Search Results - EGA European Genome-Phenome Archive

Exome sequencing for heterogeneity and evolution of DNA mutation rates

Dataset comprising 27 pairs of high-depth (300x) WES results obtained from 54 PDXs derived from primary CRCs resected synchronously with their corresponding metastases. These exoms sequences are part of a larger study on the heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer.

Dataset EGAD50000000208

INCLIVA-CC-WES

This dataset consists of WES NGS paired-end raw data (FASTQ R1, R2 and UMI sequence) obtained from 25 localised colon cancer patients. Specifically, we have 25 primary tumor tissue samples, 17 metastatic tissues, 25 white blood cell samples, 25 plasma samples collected at relapse, 12 baseline plasma samples and 15 plasma samples post-surgery.

Dataset EGAD50000000293

D1D2 trial Whole Exome Sequencing (WES)

Surgical treatment of gastric cancer: 15-year follow-up results of the randomised nationwide Dutch D1D2 trial. Molecular characterisation of N=80 resectable gastric adenocarcinomas from D1D2 trial, describing mutations obtained by matched (Tumor-Normal) whole exome sequencing (WES). Samples are annotated for TCGA’s molecular classification (MSI, GS and CIN).

Dataset EGAD50000001144

Tumor Profiler Project - OV scRNA data

The dataset contains 10x Chromium single-cell transcriptomics data from 43 samples from 38 different patients with ovarian cancer. 36 samples were collected from the tumor, 7 samples from ascites. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format.

Dataset EGAD50000001290

Tumor Profiler Project - OV scDNA data

The dataset contains 10x Chromium single-cell DNA sequencing data from 42 samples from 38 different patients with ovarian cancer. 35 samples were collected from the tumor, and 7 samples from ascites. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format.

Dataset EGAD50000001291

Tumor Profiler Project - OV bulk transcriptomics data

The dataset contains bulk transcriptomics data from 39 samples from 36 different patients with ovarian cancer. 34 samples were collected from the tumor, 5 samples from ascites. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format.

Dataset EGAD50000001413

Identification of the genes associated with EGFR-mutant lung cancer

To gain an insight into the genetic factors underlying the carcinogenesis of EGFR-mutant lung adenocarcinoma, we sequenced the exomes in peripheral-blood DNA from the patients.

Study JGAS000129

Myeloma_Targeted_Follow_up_Study

390 samples, perform WGA, and send the WGA’d DNA to core for pre-capture library and tagging, pulldown with ELID 631172 (16 samples per reaction tube), and sequencing (24 samples per lane)

Study EGAS00001000880

Deep multi-region WGS of lung cancer tumours

Deep WGS (germline and 2-5 tumour regions) was performed on 20 patients: 13 lung adenocarcinoma, 5 squamous cell carcinoma, 2 small-cell lung cancers. A total of 68 BAM files are provided, where tumours were sequenced to 60x or 150x depth.

Dataset EGAD00001005287

Constit Genome Sequencing

WGS blood data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 67 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 100bp paired-end protocol to a minimum mean coverage of 30x.

Dataset EGAD00001003190

The identification of genetic vulnerabilities in head and neck cancers for the development of novel therapies (2020-01-15)

CRISPR/Cas9 lethality screens in a set of Asian head and neck cancer cell lines to identify novel targets. . This dataset contains all the data available for this study on 2020-01-15.

Dataset EGAD00001005784

41 CRC Exome bam + 4 CRC paired fastq from EGAS00001002477 study

This dataset contain 45 pairs of colorectal tumor and adjacent normal tissue. Four of them are from a previous study EGAS00001002477. For each sample a BAM was generated by aligning to GRCh37. Those colorectal cancer all have the MSI phenotype.

Dataset EGAD00001006666

Batches 4-6 prostatectomy analysis

Whole Genome Sequencing Illumina HiSeq data from 111 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy (target sequencing depth 50X) with matched blood control (target sequencing depth 30X). This data is from batches 4 to 6.

