Search Results - EGA European Genome-Phenome Archive

Osteoporotic Fractures in Men (MrOS)

The Osteoporotic Fractures in Men Study (MrOS) is a multi-center prospective, longitudinal, observational study of risk factors for vertebral and all non-vertebral fractures in older men, and of the sequelae of fractures in men. The original specific aims of the study include: (1) to define the skeletal determinants of fracture risk in older men, (2) to define lifestyle and medical factors related to fracture risk, (3) to establish the contribution of fall frequency to fracture risk in older men, (4) to determine to what extent androgen and estrogen concentrations influence fracture risk, (5) to examine the effects of fractures on quality of life, (6) to identify sex differences in the predictors and outcomes of fracture, (7) to collect and store serum, urine and DNA for future analyses as directed by emerging evidence in the fields of aging and skeletal health, and (8) define the extent to which bone mass/fracture risk and prostate diseases are linked. The MrOS study population consists of 5,994 community dwelling, ambulatory men aged 65 years or older from six communities in the United States (Birmingham, AL; Minneapolis, MN; Palo Alto, CA; Monongahela Valley near Pittsburgh, PA; Portland, OR; and San Diego, CA). Inclusion criteria were designed to provide a study cohort that is representative of the broad population of older men. The inclusion criteria were: (1) ability to walk without the assistance of another, (2) absence of bilateral hip replacements, (3) ability to provide self-reported data, (4) residence near a clinical site for the duration of the study, (5) absence of a medical condition that (in the judgment of the investigator) would result in imminent death, and (6) ability to understand and sign an informed consent. To qualify as an enrollee, the participant had to provide written informed consent, complete the self-administered questionnaire (SAQ), attend the clinic visit, and complete at least the anthropometric, DEXA, and vertebral X-ray procedures. There were no other exclusion criteria. The baseline examination was completed over a 25-month period from March 2000 to April 2002. Participants completed questionnaires regarding medical history, medications, physical activity, diet, alcohol intake, and cigarette smoking. Objective measures of anthropometric, neuromuscular, vision, strength, and cognitive variables were obtained at a clinic visit. Skeletal assessments included DEXA, calcaneal ultrasound, and vertebral radiographs. Vertebral and proximal femoral QCT was performed on a subset (65%) of participants. Serum, urine, and whole blood specimens were collected. During the study period, participants complete a tri-annual questionnaire every four months that obtains information concerning the occurrence of incident falls and fractures. Follow-up is over 99% complete. All reported fractures are confirmed using physician review of radiology reports or study radiologist review of x-rays. All deaths are also centrally adjudicated using death certificates and recent hospitalization records. In additional to the baseline study visit and tri-annual questionnaires, all surviving active participants were invited to follow-up visits and questionnaires. A second comprehensive clinic visit was completed between March 2005 and May 2006 or about 4.5 years after baseline. Most baseline measures, including vertebral radiographs, were repeated at the second visit. A third comprehensive clinic visit was completed between March 2007 and March 2009 or about 7.0 years after baseline. Many baseline measures were repeated at the third visit. A measure of energy expenditure was also obtained utilizing an accelerometer based armband device. Surviving participants have also completed two extensive mailed questionnaires designed to updated information obtained at clinic visits. The first questionnaire was mailed between baseline and visit 2 between July 2002 and March 2004. The second questionnaire was mailed after the third questionnaire between March 2009 and February 2011. The MrOS Sleep Study, an ancillary study of the parent MrOS cohort, was conducted between December 2003 and March 2005 and recruited 3,135 MrOS participants for a comprehensive sleep assessment. Men were screened for nightly use of mechanical devices during sleep including pressure mask for sleep apnea (CPAP or BiPAP), mouthpiece for snoring or sleep apnea, or oxygen therapy and were generally excluded. The sleep visit included objective measures of sleep using actigraphy and polysomnography. Other measures at the sleep visit include neuropsychiatric measures, performance measures, health related questionnaires, routine exam measures previously completed at MrOS clinic visits and a urine and serum specimen collection. During the sleep study period, participants complete a tri-annual questionnaire every four months that contains information about incident cardiovascular events. All reported events are centrally adjudicated utilizing hospital records, study ECGs and other supporting documentation. The Hip Osteoarthritis study, another ancillary study of the parent MrOS cohort, was completed at the second clinic visit between March 2005 and May 2006. Participants were asked for consent for a hip x-ray and osteoarthritis measurements were obtained from these x-rays. DNA was extracted from baseline whole blood samples for use in genetic research. Consent for use of DNA was obtained through written consent. Raw GWAS data is housed at the study's coordinating center and not released as part of the dbGAP release. The raw data can be requested from the study's coordinating center. Only QC cleaned Plink files are available on dbGAP.

