14977 results for "cancer studies using rna-seq"

in 22.45 milliseconds.

• Achilles tendinopathy exome data

  Exemplar asymptomatic controls (n=10, 6 males) and exemplar cases with chronic Achilles tendinopathy (n=10, 6 males), representing divergent extremes of the phenotype spectrum were selected for WES. Individual samples were sequenced at paired ends on the Illumina HiSeq 2000/2500 platform at 30X coverage using the Agilent V5+UTR (71Mbp) capture kit.

  Dataset EGAD00001004362

• Exome-sequencing of H3-K27M glioma.

  Fastq or bam files are deposited for 28 patient H3-K27M diffuse midline gliomas. UMPEDD65 was profiled by targeted exome-sequencing using the TSO500 Illumina assay, while all other samples were sequenced by whole-exome sequencing.

  Dataset EGAD00001009269

• Low-coverage whole-genome sequencing (lcWGS) data of Genome in a Bottle (GIAB) reference samples

  This dataset contains low-coverage whole-genome sequencing (lcWGS) data generated from three GIAB reference samples (HG001–HG003) for method benchmarking and concordance analysis in FFPE-GWAS workflows. The data were generated using Illumina NovaSeq with paired-end 150bp reads and downsampled to 2x coverage.

  Dataset EGAD00001015533

• Whole exome sequencing of patient derived cell lines

  Whole exome sequencing of 3 patients derived cell lines and patient blood (N = 6 samples), performed using Agillent SureSelect All Exon V5 and Illumina HiSeq 4000. Data is in raw fastq format (N = 10 fastq pairs, 20 files total), as some samples were split between two lanes.

  Dataset EGAD00001007738

• Combined Metabolic Activators Reduces Liver Fat in Nonalcoholic Fatty Liver Disease Patients

  Metagenomics data for "Combined Metabolic Activators Reduces Liver Fat in Nonalcoholic Fatty Liver Disease Patients". Samples were sequenced on NovaSeq6000(NovaSeq Control Software 1.7.0/RTA v3.4.4) with a 151nt (Read1)-10nt(Index1)-10nt(Index2)-151nt(Read2) setup using ‘NovaSeqXp’ workflow in ‘S4’ mode flow cell.

  Dataset EGAD00001008142

• Germline variants in childhood melanoma

  Whole-exome sequencing was performed on DNA extracted from blood samples of 50 children diagnosed with cutaneous melanoma prior to 18 years of age. Patients were all diagnosed in Queensland, Australia, and self-reported as of European descent. Sequencing was done the Illumina platform using SureSelct V7 Post capture kits.

  Dataset EGAD00001010039

• sWGS of matched patient and PDX ovarian tumour tissues

  This dataset contains 8 .bam files of shallow WGS (~0.1×) from fresh frozen tumour tissues of four matched patients and first generation PDX models. Sequencing reads were aligned to the 1000 Genomes Project GRCh37-derived reference genome using the BWA aligner (v.0.07.17; CRUK-CI alignment pipeline).

  Dataset EGAD00001008650

• CD27hiCD38hi plasmablasts are activated B cells of mixed origin with distinct function

  Single cell sequencing analysis for Dengue patients using Smart-seq2 and 10X platforms

  Dataset EGAD00001007656

• Ashkenazi Jewish Leukoencephalopathy Syndrome

  Using whole exome sequencing (WES), we identified homozygosity for a missense variant, VPS11: c.2536T>G (p.C846G), as the genetic cause of a leukoencephalopathy syndrome in two individuals from two unrelated Ashkenazi Jewish (AJ) families. Both patients exhibited highly concordant disease progression characterized by infantile onset leukoencephalopathy with brain white matter abnormalities, severe motor impairment, cortical blindness, intellectual disability, and seizures.

  Dataset EGAD00001002005

• Whole genome sequencing of patient IPSCs and tumors (organoids)

  This dataset contains whole genome sequencing data of a patient IPS cell line with a heterozygous mutation in TSC2 (Patient 1 TSC2+/- iPSCs) . This dataset further contains whole genome sequencing data of two tumors showing CNLOH. Tumors were isolated from organoids grown using the patient IPS cell line (Patient 1 TSC2+/- iPSCs )

