Search Results - EGA European Genome-Phenome Archive

Study for establishment for effective screening and diagnosis of Lynch syndrome

The purpose of this study is to establish efficient diagnostic procedure of the Lynch syndrome in Japan and to determine the MMR gene mutation spectrum and clinicopathologic characteristics.The person who is suspected Lynch Syndrome and gives informed consent for participation in this study .To carry out the project ?Construction of clinical and genetic integral information database to help Lynch syndrome management?, the following three are required. 1) screening for Lynch syndrome-suspected cases, 2) genetic testing to define Lynch syndrome, 3) integration of detailed clinical data of Lynch syndrome, and 4) The case which has not been diagnosed Lynch syndrome, is investigated causing gene.

Study JGAS000638

Isala Citizen Science Project: Cross-sectional branch

The Isala Citizen Science Project, is named after the first female doctor in Belgium, Isala Van Diest (1842-1916). In a co-creative way, volunteers provided samples and data, proposed research objectives and survey questions, and helped to disseminate and interpret the objectives and results through different media platforms, jointly breaking taboos on women’s and vaginal health. In Flow 1, we collected a single sample from a cross-section of the population, characterized the microbiome, and associated it with data collected in questionnaires. Here, we provide extensive sample meta-data for over 3000 women who completed questionnaires on their lifestyle, diet, health, contraceptive use and environment.

Study EGAS00001006934

Spatial and temporal genomic evolution in glioblastoma

Tumor heterogeneity is a challenging barrier to successful targeted therapy in glioblastoma. Identifying the mechanisms that drive cancer cells as they genetically evolve and adapt in response to treatment is a vital goal of modern cancer research. Analysis of sequencing data provides a method for uncovering the mechanisms sustaining tumor heterogeneity and driving evolution. Here, we analyzed genomic profiles of GBM biopsies taken from pre- and post-treatment GBMs (with matched germline controls), to understand 1) the intratumoral clonal compositions of primary GBM and 2) how GBM responds to therapeutic intervention. Our results provide a molecular portrait of GBM recurrence.

Study EGAS00001001033

HSC_population_dynamics___LEUK4_samples

My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

Study EGAS00001004247

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

HSC_population_dynamics___CB001_samples

My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

Study EGAS00001003397

Mutational signatures in head and neck cancer (H019)

Genomic alterations are a driving force in the multistep process of head and neck cancer (HNC) and result from the interaction of exogenous environmental exposures and endogenous cellular processes. Each of these processes leaves a characteristic pattern of mutations on the tumor genome providing the unique opportunity to decipher specific signatures of mutational processes operative during HNC pathogenesis and to address their prognostic value. Computational analysis of whole exome sequencing data of the HIPO-HNC (n=83) and TCGA-HNSC (n=506) cohorts revealed five common mutational signatures (COSMIC signature 1, 2, 3, 13 and 16), and demonstrated their significant association with etiological risk factors (tobacco, alcohol and HPV16).

Study EGAS00001004588

Genomic landscape of malignant peripheral nerve sheath tumor (MPNST)

Neurofibromatosis type 1 (NF1) is the most common tumor predisposition syndrome, and is associated with an aggressive soft-tissue sarcoma, malignant peripheral nerve sheath tumours (MPNSTs), the greatest cause of morbidity and mortality in people with NF1. The only potentially curative therapy involves surgery which is not always possible. Even therapy with curative intent is associated with poor overall survival for both sporadic and NF1-related MPNSTs. The development of novel therapies has been largely hindered by a lack of understanding of the molecular events underpinning MPNST pathogenesis. This is a comprehensive multi-omic study of MPNST evolution based on whole genome sequencing and transcriptomic data.

Study EGAS00001006069

RNA-seq of uncultured CD112high and CD112low long-term(LT) human hematopoietic stem cells (HSC) and cultured and lentiviral transduced (CTRL, INKA1-OE) LT- and short-term HSC from umbilical cord blood

We performed RNA-sequencing to elucidate the biological pathways (1) altered by INKA1 overexpression in LT-HSC and ST-HSC that may contribute to the induced transient restraint in generating proliferative hematopoietic output in vivo and in vitro; and (2) that underlie the differential in vitro priming and regeneration phenotypes of CD112high and CD112low LT-HSC. Therefore, we prospectively isolated indicated subpopulations from 3 independent human umbilical cord blood pools and subjected them either to RNA-sequencing directly or following culture, lentiviral transduction and purification of the transduced cell fractions.