Dataset EGAD00001003225

Predictor_RIO_TNBC (2019-04-03)

In this study, samples fom a window study of the PARP inhibitor rucaparib in patients with primary triple negative or BRCA1/2 related breast cancer (RIO trial) will be investigated. Samples will undergo whole genome sequence and analysis, including use of HR Predict. . This dataset contains all the data available for this study on 2019-04-03.

Dataset EGAD00001004894

Whole genome sequencing of 40 gastric cancer tumours and matched normal samples from Singapore.

Genomic DNA of tumours and matched normal gastric tissues was extracted (QIAGEN). Libraries were constructed with 300-400 bp insert length, and 101bp or 151bp paired-end sequencing was performed on Illumina Hiseq instruments

Dataset EGAD00001004279

Ewings Sarcoma Rearrangement Screen

Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing's sarcoma tumours.

Dataset EGAD00001000389

RNAseq of patients with Ewings sarcoma

Cancer is driven my mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing's sarcoma tumours.

Dataset EGAD00001000444

Role_of_HPV_and_Interferon_in_APOBEC_mutational_signature

The aim of this project is to test whether HPV oncogenes and /or interferon induce the APOBEC mutational signature in vitro, and to test the role of APOBEC3A in this process.

Study EGAS00001002988

Targeted_NanoSeq_Sperm

Targeted NanoSeq in sperm samples provided by healthy patients. A custom-designed panel of ~200 genes will be used to achieve high depth coverage (aiming for ~1000X at panel sites).

Study EGAS00001005920

Single Cell Genome Sequence for DLP+ library A118368B

Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA605 passage 3 on DLP+ library A118368B

Dataset EGAD00001009432

Single Cell Genome Sequence for DLP+ library A96171A

Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 2, patient-derived xenograft SA611 passage 3 on DLP+ library A96171A

Dataset EGAD00001009458

Single Cell Genome Sequence for DLP+ library A96228A

Single Cell Genome Sequence for Immortalized lymphoblastoid cell line GM18507 cell line SA928,Triple negative breast cancer patient-derived xenograft SA609 passage 2 patient-derived xenograft SA609 passage 2 on DLP+ library A96228A

Dataset EGAD00001009645

Tumor Educated Platelets (TEPs) for breast cancer detection

The TEP dataset consists of 549 Fastq samples which are divided into two experiments: a training data cohort, used to train the classifier, and a validation data cohort, used to assess classifier performance

Dataset EGAD00001009790

Organoid Derivation Project - GRCh38 - TGS (2023-06-22)

Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients. . This dataset contains all the data available for this study on 2023-06-22.

Dataset EGAD00001011094

Organoid Derivation Pilot: RNAseq (2023-06-22)

Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients. . This dataset contains all the data available for this study on 2023-06-22.

Dataset EGAD00001011091

Single Cell Genome Sequence for DLP+ library A118790A

Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA610 passage 3, patient-derived xenograft SA1096C passage 1 on DLP+ library A118790A

Dataset EGAD00001009437

Whole exome sequencing of pdx models of 2 patients with metastatic colorectal cancer

Paired fastq files ( 12 pairs, WES) of EGFR treated and untreated PDX models of mCRCs of 2 patiens sequenced on Illumina HiSeq 2000, the enrichment kit was Agilent SureSelect V5+UTRs.

Dataset EGAD00001007713

Bulk RNAseq of Neuroblastoma patient's tumors

This dataset contains 9 bulk RNAseq of neuroblastoma patient's tumors used to compare with derived PDXs and/or single-cell data in the Thirant C et al, Nature Communications, 2023. They were intially produced for the Berlanga P., Cancer Discovery, 2022.