  Dataset EGAD00001006333

• 3/7 Psychiatric Genomics Consortium: Finding Actionable Variation

  The goal of this study was to generate new therapeutic hypotheses by targeted sequencing of 161 genes most likely to harbor schizophrenia (SCZ) causal variants in multi-ancestry schizophrenia case-control cohorts. The gene panel was intended to contain putative SCZ risk genes, from within which, the majority of new discoveries from additional WES/WGS would come. To this end, we integrated current knowledge of the genetic architecture of SCZ (results from The Schizophrenia Exome Sequencing Meta-Analysis Consortium, or SCHEMA) and gene membership in gene sets that have been implicated in SCZ using a Bayesian framework. A total of 23,352 individuals selected to be non-overlapping with SCHEMA, as well as other previous and ongoing sequencing efforts in the field, were identified from over 20 individual study sites. Sequencing of the exonic regions of 161 prioritized genes was performed on the Ion Torrent platform in between June 2018 and April 2019. Sequencing plates were matched with respect to ancestry and case/control composition whenever possible. The average sequencing depth across all samples was 224x. Single sample calling was performed using Torrent Variant Caller v5.8.0, which is specially optimized to exploit the underlying flow signal information generated by the Ion Torrent sequencing. The schizophrenia case-control status was obtained from each original study site.

  Study phs003138

• eMERGE Geisinger eGenomic Medicine (GeM) - MyCode Project Controls

  A research cohort of adult Geisinger Clinic patients was enrolled from community-based primary care clinics of the Geisinger Health System. Patients were eligible for enrollment if they were a primary care patient of a Geisinger Clinic physician and were scheduled for a non-emergent clinic visit. All participants provided written informed consent and HIPAA authorization. Consenting patient agreed to provide blood samples for broad biomedical research use, and permission to access data in their Geisinger electronic medical record for research. The enrollment rate was 90% of patients approached. The demographics of the cohort approximate those of the Geisinger Clinic outpatient population. Research blood samples were collected during an outpatient clinical phlebotomy encounter. Research blood samples are coded and stored in a central biorepository. Samples are linkable to clinical data in a de-identified manner for research via an IRB-approved data broker process. For genomic analysis, DNA is extracted from EDTA-anticoagulated whole blood. For the initial eMERGE Geisinger eGenomic Medicine (GeM) genotyping project, a subset of 1,232 unique samples were genotyped using Illumina HumanOmniExpress-12 v1.0 arrays, and used as population controls for other Geisinger Clinic case cohorts, including abdominal aortic aneurysm and gastric bypass surgery cases. These samples were selected from a larger subset of approximately 6,000 MyCode DNA samples using a partial matching algorithm that included age, sex, and body mass index as variables.

  Study phs000381

• PGRN-RIKEN: Genetic Determinants of Clinical Cardiovascular Events in Patients Receiving Statins

  Coronary heart disease (CHD) is an important public health problem in developed countries. Statins are effective in the prevention and treatment of CHD; nevertheless, many patients receiving statins still suffer cardiovascular events (CV) such as heart attack. Identifying genetic variants responsible for differential clinical responses to statins will not only allow individual patients at high residual risk to be targeted for additional therapies, but also will define new biologic pathways contributing to statin response, and thus new targets for future therapies. Accordingly, the goal of this study is to identify genetic variants associated with clinical CV in patients receiving statins. Subjects identified for study are of European descent and include 1718 subjects with CV while on statins (cases) and 4172 subjects without CV while on statins (controls). Key research resources utilized in this effort include VanderbiltD's BioVU DNA databank and associated Synthetic Derivative database of clinical information, and software tools developed to identify drugs and clinical events using Electronic Health Record-derived structured and unstructured ("free text") data. Most cases and controls identified include three data types: ICD-9 codes, medication regimens, and medical test results. Genotyping, using IlluminaD's Infinium HumanOmniExpressExome BeadChip (OmniExpressExome), was performed by the RIKEN Integrative Medical Sciences Center (IMS) and supported by the Pharmacogenomics Research Network (PGRN)-RIKEN IMS Global Alliance.

