD00001015709

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