Search Results - EGA European Genome-Phenome Archive

Normal brain controls for ICGC PedBrain DNA methylation sequencing

DNA methylation profiling of 8 control samples from adult (4) and fetal brain (4) used, for example, for the following studies: Mack, Witt, et al. Epigenomic alterations define lethal CIMP-positive ependymomas of infancy. Nature 506(7489):445-450, 2014 (see EGAS00001000443) Hovestadt, et al. Decoding the regulatory landscape of medulloblastoma using DNA methylation sequencing. 510(7506):537-541, 2014 (see EGAS00001000561)

Study EGAS00001000909

March 2019 data update for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

March 2019 data update for cord blood CD34+CD38-, CMP, GMP, MEP, monocyte, erythroid precursor, B cell and primary AML total blasts reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium. This dataset contains data for samples: CEMT0158 CEMT0159 CEMT0160 CEMT0161 CEMT0162 CEMT0163 CEMT0164 CEMT0165 CEMT0166 CEMT0167 CEMT0168 CEMT0169 CEMT0170 CEMT0171 CEMT0172 CEMT0189

Dataset EGAD00001004950

DAC for study CMMRD–associated high-grade glioma

This Data Access Committee (DAC) is responsible for de-identified, summarized somatic variant call data derived from paired tumor–blood Whole-exome sequencing of human samples in a glioma research study. Access requests are approved without additional restrictions and are granted solely for health-related research purposes.

Dac EGAC50000000855

Long-read whole genome sequencing as a tool for variant detection in inherited retinal dystrophies

WGS sequencing using nanopore long reads sequencing. These data is used for the diagnosis of patients with inherited retinal dystrophies.

Study EGAS50000000846

Whole Genome Sequencing for Korean Diffuse Gastric Cancer

Fastq files for the whole genome sequencing data (Illumina HiSeq 2500; 32.6-fold) for two diffuse gastric cancers revealing the fusion breakpoints. 2102T: CTNND1-ARHGAP26 gene fusion (g.chr11:57,578,103-g.chr5:142,358,707) 354T: ANXA2-MYO9A gene fusion (g.chr15:60,656,550-g.chr15:72,157,966)

Dataset EGAD00001003953

The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia

RNA-seq data for ALL patients as described in "The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia"

Dataset EGAD00001006335

Hyperpolarized carbon-13 MRI for very early response assessment of neoadjuvant chemotherapy in breast cancer patients

Transcriptomic data for five patients with breast cancer undergoing neoadjuvant chemotherapy and hyperpolarised 13C-MRI for early response assessment

Dataset EGAD00001008141

First genome-wide association study in an Australian Aboriginal population provides insights into genetic risk factors for Body Mass Index and Type 2 Diabetes

A body mass index (BMI) >22kg/m2 is a risk factor for type 2 diabetes (T2D) in Aboriginal Australians. To identify loci associated with BMI and T2D we undertook a genome-wide association study using 1,355,133 quality-controlled single nucleotide polymorphisms (SNPs) genotyped (Illumina 2.5M Duo Beadchip) in 402 individuals in extended pedigrees from a Western Australian Aboriginal community. Imputation using the thousand genomes (1000G) reference panel extended the analysis to 6,724,284 post quality-control autosomal SNPs. No associations achieved genome-wide significance, commonly accepted as P<5x10-8. Nevertheless, genes/pathways in common with other ethnicities were identified despite the arrival of Aboriginal people in Australia >45,000 years ago. The top hit (rs10868204 Pgenotyped=1.50x10-6; rs11140653 Pimputed_1000G=2.90x10-7) for BMI lies 5’ of NTRK2, the type 2 neurotrophic tyrosine kinase receptor for brain-derived neurotrophic factor (BDNF) that regulates energy balance downstream of melanocortin-4 receptor (MC4R). PIK3C2G (rs12816270 Pgenotyped=8.06x10-6; rs10841048 Pimputed_1000G=6.28x10-7) was associated with BMI, but not with T2D as reported elsewhere. BMI also associated with CNTNAP2 (rs6960319 Pgenotyped=4.65x10-5; rs13225016 Pimputed_1000G=6.57x10-5), previously identified as the strongest gene-by-environment interaction for BMI in African-Americans. The top hit (rs11240074 Pgenotyped=5.59x10-6, Pimputed_1000G=5.73x10-6) for T2D lies 5’ of BCL9 that, along with TCFL2, promotes beta-catenin’s transcriptional activity in the WNT signaling pathway. Additional hits occurred in genes affecting pancreatic (KCNJ6, KCNA1) and/or GABA (GABRR1, KCNA1) functions. Notable associations observed for genes previously identified at genome-wide significance in other populations included MC4R (Pgenotyped=4.49x10-4) for BMI and IGF2BP2 Pimputed_1000G=2.55x10-6) for T2D. Our results may provide novel functional leads in understanding disease pathogenesis in this Australian Aboriginal population.