Dataset EGAD00001010287

FASTQ file for paper titled "Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression"

This data set includes 27 full-length transcript sequence generated from PacBio IsoSeq that were used for verify the cancer-specific exons identified in three genes: FN1, COL6A3 and TNC. The data were generated from PDX models of osteosarcoma patients.

Dataset EGAD00001015356

eMERGE Network Phase III Clinical Sequencing: eMERGEseq Panel

The Electronic Medical Records and Genomics (eMERGE) Network is a National Institutes of Health (NIH)-organized and funded consortium of U.S. medical research institutions. The primary goal of the eMERGE Network is to develop, disseminate, and apply approaches to research that combine biorepositories with electronic medical record (EMR) systems for genomic discovery and genomic medicine implementation research. eMERGE was announced in September 2007 and began its third phase in September 2015. eMERGE III consists of nine study sites, two central sequencing and genotyping facilities, and a coordinating center. eMERGE Phase III aims to: 1) sequence and assess the phenotypic implication of rare variants in a custom designed eMERGEseq panel consisting of 109 genes (including 56 ACMG actionable finding list genes and the top 6 genes from each site relevant to their specific aims), as well as approximately 1400 SNPs; 2) assess the phenotypic implications of these variants by developing, validating and implementing new phenotype algorithms, 3) integrate genetic variants into EMRs to inform clinical care; and 4) create community resources. Included in this study are: ~24,000 eMERGE participants from 10 eMERGE III study sites. Corresponding demographics, body mass index measurements. Top PheWAS codes generated from a collated list of ICD codes from all study sites. Study sites and participants include: Cincinnati Children's Hospital Medical Center (CCHMC): Cincinnati Children's Hospital Medical Center (CCHMC) is a not-for-profit hospital and research center pioneering breakthrough treatments, providing outstanding family-centered patient care and training healthcare professionals for the future, and dedicated to improving health and welfare of children and to the shared purpose of discovery and practical application of new genomic information to the ordinary care of children. We bring a comprehensive electronic health record (EPIC), a deidentified i2b2 data warehouse of 680K patient records, a biobank with >261,000 consents that allow return of results to >84,000 patients and guardians who have provided DNA samples, and hundreds of faculty and senior staff who make genomics or informatics an active focus of their research. CCHMC will help the eMERGE III Steering Committee identify genes for the eMERGE III targeted sequencing panel, provide 3,000 DNA samples from CCHMC patients to be sequenced, review targeted gene panels from clinical care at CCHMC for somatic mosaicism and reinterpretation, and further develop and disseminate a software workflow suite for sequence analysis. We will also extend our work generating phenotype algorithms using heuristic and machine learning methods to many new childhood diseases. We will develop tools to evaluate adolescent return of results preferences, examine the ethical and legal obligations and potential to reanalyze results, and develop clinical decision support for phenotyping, test ordering, and returning sequencing results. Children's Hospital of Philadelphia (CHOP): The Center for Applied Genomics (CAG) is a specialized Center of Emphasis at the Children's Hospital of Philadelphia (CHOP), and one of the world's largest genetics research programs, with to state-of-the-art high-throughput sequencing and genotyping technology. Our primary goal is to translate basic research findings to medical innovations. We aim to develop new and better ways to diagnose and treat children affected by rare and complex medical disorders, including asthma, autism, epilepsy, pediatric cancer, learning disabilities, and a range of rare diseases. Ultimately, our objective is to generate new diagnostic tests and to guide physicians to the most appropriate therapies. Participants were recruited from the CAG biorepository (n>450,000), specifically from >100,000 CHOP pediatric patients and family members, which is enriched for rare-diseases (n>12,000). Center for Applied Genomics, The Children's Hospital of Philadelphia We gratefully thank all the children and their families who enrolled in this study, and all individuals who donated blood samples for research purposes. Genotyping for this project was performed at the Center for Applied Genomics and supported by an Institutional Development Award from The Children's Hospital of Philadelphia. Sequencing was supported by the National Institutes of Health through an