Study phs000373

Cell-free DNA Methylome Analysis Enables Early Preeclampsia Prediction

This dataset contains in solution target-enrichment bisulfite sequencing of placental tissue, buffy coat and plasma DNA from pregnant women. Blood samples were taken for cell-free DNA (cfDNA) DNA extraction from 64 women at the time of early-onset preeclampsia (PE) diagnosis, or from 38 controls (uncomplicated pregnancies) at a similar gestational age that did not develop preeclampsia subsequently. Among these subjects, plasma samples from 7 PE patients and 6 controls were also subjected to oxidative bisulfite sequencing. Placental tissues from 11 PE and 26 control subjects after delivery, and buffy coat from 16 PE and 16 control subjects at the same time of cfDNA sampling were profiled. A discovery cohort for early PE assessment in the first trimester was collected. In this cohort, cfDNA from 75 pregnancies that went on to develop early-onset PE and from 124 matched controls were collected and methylome sequencing were carried out. An independent validation cohort to validate early PE assessment with methylome profiling was collected as well. This validation cohort includes cfDNA samples from 61 PE and 136 control pregnancies.

Dataset EGAD00001010159

Covacta RNAseq merged EGA metadata

Sample metadata for the RNA-seq dataset. This dataset includes subject-level data and longitudinal visit day information for the corresponding samples.

Dataset EGAD00001011162

H3Africa H3AChipDesign TrypanoGEN1

26 samples from Cameroon generated for the H3Africa Chip Design Study. The dataset includes BAM, FASTQ and decompressed gVCF files.

Dataset EGAD00001004393

Whole_Genome_sequencing_of_individuals_from_Val_Borbera__Italy

This study includes Phase 2 whole-genome sequencing data (at 4x depth)of 100 individuals from an Italian genetic isolate population (Val Borbera, abbreviated VBI) of the Italian Network of Genetic Isolates (INGI). The INGI-VBI_SEQ2 project aims to combine available extensive genetic and phenotypic data to the latest high-throughput genome sequencing technology and ad hoc statistical analysis to identify new rare genetic variants underlying complex traits.

Study EGAS00001000458

Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be Heart Health Study (nuMoM2b Heart Health Study)

Participants from study sites that recruited during the original study funded by NICHD of pregnant people, called nuMoM2b, participated in this study. The nuMoM2b-HHS1 was a prospective observational follow-up study of the nuMoM2b cohort consisting of interval contacts via phone or web every 6 months to about a year, and an in-person visit 2 to 7 years after the end of the nuMoM2b pregnancy including: Demographics Self-administered questionnaires Clinical measurements Lab results An in-home sleep breathing assessment for the subset of participants with at least one valid sleep breathing assessment during nuMoM2b Abstraction of medical records for pregnancies subsequent to nuMoM2b involving self-reported adverse pregnancy outcomes or multiple births Abstraction of medical records of selected cardiovascular risk-related events or procedures reported by participants. The study capitalized on the rich and unique data prospectively collected during nuMoM2b (biomarkers, uterine artery Doppler studies, fetal growth, psychosocial determinants, sleep, and blood pressure) and rigorous definitions of adverse pregnancy outcomes. These data are stored in the NICHD repository DASH (https://dash.nichd.nih.gov/study/226675). A total of 8,838 nuMoM2b participants were targeted for contact during nuMoM2b-HHS and 7,872 participants were reached, of whom 7,003 completed one or more interval contacts. Of these, 5,206 agreed to the visit, and 4,508 attended an in-person visit.

Study phs002808

DAC for Hungarian human exome team (Department of Medical Biology, University of Szeged, Hungary)

Dac EGAC00001000838

Next Generation Mendelian Genetics: Kabuki Syndrome

The ultimate purpose of this research is to identify genes causing hereditary disorders. We are scaling a new approach to identify the candidate genes and gene mutations that underlie rare human Mendelian (a set of primary tenets relating to the transmission of hereditary characteristics from parent to child) diseases by using exome (protein coding segments of DNA) resequencing. The exome sequences of ten unrelated individuals with a diagnosis of Kabuki Syndrome (OMIM: 147920) were obtained by massively parallel DNA sequencing.

