Search Results - EGA European Genome-Phenome Archive

Xenograph files for PCGP SJERG

Additional Xenograph files for PCGP SJERG

Dataset EGAD00001002741

RNASeq files for Klco tMN data

RNASeq files for paper titled "The Acquisition of Molecular Drivers in Pediatric Therapy-Related Myeloid Neoplasms"

Dataset EGAD00001006674

WXS files for Klco tMN data

WXS files for paper titled "The Acquisition of Molecular Drivers in Pediatric Therapy-Related Myeloid Neoplasms"

Dataset EGAD00001006675

WGS files for Klco tMN data

WGS files for paper titled "The Acquisition of Molecular Drivers in Pediatric Therapy-Related Myeloid Neoplasms"

Dataset EGAD00001006676

Study of Environment, Lifestyle and Fibroids SNP Data

Uterine fibroids are hormonally-dependent benign tumors of the uterine muscle that develop in premenopausal women. Currently, the primary symptoms (pain and bleeding) are treated, but when those treatments fail, major procedures to remove or shrink the fibroids are frequently the only options for women. Fibroids are the leading indication for hysterectomy in the United States. African-American women develop fibroids an average of 10 years earlier than white women in the U.S., and they are approximately three times more likely to have a hysterectomy for fibroids. The known risk factors for fibroids do not explain this disparity.The goal of the Study of Environment, Lifestyle & Fibroids (SELF) is to identify risk factors for uterine fibroid development. It is the first study to identify incident cases based on ultrasound screening. We enrolled a cohort of 1693 women who self-identified as Black or African American, ages 23-35, from the Detroit, Michigan area. Women with a prior diagnosis of fibroids were not eligible. Participants were screened for fibroids with ultrasound at enrollment, and follow-up ultrasounds occurred approximately every 20 months to identify new fibroids. Fibroids that were detected at enrollment and those that arose during follow up were monitored at subsequent visits for fibroid growth. We collected risk factor and symptom data, physical measurements, as well as blood, urine, and vaginal swab specimens at enrollment and follow-up visits.The study was designed to test three primary hypotheses:Vitamin D deficiency is a risk factor for fibroid incidence and/or growth.Reproductive tract infections can increase risk of fibroid development.Genotypic variation in African ancestry may influence fibroid development directly, or through interaction with life-course risk factors.In addition, we collected extensive information to examine other exposures of interest, and our extra specimens can be used to test new hypotheses in the future.With this first prospective study of fibroid development, we aim to identify new preventative factors that could directly benefit women. We anticipate that the detailed data on fibroid development can be used to help design new interval treatment strategies to limit fibroid growth and thus reduce the need for the invasive treatments that remain the standard of care when first-line treatments fail.

Study phs002513

An evaluation of different strategies for large-scale pooled sequencing study design.

Dataset EGAD00001000037

Array data for oesophageal and related samples â€“ sj_paper_methyl_barretts_release

Dataset EGAD00010001838

Validation_for_human_early_embryonic_substitutions_

PCR and MiSeq validation for early embryonic substitution candidates from 400 Breast cancer patients

Study EGAS00001001218

PACA-CA Whole Genome Sequence bam files

Merged bam files for PACA-CA Whole Genome Sequencing, for DCC release 25

Dataset EGAD00001003591

Exome Sequencing

Exome sequencing of for 10 patients: 10 tumors, 10 cell lines and 7 blood samples (for 3 patients blood was not available)

Dataset EGAD00001002690

HiC files for Zhang GenomePaint paper

HiC files for GenomePaint paper titled "Exploration of coding and non-coding variants in cancer using GenomePaint."

Dataset EGAD00001006678

Acute myeloid leukemia sequencing data

This study contains tumor DNA and RNA sequencing data for 1 AML patient

Study EGAS00001006354

Glioma sequencing data

This study contains sequencing data for various glioma subtypes (astrocytoma, glioblastoma, diffuse midline glioma).

Study EGAS00001006355

oxBS-seq for APL

Oxidative bisulfite sequencing (oxBS-Seq) for APL

Dataset EGAD00001008135

WGBS for APL

Whole genome bisulfite sequencing (WGBS) for APL

Dataset EGAD00001008136

Dataset for iAMP21 scRNA-seq

10x Genomics 5' library scRNA-seq data for 4 iAMP21 patients

Dataset EGAD00001009504

RNA-Seq for academic use only

RNA-Seq transcriptome data is only for academic use.