  Study phs000963

• INSIGHT (Intervention Nurses Start Infants Growing on Healthy Trajectories) Cohort

  This is a study of the biological risk factors for children enrolled in the INSIGHT (Intervention Nurses Start Infants Growing on Healthy Trajectories) study. INSIGHT is a randomized, controlled trial testing a responsive parenting intervention designed for the primary prevention of childhood obesity against a safety control. These first-born children were deeply studied in this time period with data collected on a wide variety of variables including mode of delivery, gender, weight and height (collected at 7 time points), medication usage, diet information, and maternal health information (gestational weight gain, gestational diabetes, smoking during pregnancy). This study includes a survey of the oral and gut microbiota from 226 mother-child dyads. It was designed to investigate the relationship between a cross-sectional view of the child's microbiome (at two years of age) and the patterns of growth between birth and 2 years. Microbiome samples from children (buccal swab and stool sample) and their mothers (buccal swab) are collected at the children's 2-year clinical research visit. Stool metabolites have also been assayed for a subset of the 226 children using 1H-NMR. Additionally, we genotyped the same individuals for SNPs across the genome. For a subset of 48 individuals we have added second-born siblings. For these additional 48 children, we characterized the methylation pattern across the genome using cord blood and placenta samples.

  Study phs001498

• MRCA and MRCE SNP genotypes

  Gene expression levels can be an important link DNA between variation and phenotypic manifestations. Our previous map of global gene expression based on approximately 400K SNPs and 50K transcripts in 400 sib pairs from the MRCA family panel has been widely used to interpret the results of GWAS. Here, we more than double the size of our initial dataset with expression data on 550 additional individuals from the MRCE family panel using the Illumina whole genome expression array. We have used new statistical methods for dimension reduction to account for non-genetic effects in estimates of expression levels and we have also included SNPs imputed from the 1000 Genomes Project. Our methods reduced false discovery rates and increased the number of eQTLs mapped either locally or at a distance (i.e. in cis or trans) from 1,534 in the MRCA dataset to 4,452 (with <5% FDR). Imputation of 1000 Genomes SNPs further increased the number of eQTLs to 7,302. Using the same methods and imputed SNPs in the newly acquired MRCE dataset we identified eQTLs for 9000 genes. The combined results identify strong local and distant effects for transcripts from 14,177 genes. Our eQTL database (http://www.hsph.harvard.edu/faculty/liming-liang/software/eqtl/) based on these results is freely available to help define the function of disease-associated variants.

  Study EGAS00000000137

• Genetic insights into the biological mechanisms governing human ovarian ageing

  Reproductive longevity is critical for fertility and impacts healthy ageing in women, yet insights into the underlying biological mechanisms and treatments to preserve it are limited. Here, we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in ~200,000 women of European ancestry. These common alleles influence clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. Identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increase fertility and extend reproductive life in mice. Causal inference analyses using the identified genetic variants indicates that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases risks of hormone-sensitive cancers. These findings provide insight into the mechanisms governing ovarian ageing, when they act across the life-course, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

  Study EGAS00001004947

• Cell-free DNA fragmentation patterns and personalized sequencing reveal circulating tumor DNA in urine and plasma of glioma patients

  Glioma-derived cell-free DNA (cfDNA) is challenging to detect using liquid biopsy as levels in body fluids are low. We determined the glioma-derived DNA fractions in tumor biopsies, in cerebrospinal fluid (CSF), plasma and urine samples, using deep sequencing of personalized capture panels. By sequencing cfDNA across thousands of mutations identified individually in each patient’s matched tumor we detected tumor-derived DNA in plasma (10/12) and urine samples (8/11). The median tumor fraction was 6.4x10-3 in CSF, 3.1x10-5 in plasma and 4.7x10-5 in urine. We identified a shift in the size distribution for mutant cfDNA fragments in these body fluids. Next, we analyzed cfDNA fragment sizes with paired-end shallow whole genome sequencing (WGS) in urine samples from 35 patients with gliomas, 8 individuals with non-malignant brain disorders, and 26 controls (n=69 individuals, 96 samples). cfDNA in urine of glioma patients was significantly more fragmented compared to urine from patients with non-malignant brain disorders (t-test, p=1.7x10-2) and compared to urine of controls (t-test, p=5.2x10-9). The proportion of DNA fragments &lt;60 bp was higher in glioma patients urine and could be used for classification (AUC=0.93). Machine learning models integrating fragment lengths could identify urine samples from glioma patients (AUC=0.97 in cross-validation).