award from the National Human Genome Research Institute's Electronic Medical Records and Genomics (eMERGE) program (U01HG008684). Columbia University: The goal of the Columbia eMERGE III project is to develop methods for integrating genomic data in EHRs and to study the impact of such genomic informatics interventions on the health of a diverse, underserved urban adult English- and Spanish-speaking patient population in Northern Manhattan served by Columbia University Medical Center/New York-Presbyterian Hospital system. The study group is 2500 patients recruited from diverse clinics and community outreach centers of self-reported White (~61%), Asian (~11%), African-American (~11%), American Indian/Alaska Native (<1%) racial and Hispanic (~33%) ethnic backgrounds. There are two subgroups in the study cohort - a retrospective group (N=1052) that includes patients from oncology and nephrology clinics, and a prospective one (N=1448) that includes healthy individuals as well as participants with diverse medical conditions. Confirmed pathogenic variants in 70 selected genes will be returned to participants and their healthcare providers through the EHR integration. Participants are able to choose the results they receive and will have the freedom to meet with a genetic counselor and a geneticist to review results. The impact of genetic testing on clinical care is determined by periodic monitoring of EHRs. Geisinger: Samples and phenotype data in this study were provided by the Geisinger MyCode® Community Health Initiative. Participants are recruited across the Geisinger System via online consents or in-person consents at a hospital or clinic visit. Enrollment is ongoing with over 100,000 individuals currently consented. Partners Healthcare (Harvard University): The Partners HealthCare Biobank is a large research program designed to help researchers understand how people's health is affected by their genes, lifestyle, and environment. This large research data and sample repository provides access to high-quality, consented blood samples to help foster research, advance our understanding of the causes of common diseases, and advance the practice of medicine. For the Partners research community (Massachusetts General Hospital and Brigham and Women's Hospital), the Biobank provides: Banked samples (plasma, serum, and DNA) collected from consented patients Blood samples that were discarded after clinical testing in the Crimson Cores maintained in the Brigham and Women's Hospital and Massachusetts General Hospital Pathology Departments Sample handling and preparation services Link to the biobank data to the Partners Research Patient Data Registry (RPDR) a research instance of our electronic clinical chart Data access through our research portal. To date, over 70,000 Partners patients have given their consent to enroll, give a blood sample, receive research results and agreed to be re-contacted for additional research studies. The Biobank has enabled Partners investigators to compete for nationally recognized grants in personalized medicine such as a clinical electronic Medical Records and Genomics network (eMERGE) site and the national All of US program. The Biobank currently supports over 120 Partners investigators and over 130 million dollars in NIH research. Kaiser Permanente Washington/ (KPWA) / University of Washington (UW): KPWA participants were enrolled in the eMERGE Network through the Northwest Institute of Genetic Medicine (NWIGM) biorepository, and provided the appropriate consent to receive clinically relevant genetic results (N=2,500.) NWIGM is based at the University of Washington and co-managed by the University of Washington and KPWA. The purpose of the NWIGM biorepository is to build infrastructure and resources to carry out a broad range of future genetic research. KPWA members enrolled in the biorepository are asked to provide informed consent to providing a DNA sample for storage in the NWIGM biorepository. The consent is purposefully broad to serve the dual purpose of reducing the burden on researchers who wish to use this biorepository and the IRB committees who will be responsible for reviewing these requests in the future. Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in KPWA's integrated group practice, and had completed an online Health Risk Appraisal. The selection algorithm was based on several data sources from the EHR at KPWA. 1) Demographics - participants with self-reported race as Asian ancestry were prioritized and selected to enrich for non-European ancestry. The KPWA eMERGE cohort includes N=1,245 members of Asian ancestry. 