Study phs000295

BLUEPRINT release August 2015, ChIP-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

ChIP-Seq data for 5 CD8-positive, alpha-beta T cell sample(s). 26 run(s), 26 experiment(s), 26 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

Dataset EGAD00001001513

TARGET Trial Study Cohort

In a randomized controlled clinical trial, investigators will compare the effects on [18F]-fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET/CT) from two treatment regimens in rheumatoid arthritis (RA) patients deemed methotrexate inadequate responders (MTX-IRs). Two common RA treatments will be compared: triple therapy (sulfasalazine, methotrexate, and hydroxychloroquine) versus tumor necrosis factor (TNF) inhibitor (etanercept or adalimumab, plus background methotrexate for all subjects and hydroxychloroquine for subjects who were taking this at screening). Consenting subjects will be screened for eligibility and randomized to a treatment arm. Subjects will be randomized to a treatment arm with either synthetic disease-modifying antirheumatic drugs (DMARDs) [triple therapy: sulfasalazine, methotrexate, and hydroxychloroquine] or biologic DMARDs [etanercept or adalimumab, plus background methotrexate for all subjects and hydroxychloroquine for subjects who were taking this at screening]. Once randomized, a baseline visit will be conducted with each subject. Baseline data collection includes questionnaires, disease activity score, and the first FDG-PET/CT imaging. After the baseline at week 0, subjects will visit with their rheumatologist at weeks 6, 12, 18, and 24 for safety labs and further collection of disease activity scores and questionnaires. The second FDG-PET/CT will be performed at week 24. Blood specimens will be collected at weeks 0, 6, 18, and 24 for bioassays. Subject participation will end after the week 24 visit. Patients and care providers will be unblinded. The FDG-PET/CT image readers will be blinded to treatment arm as well as timepoint of image acquisition.

Study phs003720

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 <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

Refractory Classic Hodgkins Lymphoma (cHL) sWGS

Associated with the study: Blood-based Monitoring of Relapsed/Refractory Hodgkin Lymphoma Patients Predict Responses to Anti-PD-1 Treatment. 26 ctDNA Samples from 4 patients followed longitudinally. sWGS performed for copy number aberration (CNA) analysis.

Dataset EGAD50000001163

RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial.

DAC for RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial.

Dac EGAC50000000627

fragmentomic features of individuals with different cfDNA concentrations

The uploaded data includes sequencing data of 862 individuals from the nasopharyngeal carcinoma (NPC) screening study. Samples from this cohort were sequenced using targeted sequencing methods for the Epstein Barr Virus (EBV) and selected autosomal DNA, but only ‘off-target’ reads were used for fragmentomic analyses. We have also performed genome-wide (non-targeted sequencing) for 1) Individuals with the highest and lowest cell-free DNA concentration (40 individuals); 2) A subsequent collection of the subjects with the highest and lowest DNA concentrations after six years (26 individuals); 3) 30 cases of pregnancy and 4) 20 patients with hepatocellular carcinoma. All sequencing data are of extracted plasma cfDNA from human subjects. The targeted sequencing samples from 862 individuals were sequenced on the NextSeq500 System (Illumina) and aligned to the EBV genome (AJ507799.2) and the human genome (hg19). The alignments were provided in bam format. The original fastq files of the remaining non-target sequencing samples were provided.