Study EGAS00001004768

Single-cell level characterization of B cell depletion and repopulation following rituximab in systemic lupus erythematosus

Rituximab, a CD20+ B cell depletion therapy, is frequently used in the treatment of systemic lupus erythematosus (SLE). However, variability in patient response highlights the need for a deeper understanding of the underlying immune cell dynamics of B cell depletion and repopulation. In this study, we conducted longitudinal single-cell profiling of nine SLE patients treated with rituximab from pretreatment to up to 15 months post-treatment. These were compared to eight healthy controls. We profiled PBMCs via 10X Genomics single-cell RNA, surface protein (CITE-seq), B cell receptor (BCR), and T cell receptor (TCR) sequencing and sequenced bulk BCR repertoires in parallel. For single cell sequencing, 10 pools were created with an equal number of cells from 4 samples each. Samples collected at different timepoints from the same patient were distributed across different pools to allow demultiplexing of individuals using genotypes captured from the scRNA-seq data. Libraries were pooled using a ratio of GEX:CITE:TCR:BCR=9:2:1:1 and were sequenced across two lanes of the NovaSeq 6000. For bulk BCR sequencing, individual samples were demultiplexed using primer barcodes and paired-end BCR amplicon reads were merged prior to submission; data are provided as unmapped single-end reads.

Dataset EGAD00001015817

Sleep Heart Health Study (SHHS-BioLINCC)

Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Related StudiesParent cohort phenotype data can be accessed through ARIC-BioLINCC, Framingham-BioLINCC, and CHS-BioLINCC. Objectives To determine the cardiovascular and other consequences of sleep-disordered breathing and to test whether sleep-disordered breathing is associated with an increased risk of coronary heart disease, stroke, all-cause mortality and hypertension by examining subjects from well-characterized and established epidemiologic cohorts. Background Obstructive sleep apnea syndrome (OSA) is a potentially debilitating condition characterized by repetitive episodes of apnea while asleep, nocturnal oxygen desaturation, excessive daytime sleepiness, and loud disruptive snoring. Epidemiologic data from middle-aged adults indicate that OSA is common, with prevalence rates of 4% in men and 2% in women. Prior studies implicated OSA as a risk factor for the development of hypertension, ischemic heart disease, congestive heart failure, stroke and consequently premature death. Questions arose as to whether an increased propensity for cardiovascular and cerebrovascular diseases was limited to only those with frank OSA or whether more subtle forms of sleep-disordered breathing (SDB) would also confer elevated risk. Further evidence was also needed to clarify whether, SDB, including OSA, is an independent risk factor for the development of cardiovascular or cerebrovascular disease. Known cardiovascular and cerebrovascular disease risk factors such as obesity and smoking are commonly present in those with SDB; therefore, apparent associations between SDB and cardiovascular and cerebrovascular diseases may have resulted from the effects of these concomitant risk factors. Moreover, there was no understanding as to whether such factors as race, age, gender, and prevalent cardiovascular or cerebrovascular disease might interact with SDB to alter future cardiovascular and cerebrovascular disease risk. Mechanisms underlying any propensity to develop cardiovascular or cerebrovascular disease with SDB had not been firmly established (Quan, et al., 1997, PMID: 9493915). Participants Participants in SHHS were recruited from nine existing NHLBI epidemiological studies in which data on cardiovascular risk factors had been collected previously. The “parent” cohorts included: Two sites of the Atherosclerosis Risk in Communities Study (ARIC) Three sites of the Cardiovascular Health Study (CHS) The Framingham Offspring Cohort The Strong Heart Study (SHS) sites in South Dakota, Oklahoma, and Arizona The New York Hypertension Cohorts The Tucson Epidemiologic Study of Airways Obstructive Diseases and the Health and Environment Study From these parent cohorts, a sample of participants who met the inclusion criteria (age 40 years or older; no history of treatment of sleep apnea; no tracheostomy; no current home oxygen therapy) was invited to participate in the baseline examination of the SHHS, which included an initial polysomnogram (SHHS-1). Several cohorts over-sampled snorers in order to increase the study-wide prevalence of sleep-disordered breathing. In all, 6441 individuals were enrolled between November 1, 1995 and January 31, 1998. During exam cycle 3 (January 2001-June 2003), a second polysomnogram (SHHS-2) was obtained in 3295 of the participants. Due to sovereignty issues, Strong Heart Study participants are not included in the shared SHHS data. Data from a total of 5839 participants (1920 ARIC, 1249 CHS, 997 Framingham Offspring and OMNI 1, and 1673 from other studies), consenting to share data are available. Design The Sleep Heart Health Study added in-home polysomnography to the data collected in each of the parent studies at a baseline SHHS exam and a follow-up approximately 4 years later. Using the Compumedics PS polysomnograph, sleep studies were obtained in an unattended setting, usually in the homes of the participants, by trained and certified technicians. The recording montage consisted of: C3/A2 and C4/A1 EEGs, sampled at 125 Hz right and left electrooculograms (EOGs), sampled at 50 Hz a bipolar submental electromyogram (EMG), sampled at 125 Hz thoracic and abdominal excursions (THOR and ABDO), recorded by inductive plethysmography bands and sampled at 10 Hz "airflow" detected by a nasal-oral thermocouple (Protec, Woodinville, WA), sampled at 10 Hz finger-tip pulse oximetry (Nonin, Minneapolis, MN) sampled at 1 Hz ECG from a bipolar lead, sampled at 125 Hz for most SHHS-1 studies and 250 Hz for SHHS-2 studies Heart rate (PR) derived from the ECG and sampled at 1 Hz body position (using a mercury gauge sensor) ambient light (on/off, by a light sensor secured to the recording garment)This montage provides data on the occurrence of sleep-disordered breathing, sleep stages, heart rate, oximetry and on arousals. Each participant in the parent studies was also asked to complete the Sleep Habits Questionnaire which covers usual sleep pattern, snoring, and sleepiness.