  Study EGAS00001004355

• Sequencing to Guide Cancer Care (CanSeq)

  The overall goal of the CanSeq U01 project is to study the impact of whole-exome sequencing (WES) on the clinical care of cancer patients and oncology provider practices. The aims of Project 1 are to implement and establish the feasibility of germline and somatic WES in patients with advanced solid tumors (lung and colon); to develop a framework for interpreting and reporting for exome sequencing data; to determine the proportion of patients with &#34;actionable items&#34; compared to existing technologies; and to report on the percentage of patients in whom unique WES findings led to a clinical action. The aims of Project 2 are to implement a production-scale platform for WES from archival (FFPE) material; to identify biologically relevant somatic and germline alterations existing in tumor/normal DNA from individual patients; to produce an evidence-based list of clinically &#34;actionable&#34; genetic alterations; and to develop inferential models that predict the utility of tumor genomic data within the larger clinical context. The goals of Project 3 are to describe the impact of information derived through WES on cancer patients; to test the hypothesis that patients will want to receive information about all potentially informative somatic and germline variants; to study patients&#39; understanding of disclosed genomic information; and to describe the experiences of oncology providers as they implement WES into cancer care delivery.

  Study phs001075

• CRU-Ukrainian National Research Center for Radiation Medicine Trio Study

  Data on transgenerational effects following nuclear accidents are important for understanding fully the consequences of parental exposure to ionizing radiation. Few studies to date have had adequate statistical power to detect effects of the magnitude expected based on animal data, and most have not been of low-dose, protracted exposures associated with nuclear accidents and their aftermath. Although, to date, scant use has been made of the new genomic technologies, in Chernobyl-exposed areas of Ukraine and Belarus, excess minisatellite mutations have been seen in children born after the accident. We propose a study of parent-child trios in which at least one parent was exposed to Chernobyl radiation as a clean-up worker (mean dose&#62;&#61;100 mGy) and&#47;or evacuee from a contaminated area (mean &#62;&#61;50 mGy). The specific aims are to investigate the transgenerational and de novo mutation rates of the spectrum of genetic variants in trios, in particular looking at effects in children and mapping them to possible parental origin of the chromsoome. Together with long-term collaborators at the Research Center for Radiation Medicine (RCRM) in Kiev, epidemiologic data will be collected for up to 450 trios of parents with preconceptional doses and their unexposed offspring. We will use state-of-the-art genomic technologies to characterize the landscape of the genomes of the trios to determine whether parental radiation exposure is associated with genetic mutations transmitted to the offspring, by examining de novo mutation rates, minisatellite mutations, copy number alterations, and variations in telomere length. The analysis will be conducted in peripheral blood and/or buccal samples (when blood is not available) from complete father-mother-child trios. Doses to the gonads from the time of the accident to the time of conception will be reconstructed for all parents using existing records supplemented by interview data. Trio subjects will be selected from representative populations exposed to radiation from Chernobyl who are under active follow-up in the Clinico-Epidemiologic Registry at RCRM. To help identify specific effects of paternal and maternal radiation exposure, we will initially select sets of trio subjects in five categories: (1) exposed father, unexposed mother; (2) unexposed father, exposed mother; (3) both parents exposed; (4) both parents unexposed; and (5) a group of high dose &#34;emergency workers&#34; with acute radiation syndrome. All trio members will be invited to the RCRM outpatient clinic for collection of a 20 ml blood sample (or buccal cells for those who refuse phlebotomy). Both parents will be asked to complete a general questionnaire to obtain demographic and lifestyle data. Then one or both will complete detailed dosimetry questionnaires, based on forms used in previous collaborations with RCRM and administered by specially trained interviewers. Once 50 trios have been recruited (10 from each of the 5 exposure categories), we will conduct an interim evaluation of participation rates, sample collection and quality, and dose reconstruction in order to modify the protocol as needed. The analytical approach will be to correlate the extent, especially for de novo events of genetic alterations in the offspring with parental pre-conceptional radiation dose overall and by parental origin. The statistical power in relation to de novo mutations is very high, in excess of 90&#37;, but somewhat lower for trends in minisatellite mutations. Study findings will contribute importantly to knowledge of the heritable effects of moderate- and low-dose radiation exposure in humans and to radiation risk projection. Eventually data from the Trio Study may be shared with the international community through dbGap.