Dataset EGAD50000000970

The EGA Helpdesk team: 2025 in review and what we are building next

Behind every dataset submitted, every access request processed, and every technical question answered, there is a team working quietly to keep things moving: the Helpdesk (HD). With the onset of 2026, this feels like the right moment to look back on what 2025 has been like for the HD team: the challenges we faced, how we adapted, and where we're heading next. Why the Helpdesk matters to EGA The EGA Helpdesk is more than a support channel. It plays a key role in maintaining trust in the EGA ecosystem. By supporting data submitters, researchers, Data Access Committees (DACs), and institutional partners, the HD helps ensure that data can flow securely, efficiently, and reliably. When issues arise, the Helpdesk is often the first place where their impact is felt and addressed. In that sense, the HD sits at the intersection of technology, policy, and people. One Helpdesk, two locations, one shared mission The EGA Helpdesk is a joint, distributed team working closely across two locations: CRG (Barcelona, Spain) and EMBL-EBI (Cambridge, UK). Although we are based in different institutions, we operate as a single Helpdesk, with shared workflows, priorities, and responsibility towards users. At CRG, the HD team is formed by: Andrea Max Àlex and me At EMBL-EBI, we work closely with: Silvia Coline Aravind What defines us as a team is simple: we work user-first, even under pressure. In a highly technical environment, clarity, empathy, and consistency matter just as much as tools and processes. A close collaboration across sites is essential to making that happen. What does the EGA Helpdesk do? The HD supports users across the full lifecycle of data in EGA. This includes: Data submissions, uploads, and encryption workflows. Data access requests and permissions. Questions around policies, consent, and data usage. Technical and system-related issues. Coordination between users, internal teams, and external partners. 2025: growth, change, and recalibration 2025 was a year of growth, but not always a predictable one. Early in the year, several technical and system-related challenges required us to adjust our original plans. Priorities shifted, timelines changed, and some improvements had to be rethought. For the HD team, this is often the hardest part of the job: we see delays through the eyes of users and understand the real impact they can have on ongoing research. One of the key lessons from 2025 was that stability is not only a technical challenge, but also an organisational one. Teamwork proved to be essential: anticipating peak periods, sharing context early, and coordinating closely across teams made a tangible difference. When things became complex, working together across roles and locations was what allowed us to keep moving forward. In 2025, the Helpdesk received 5.313 tickets and resolved 5.511 requests, reflecting both increased adoption of EGA and the team’s ability to absorb higher demand. At the same time, demand continued to grow. Compared to 2024, ticket creation increased by over 6%, while resolution capacity grew by more than 11%. The team not only kept up with incoming requests but also resolved part of the accumulated backlog, finishing the year having solved more tickets than were created. The real challenge of 2025 was not overall performance, but how the workload was concentrated during peak months. Seasonality and demand spikes placed pressure on the system, even while overall efficiency remained strong. On a team level, 2025 was also a year of transition. I joined the HD leadership role in January 2025, stepping into a period of change and rapid learning. Later in the year, in October, we said goodbye to Raül, and in January 2026, we welcomed Àlex, strengthening the team for the next phase. What users needed most in 2025 While requests vary widely, some themes stood out throughout the year: Support with data submissions and uploads Data access requests and permissions Technical and system-related issues As EGA matures, day-to-day operations have become more complex. Many long-running tickets are not delayed due to a lack of follow-up, but because they depend on external approvals, cross-institutional coordination, or multi-step processes. Understanding these patterns helps us focus not just on resolving tickets, but on improving how work flows through the system. Looking ahead to 2026 With a reinforced team and clearer insights from 2025, our focus for 2026 shifts from throughput to flow. Key priorities include: Strengthening our web content and documentation Reducing structural backlog Improving cross-team and cross-system coordination Anticipating peak demand earlier and planning capacity accordingly Challenges will continue to arise in 2026, as they always do. However, 2025 reinforced something important: a stable, empathetic, and well-aligned Helpdesk team is essential to supporting EGA's mission at scale. Supporting users well means supporting research, and that remains at the core of what we do.

Blog ega-helpdesk-team-2025-in-review-and-upcoming-improvements

Genomic data from analysis of the human placenta, part of the Pregnancy Outcome Prediction study (POPs)

The Pregnancy Outcome Prediction (POP) study is a prospective cohort study of nulliparous women attending the Rosie Hospital (Cambridge, UK) for their dating ultrasound scan. The study included 4512 women with a viable singleton pregnancy; study participants provided written informed consent and were recruited between January 2008 and July 2012. The POP study aimed both at evaluating performance of known biomarkers and serial ultrasonography in assessing maternal and fetal well-being, as well as identifying novel biomarkers. The study is sufficiently large to be powered for relatively uncommon adverse pregnancy outcomes. Women attended four study visits scheduled every 8 weeks, starting with the first trimester. Participants had blood taken during the dating/recruitment visit (at approximately 12 weeks gestation (wkGA)), as well as at three subsequent visits (at ∼20wkGA, ∼28wkGA and ∼36wkGA). For more detail, please visit: https://www.obgyn.cam.ac.uk/research/pops-2/.