Study phs003637

EGAD00000000024

WTCCC2 project samples from National Blood Donors (NBS) Cohort

Dataset EGAD00000000024

methylation_predictive_case

Raw methylation from cervical samples of individuals who developed CIN 1-4 years after sampling.

Dataset EGAD00010002071

Major Depression: Stage 1 Genomewide Association in Population-Based Samples

Identification of genomic regions that confer susceptibility to or protection from major depressive disorder (MDD) via genomewide association. Consent groups and participant set Psychiatric and Related Somatic Conditions (PRSC): 3741 (1821 cases, 1822 controls, 98 others)

Study phs000020

SIGi001-A-13 / SAMEA104386250 WGS data

The iPSC line SIGi001-A-13 / SAMEA104386250 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-13 is available for research use at www.EBiSC.org.

Dataset EGAD50000001031

BIONi010-C-8 / SAMEA4454011 WGS data

The iPSC line BIONi010-C-8 / SAMEA4454011 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-8 is available for research use at www.EBiSC.org.

Dataset EGAD50000001028

BIONi010-C-3 / SAMEA4342740 WGS data

The iPSC line BIONi010-C-3 / SAMEA4342740 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-3 is available for research use at www.EBiSC.org.

Dataset EGAD50000001034

BIONi010-C-7 / SAMEA4454010 WGS data

The iPSC line BIONi010-C-7 / SAMEA4454010 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-7 is available for research use at www.EBiSC.org.

Dataset EGAD50000001035

BIONi010-C-6 / SAMEA4454009 WGS data

The iPSC line BIONi010-C-6 / SAMEA4454009 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-6 is available for research use at www.EBiSC.org.

Dataset EGAD50000001037

BIONi010-C-9 / SAMEA4454012 WGS data

The iPSC line BIONi010-C-9 / SAMEA4454012 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-9 is available for research use at www.EBiSC.org.