Study EGAS00001001004

Profiling RNA Translation in Pediatric Medulloblastoma

This study provides RNA-sequencing and ribosome profiling data for patient-derived cell lines and patient tissue samples for children with medulloblastoma. Ribosome profiling is a variant protocol of RNA-sequencing that directly sequences ribosome-bound RNA fragments only. Associated RNA-seq and Ribo-seq data obtained separately for some cancer cell lines can be found on the NCBI SRA as PRJNA957428. Samples were processed for poly-A mRNA sequencing using the Roche Kapa Kit. Ribosome profiling was performed as described in the manuscript referenced below (Hofman et al.) and based on the article by McGlincy et al., Methods (2017). Ribo-seq data were analyzed for sample quality using RiboseQC (Calviello, Nat Struct Mol Biol, 2020). These data were used to quantify P-sites of open reading frames. RNAseq and ribo-seq data were integrated and compared to determine translational efficiency values using TPM (Ribo-seq) over TPM (RNA-seq) as the metric. Ribo-seq data on 14 samples and RNAseq data on 21 samples derived from 16 fresh-frozen surgical samples for medulloblastoma and 5 autopsy samples are available through dbGaP. A second cohort of 4 medulloblastoma samples (RNAseq, Ribo-seq) related to this study can be found on the EGA at EGAS00001007426.

Study phs003446

This DAC takes care of requests for data for the Swiss epigenetic colorectal cancer cohort study, SWEPIC

Dac EGAC00001003471

Cell-free DNA methylation profiling for non-invasive detection and classification of lymphoma

Compared with traditional tissue biopsies used for lymphoma diagnosis, cell-free DNA methylation profiling offers a minimally invasive approach capable of capturing lymphoma-specific epigenetic alterations. This study investigates genome-wide methylation patterns in plasma using cell-free methylated DNA immunoprecipitation and sequencing (cfMeDIP-seq). Differential methylation analysis of discovery samples identified lymphoma-associated hypermethylated regions that were used to develop classification models for lymphoma detection. Validation analyses demonstrated high accuracy and strong associations between cfDNA methylation scores and independent measures of tumor burden and clinical outcome. These findings support cfDNA methylation profiling as a sensitive approach for non-invasive lymphoma diagnosis.

Study EGAS50000001463

Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomic Confirmatory Study of Breast, Colon, Lung, and Ovarian Tumors

Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.). The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein-protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the second phase of the CPTC initiative in September 2011. Renamed the Clinical Proteomic Tumor Analysis Consortium, CPTAC is beginning to leverage its analytical outputs from Phase I to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach is to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. The data contained in this dataset are derived from samples designed to confirm CPTAC findings from the TCGA samples. These confirmatory samples contain breast, ovarian, colon, and lung tumors collected via a protocol optimized for proteomics. Specifically, ischemic time of the sample was controlled and restricted to less than 30 minutes. ACGT, Inc. produced whole exome, mRNAseq, and miRNAseq for these samples. Corresponding proteomic data are available at: https://cptac-data-portal.georgetown.edu/cptacPublic/ The study design was to profile colon, breast, ovarian, and lung tumors both genomically and proteomically. Germline DNA was obtained from blood. Normal control samples for proteomics varied by organ site: adjacent colon tissue for colon cases, contralateral breast tissue for some breast cases, and Fallopian tube fimbria for some ovarian cases. Lung cases had no normal control for proteomic analysis. All cancer samples were derived from primary and untreated tumors.

Study phs000892

Resequencing (MIPS) of candidate genes for Keratoconus (2020)

In this study, we selected 34 candidate genes for KC based on previous Whole Exome Sequencing (WES) and the literature, and resequenced them in 745 KC patients and 810 ethnically matched controls. Data analysis was performed using the single variant association test as well as gene-based mutation burden and variance components tests. In our study, we detected enrichment of genetic variation across multiple gene-based tests for the genes COL2A1, COL5A1, TNXB, ZEB1 and ZNF469. The top hit in the Fisher’s exact test was obtained for a common variant in the COL12A1 gene. Interestingly, COL5A1, TNXB, ZNF469 and COL12A1 are all known Ehlers-Danlos Syndrome (EDS) genes. Though the co-occurrence of KC and EDS has been reported previously, this study is the first to demonstrate a consistent role of genetic variants in EDS genes in the etiology of KC. In conclusion, our data show a shared genetic etiology between KC and EDS, and clearly confirm the currently disputed role of ZNF469 in disease susceptibility for KC. Besides the role for EDS genes, we also confirm the previously reported involvement of genetic variation in ZEB1 in KC.

Study EGAS00001004267

DAC for present-day Central Asia genotype data at the Centre for GeoGenetics, Natural History Museum of Denmark.

Dac EGAC00001000894

DAC for "The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia"

Dac EGAC00001001501

Navarrabiomed DAC for XPAND project

This DAC is created for the XPAND project by the Translational Bioinformatics unit.

Dac EGAC50000000462

Leukemia Data Access committee for the deposited data. The committee consists of the principal investigators for the data set.

Dac EGAC00001003565

Inter and intra - tumor heterogeneity in Colorectal Cancer

The dataset consists of two main sample groups. 1) The inter-tumour sample group contains a total of 97 samples from 27 patients. Each patient has a single normal and primary sample as well as one or more metastases. All samples were sequenced using IonTorrent PGM and a custom colorectal cancer (CRC) panel. 2) The intra-tumour sample group contains a total of 68 samples from a single tumour as well as a normal tissue sample. All 68 samples were sequenced using IonTorrent PGM and a custom CRC panel. Shallow whole genome sequencing was additionally applied to 10 of the samples using Illumina HiSeq 4000.

Dataset EGAD00001003131

15407 results for "1 mil coins fc 26 Visit Buyfc26coins.com for latest FC 26 coins news..buoc"

in 57.51 milliseconds.