Study EGAS00001002205

Count Me In (CMI): The Metastatic Breast Cancer (MBC) Project (CMI-MBCproject)

Count Me In - The Metastatic Breast Cancer Project: A Patient-Driven Research Initiative to Accelerate Metastatic Breast Cancer Research The Metastatic Breast Cancer Project is a research study that directly engages patients with metastatic breast cancer via social media and advocacy groups and empowers them to accelerate cancer research by sharing their samples and clinical information. Our goal is to create a publicly available dataset of genomic, molecular, clinical, and patient-reported data to enable research. Patients in the US or Canada may register online. Registered patients are sent an online consent form that asks for permission to obtain and analyze their medical records, tumor tissue, saliva, and blood samples. Once enrolled, patients are sent a saliva kit and asked to mail back a saliva sample, which is used to extract germline DNA. Study staff contact participants' medical providers and obtain medical records and a portion of their stored tumor biopsies. Patients may be asked to mail in a blood sample, which is used to extract cell free DNA (cfDNA). Whole exome sequencing (WES) is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing is performed on tumor RNA. Clinically annotated genomic data are used to study specific patient cohorts (including outliers) and to identify mechanisms of response and resistance to therapies. All de-identified data, including genomic, clinical, and patient-reported data, are shared via public databases on a pre-publication and recurring basis as it is generated. The latest data release in cBioPortal is available here. Study updates are shared with participants regularly.

Study phs001709

Comprehensive molecular and clinicopathological profiling of glioma

Various molecular profiles are needed to classify malignant brain tumors, including gliomas, based on the latest classification criteria of the World Health Organization, and their poor prognosis necessitates new therapeutic targets. The Todai OncoPanel 2 RNA Panel (TOP2-RNA) is a custom-target RNA-sequencing (RNA-seq) using the junction capture method to maximize the sensitivity of detecting 455 fusion gene transcripts and analyze the expression profiles of 1,390 genes. This study aimed to classify gliomas and identify their molecular targets using TOP2-RNA. A total of 124 frozen samples of malignant gliomas were subjected to TOP2-RNA for classification based on their molecular profiles and the identification of molecular targets.

Study JGAS000671

Sequencing files for "Transcriptional Mechanisms of Resistance to Anti-PD-1 Therapy"

Files from whole exome sequencing of 26 tumors and two matched normals from one melanoma patient. The 26 tumors include the untreated primary, cutaneous metastases and distant metastases to internal organs.

Dataset EGAD00001003200

dataset1

Contains test sample 1-26

Dataset EGAD00010002041

National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS)

NIAGADS is an NIH controlled-access data repository that collaborates with researchers around the world to facilitate data access and sharing for genomic and associated omics data related to Alzheimer's Disease (AD), Alzheimer's Disease Related Dementias (ADRD), as well as healthy aging. Serving as the data coordinating center for the Alzheimer's Disease Sequencing Project (ADSP), NIAGADS hosts all ADSP-generated whole-exome, whole-genome and associated phenotypes. Other data types hosted by NIAGADS include genotype SNP arrays, functional omics, fluid biomarkers, aggregated imaging data (such as volumetric data for brain regions of interest), and summary statistics. In adherence with NIH security best practices and genome data sharing policies, NIAGADS supports data access requests through review by an NIH-appointed and registered Data Access Committee. Data stored within NIAGADS cannot be requested via dbGaP. Data requests must go through the NIAGADS Data Sharing Service (DSS) via the following NIAGADS url: https://dss.niagads.org/. Questions related to the request of data should be directed to the NIAGADS admin team at: niagads@pennmedicine.upenn.edu. DSS is a FISMA certified platform built by a team of data scientists at the University of Pennsylvania to support the request and access of AD/ADRD data by qualified researchers internationally. Questions related to the use of data hosted in the DSS should be directed to the Portal admin team at: help@niagads.org.

Study phs004180

Tracking Therapy-Resistant Alterations in Childhood Acute Lymphoblastic Leukemia

Relapse is currently the major cause of death in children with B-ALL. The goal of this study is to uncover the genetic underpinnings of relapsed B-ALL in the AALL1331 cohort (PMID: 33651090) via whole genome and transcriptome sequencing of matched diagnosis, relapse, and remission specimens. We aim to discover genetic alterations that drive treatment resistance in relapsed tumors. We also aim to investigate the feasibility of detecting residual tumors from remission samples with the ultimate goal to improve risk stratification using NGS-based minimal residual disease (MRD) detection. Here we only report data from patients in remission with the aim of determining MRD. We will submit corresponding data for the diagnosis and relapse components of our cohort in a future version of our study.