Dataset EGAD50000001040

SIGi001-A-3 / SAMEA4448571 WGS data

The iPSC line SIGi001-A-3 / SAMEA4448571 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-3 is available for research use at www.EBiSC.org.

Dataset EGAD50000001041

BIONi010-C-4 / SAMEA4452060 WGS data

The iPSC line BIONi010-C-4 / SAMEA4452060 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-4 is available for research use at www.EBiSC.org.

Dataset EGAD50000001043

EDi014-A / SAMEA4459369 WGS data

The iPSC line EDi014-A / SAMEA4459369 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-A is available for research use at www.EBiSC.org.

Dataset EGAD50000001051

EDi014-B / SAMEA4459371 WGS data

The iPSC line EDi014-B / SAMEA4459371 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-B is available for research use at www.EBiSC.org.

Dataset EGAD50000001053

SIGi001-A-7 / SAMEA4448730 WGS data

The iPSC line SIGi001-A-7 / SAMEA4448730 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-7 is available for research use at www.EBiSC.org.

Dataset EGAD50000001060

BIONi010-C-5 / SAMEA4452061 WGS data

The iPSC line BIONi010-C-5 / SAMEA4452061 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-5 is available for research use at www.EBiSC.org.

Dataset EGAD50000001062

BIONi010-C-2 / SAMEA4342705 WGS data

The iPSC line BIONi010-C-2 / SAMEA4342705 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-2 is available for research use at www.EBiSC.org.

Dataset EGAD50000001068

SIGi001-A-10 / SAMEA4451117 WGS data

The iPSC line SIGi001-A-10 / SAMEA4451117 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-10 is available for research use at www.EBiSC.org.

Dataset EGAD50000001074

SIGi001-A-12 / SAMEA104237570 WGS data

The iPSC line SIGi001-A-12 / SAMEA104237570 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-12 is available for research use at www.EBiSC.org.

Dataset EGAD50000001076

SIGi001-A-2 / SAMEA4451116 WGS data

The iPSC line SIGi001-A-2 / SAMEA4451116 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-2 is available for research use at www.EBiSC.org.

Dataset EGAD50000001077

SIGi001-A-6 / SAMEA4447426 WGS data

The iPSC line SIGi001-A-6 / SAMEA4447426 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-6 is available for research use at www.EBiSC.org.

Dataset EGAD50000001078

SIGi001-A-4 / SAMEA4448632 WGS data

The iPSC line SIGi001-A-4 / SAMEA4448632 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-4 is available for research use at www.EBiSC.org.

Dataset EGAD50000001088

SIGi001-A-5 / SAMEA4448708 WGS data

The iPSC line SIGi001-A-5 / SAMEA4448708 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-5 is available for research use at www.EBiSC.org.

Dataset EGAD50000001092

SIGi001-A-8 / SAMEA4448777 WGS data

The iPSC line SIGi001-A-8 / SAMEA4448777 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-8 is available for research use at www.EBiSC.org.

Dataset EGAD50000001093

SIGi001-A-9 / SAMEA4447499 WGS data

The iPSC line SIGi001-A-9 / SAMEA4447499 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-9 is available for research use at www.EBiSC.org.

Dataset EGAD50000001095

Tumor Profiler Project - OV bulk transcriptomics data additional samples

The dataset contains bulk transcriptomics data from 4 samples from 3 different patients with ovarian cancer. 3 samples were collected from the tumor, 1 sample from ascites. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format. These samples are from patients not classified as as having high-grade serous adenocarcinoma.

Dataset EGAD50000001411

Whole exome sequence of human XXY fibroblasts

This dataset contains Whole exome sequence generated using human skin fibroblast sample (ID 419281) from Klinefelter XXY syndrome patient fibroblasts. These fibroblasts were used to generate autosomally isogenic human iPSCs. The sample DNA was collected using commercial kit and Human All Exon v5 capture paired library was sequenced using Illumina HiSeq device. The fastq file (ID 493224) and analysis (ID 3209) bam files have been deposited.

Dataset EGAD50000001362

6365 results for "11+1双色球多少钱一注"

in 18.10 milliseconds.