  Study phs001163

• NHLBI TOPMed - NHGRI CCDG: The BioMe Biobank at Mount Sinai

  The IPM BioMe Biobank, founded in September 2007, is an ongoing, broadly-consented electronic health record (EHR)-linked clinical care biobank that enrolls participants non-selectively from the Mount Sinai Medical Center patient population. BioMe currently comprises &gt;42,000 participants from diverse ancestries, characterized by a broad spectrum of longitudinal biomedical traits. Participants are enrolled through an opt-in process and consent to be followed throughout their clinical care (past, present, and future) in real-time, allowing us to integrate their genomic information with their EHRs for discovery research and clinical care implementation. BioMe participants consent for recall, based on their genotype and/or phenotype, permitting in-depth follow-up and functional studies for selected participants at any time. Phenotypic and genomic data are stored in a secure database and made available to investigators, contingent on approval by the BioMe Governing Board. BioMe uses a "data-broker" system to protect confidentiality. Ancestral diversity - BioMe participants represent a broad racial, ethnic and socioeconomic diversity with a distinct and population-specific disease burden. Specifically, BioMe participants are of African (AA), Hispanic/Latino (HL), European (EA) and other/mixed ancestry. BioMe participants are predominantly of African (AA, 24%), Hispanic/Latino (HL, 35%), European (EA, 32%), and other ancestry (OA, 10%). Participants who self-identify as Hispanic/Latino further report to be of Puerto Rican (39%), Dominican (23%), Central/South American (17%), Mexican (5%) or other Hispanic (16%) ancestry. More than 40% of European ancestry participants are genetically determined to be of Ashkenazi Jewish ancestry. With this broad ancestral diversity, BioMe is uniquely positioned to examine the impact of demographic and evolutionary forces that have shaped common disease risk. Phenotypes available in BioMe - BioMe has a high-quality and validated set of fully implemented clinical phenotype data that has been culled by a multi-disciplinary team of experienced investigators, clinicians, information technologists, data-managers, and programmers who apply advanced medical informatics and data mining tools to extract and harmonize EHRs. BioMe, as a cohort, offers a great versatility for designing nested case-control sample-sets, particularly for studying longitudinal traits and co-morbidity in disease burden. Biomedical and clinical outcomes: The BioMe Biobank is linked to Mount Sinai's system-wide Epic EHR, which captures a full spectrum of biomedical phenotypes, including clinical outcomes, covariate and exposure data from past, present and future health care encounters. As such, the BioMe Biobank has a longitudinal design as participants consent to make all of their EHR data from past (dating back as far as 2003), present and future inpatient or outpatient encounters available for research, without restriction. The median number of outpatient encounters is 21 per participant, reflecting predominant enrollment of participants with common chronic conditions from primary care facilities. Environmental data: The clinical and EHR information is complemented by detailed demographic and lifestyle information, including ancestry, residence history, country of origin, personal and familial medical history, education, socio-economic status, physical activity, smoking, dietary habits, alcohol intake, and body weight history, which is collected in a systematic manner by interview-based questionnaire at time of enrollment. The IPM BioMe Biobank contributed ~10,600 DNA samples for whole genome sequencing to the TOPMed program. Samples were selected for the Coronary Artery Disease (CAD) and the Chronic Obstructive Pulmonary Disease (COPD) working groups. Using a Case-Definition-Algorithm (CDA), we identified ~4,100 individuals with CAD (~50% women) and ~3,000 individuals as controls (65% women). In addition, we identified ~800 individuals with COPD (62% women) and 1800 individuals as controls (72% women). Another 600 BioMe participants with Atrial Fibrillation, all of African ancestry, were included.

  Study phs001644

• Memorial Sloan Kettering Cancer Center - Human Oncology &amp; Pathogenesis Program (HOOP) - Data Access Committee

  Dac EGAC00001000305

• Functional Genomics Laboratory, Kolling Institute of Medical Research DAC - TP53 mutation data in ovarian cancer

  Dac EGAC00001000589

• The data access committee for genome-wide cell-free DNA fragmentation in patients with cancer

  Dac EGAC00001001180

• Somatic pathogenic variants in the normal mammary gland of sporadic breast cancer patients.

  Dac EGAC00001002391

• DAC Molecular heterogeneity and commonalities in pancreatic cancer precursors with gastric and intestinal phenotype

  Dac EGAC00001002978

• NPY methylated ctDNA is a promising biomarker for treatment response monitoring in metastatic colorectal cancer

  Dac EGAC00001003001

• EGAD00010000526

  SNP 6.0 arrays of small cell lung cancer

  Dataset EGAD00010000526

• Microbiome confounders and quantitative profiling challenge established microbial targets in colorectal cancer developmental stages

  Study EGAS00001007413

• Genomic validation of the revised Bethesda criteria in terms of pathogenesis and oncologic significance

  Study EGAS00001003959

• Accurate mutation detection in leukemia by re-sequencing a cancer gene set

  Study EGAS00001000268