Study phs003409

Long-read data (PacBio)

The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

Dataset EGAD00001006597

Exome-wide mutation analysis of cell-free DNA to simultaneously monitor the full spectrum of cancer treatment outcomes

Purpose: Cell-free DNA (cfDNA) offers a non-invasive approach to monitor cancer. Here we develop a method using whole-exome sequencing (WES) of cfDNA for simultaneously monitoring the full spectrum of cancer treatment outcomes, including MRD, recurrence, evolution, and second primary cancers. Experimental Design: Three simulation datasets were generated from 26 cancer patients to benchmark the detection performance of MRD/recurrence and second primary cancers. For further validation, cfDNA samples (n=76) from cancer patients (n=35) with six different cancer types were used for performance validation during various treatments.Results: We present a cfDNA-based cancer monitoring method, named cfTrack. Taking advantage of the broad genome coverage of WES data, cfTrack can sensitively detect MRD and cancer recurrence by integrating signals across known clonal tumor mutations of a patient. In addition, cfTrack detects tumor evolution and second primary cancers by de novo identifying emerging tumor mutations. A series of machine learning and statistical denoising techniques are applied to enhance the detection power. On the simulation data, cfTrack achieved an average AUC of 99% on the validation dataset and 100% on the independent dataset in detecting recurrence in samples with tumor fraction ≥0.05%. In addition, cfTrack yielded an average AUC of 88% in detecting second primary cancers in samples with tumor fraction ≥0.2%. On real data, cfTrack accurately monitors tumor evolution during treatment, which cannot be accomplished by previous methods.Conclusion: Our results demonstrated that cfTrack can sensitively and specifically monitor the full spectrum of cancer treatment outcomes using exome-wide mutation analysis of cfDNA.

Study EGAS00001005906

Team

The Team Mallory Freeberg Roderic Guigó Arcadi Navarro Helen Parkinson Jordi Rambla Ana T. Alonso Silvia Bahena Àlex Bedmar Kenneth Buckley Aldar Cabrelles Ángel Carreño Marcos Casado Giulia Cellerino Amy Curwin Teresa D'Altri Abeer Fadda Teresa Garcia Sara Gregorio Max Fischer Bela Juhasz Oriol Lopez-Doriga Mireia Marin Óscar Martínez Andrea Mero Akiris Moctezuma Aurora Moreno Liina Nagirnaja Francesc de Puig Santiago Rensonnet Gabriele Rinck Aravind Sankar Andres Silva Coline Thomas Sabela de la Torre Gemma Vicente The EGA Team at the CRG co-manages the European Genome and phenome Archive together with the EGA Team at the European Bioinformatics Institute. In addition to maintaining and distributing data, we enrich the contents of the EGA contributing with our knowledge about genomics and the relationship between genomes and phenomes. Previous Team Members Alexander Vikhorev Jeff Almeida-King Mario Alberich Sergi Aguilo Pablo Arce Minjie Ding Alfred Gil Leslie Glass Jag Kandasamy Vasudev Kumanduri llkka Lapalainen Audald Lloret i Villas Sira Martinez Anand Mohan Dietmar Orth Justin Paschall Saif Ur Rehman Gary Saunders Thomas Smith Ashutosh Shimpi Marc Sitges Dhvani Solanki Giselle Kerry Nino Spataro Dylan Spalding Matthieu Vizuete-Forster Cristina Yenyxe Gonzalez Garcia Paul Flicek Anna Foix Emilio Garcia Rios Jorge Izquierdo Roberto Ariosa Marta Ferri Peradalta Daniel Barrowdale Babita Singh Umuthan Uyan Aleix Canalda Dona Shaju Mauricio Moldes Carles Garcia Frédéric Haziza Alegria Aclan Lauren Fromont Alvis Brazma Marta Huertas Arnau Soler Gemma Milla Claudia Vasallo Aina Jené Csaba Halmagyi Raül Garcia Thomas Keane Mei Gascón

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