2) Participants were also selected for a history of colorectal cancer (N=1,255), in order to allow us to enrich germline pathogenic variants. Mayo Clinic: The Return of Actionable Variants Empirical (RAVE) Study was approved by the Mayo Clinic IRB. We recruited 2537 participants from Mayo Clinic biobanks in Rochester, MN, who had hypercholesterolemia or colon polyps, thereby enriching for Familial hypercholesterolemia (FH) and monogenic causes of colorectal cancer (CRC). Additional eligibility criteria were: 1) residents of Southeast MN who were alive and aged 18-70 years; 2) LDL-C level >155 or >120 mg/dl while on lipid-lowering therapy; 3) no known cause of secondary hyperlipidemia; and 4) no cognitive impairment or dementia that would compromise their ability to give written informed consent. Based on these criteria, we identified 5270 eligible patients and obtained informed consent from 3030 participants. Recruitment was conducted in waves and utilized mailed recruitment packets consisting of a study brochure, a written informed consent form, a baseline psychosocial questionnaire, and a return postage-paid envelope. DNA of 2537 participants was sent for CLIA-certified targeted sequencing of 109 genes including genes associated with FH and CRC. Targeted sequencing and genotyping was performed in a Central Laboratory Improvement Amendment (CLIA)-certified laboratory. Northwestern University: Samples and data used in this study were obtained from patients from Northwestern Medicine, an integrated healthcare system, formed through a partnership of Northwestern Memorial HealthCare and Northwestern University Feinberg School of Medicine. Participants include a retrospective cohort from the Northwestern Pharmacogenomics Study, funded through the eMERGE II project, NHGRI (3U01HG006388-02S1) and a prospective cohort from the Genetic Testing and Your Health Study, funded through the eMERGE III project, NHGRI (U01HG008673). Patients were eligible to participate if they were18 years or older and see a physician at Northwestern Medicine. Patients consented to genetic testing and to allow their results to be placed in their electronic medical record. Vanderbilt University Medical Center: Vanderbilt University Medical Center (VUMC) participants were enrolled in the eMERGE Network through the Vanderbilt Genome-Electronic Records (VGER) project. Patients were provided the appropriate consent to receive clinically relevant genetic results (N=2,700). Participants were eligible if aged 21 or over, had a healthcare provider at VUMC, and visited the provider at least 3 times in the past 3 years. Meharry Medical College: Inclusion of ethnic groups in genomic research is critical to identify possible reasons for health disparities. African-Americans are being enrolled in various outpatient clinics of Nashville General Hospital at Meharry, an inner city hospital primary serving a poorer patient group. A total of 500 African Americans with four cancer types demonstrating health disparities in this population - prostate, colon, breast, lung are identified and approached by clinical research coordinators. The purpose of the study is to determine if any genetic information can be identified from these patients who have or are at high risk of one of these disparate cancers. All participants provide written informed consent and HIPAA authorization to provide blood samples for broad research use and permission to access data in their hospital electronic medical record for research now and in the future. An extensive demographic profile is obtained and entered into a REDCap database. Blood samples are obtained for a panel of alleles from extracted DNA at Baylor. In addition, de-identified coded samples are processed and stored in a central biorepository for further DNA, RNA and proteomic analyses. The survey and phlebotomy are performed at the time of the initial contact and agreement to participate. Nearly all patients approached willingly agree to participate for potential benefit to themselves, family members, or humankind. Little concern is voiced of providing samples for genetic analysis. Study investigators will share results with the participants and providers if testing does not indicate high risk. Results indicating increased risk or actionable alleles for the patient and/or family will be returned by a genetic counselor. Monitoring of the patients' health in this cohort will continue to be followed in the EMR to identify any future associations that might explain health disparities in African Americans. Proposals will be reviewed from investigators to study the genetic or proteomic samples as well as the clinical and demographic information in the repository. Please note that this version of the dataset has a handful of mismatches between genotyped and provided sex. Data with the following IDs should be removed prior to analysis: 420252874213744142412243424569384245694642672223

Study phs001616

14970 results for "cancer studies using rna-seq"

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