Dataset EGAD00001009675

Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (ONT)

Dataset EGAD00001009632

Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (pacBio)

Dataset EGAD00001009631

Whole exome sequencing data for paired non-serous endometrial and ovarian carcinomas from 27 patients with concurrent tumours.

Dataset for Synchronous Endometrial and Ovarian Cancer

Dataset EGAD00001015680

Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Framingham Heart Study (FHS)

Cohort DescriptionIn 1948, the researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have returned to the study every two years for an examination consisting of a detailed medical history, physical examination, and laboratory tests, and in 1971, the study enrolled a second-generation cohort -- 5,124 of the original participants' adult children and their spouses -- to participate in similar examinations. The second examination of the Offspring cohort occurred eight years after the first examination, and subsequent examinations have occurred approximately every four years thereafter. In 1994, the need to establish a new study reflecting a more diverse community of Framingham was recognized, and the first Omni cohort of the Framingham Heart Study, consisting of 506 participants, was enrolled. In April 2002 4095 third generation of participants, the grandchildren of the original cohort, were added. In 2003, 103 spouses of the offspring Cohort (NOS), and a second group of 410 Omni participants were enrolled. Through 2019, the original cohort has completed a total of 32 exams, the Offspring cohort 9 exams, the OMNI1 cohort 4 exams, and GEN3, NOS and OMNI2 cohorts each have completed 3 exams. The FHS is a joint project of the National Heart, Lung and Blood Institute and Boston University.Data Being Submitted Wave 1 questionnaire data includes 3967 variables for up to 3112 FHS participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 2337 FHS participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 2189 FHS participants in C4R.Derived data includes 43 variables for up to 3151 FHS participants in C4R.Phenotype data includes 113 variables for up to 3151 FHS participants in C4R.

Study phs002911

After the completion of CINECA, EUCANCan, and euCanSHare. What's next?

CINECA, EUCANCan, and euCanSHare were part of the EUCAN Cluster, made up of six projects that received funding under the same Horizon 2020 call. All EUCAN projects (CINECA, EUCANCan, EUCAN-Connect, euCanSHare, Receptor Plus, and ReCoDID) were aimed at facilitating data reuse and knowledge discovery by enhancing data exchange and long-term collaboration in the health field. Here are some highlights about EGA’s contribution to these projects. CINECA: advances in Federated discovery and infrastructure for cohorts CINECA (Common Infrastructure for National Cohorts in Europe, Canada, and Africa) developed a federated cloud-based infrastructure for making genomic and biomolecular data accessible. The project has assembled a virtual cohort of 1.4 million individuals from sources such as the EGA, CanDIG and H3Africa. The EGA–CRG co-leaded a work package Work Package 1 on Federated Data Discovery and Querying. Beacon v2, championed by Jordi Rambla and Lauren Fromont, has been one of the central elements for the discovery of human genetic and phenotypic data. The EGA-CRG contributed to the development of a model for cohort discovery inside the Beacon v2 model. The team also delivered a Discovery Portal was implemented to explore cohorts and individuals of synthetic data. It is a UI that gathers a network of Beacons, a service for query expansion, and a visualisation tool. Have a look at the Discovery Portal UI, gathering a network of Beacons. You will find entities such as the Barcelona Supercomputing Center (BSC), BioData.pt and the European Genomic Data Infrastructure (GDI), among others. euCanSHare: facilitation of data access management This joint EU-Canada project aimed to build a European and Canadian FAIR platform for cardiovascular data sharing and analysis. The EGA’s tasks contributed to the development of the data management plan and data flows, main web-portal and interoperability protocols. An important part of the EuCanShare platform is the data access manager, a tool for the data owners to control the access to their sensitive datasets. We built a user-friendly interface for data access committees (data owners) to easily manage their data requests and access credentials. The data access portal facilitates the creation and internal organization of the data access committees as well as the linkage of data usage conditions to specific datasets. The interface includes filters for browsing requests and page to visualize the request history helping with the handling of data access requests. EUCANCan: toward a federation of clinical institutions in oncology The EUropean-CAnadian CANcer Network worked towards building a federated network to advance personalized medicine in oncology, by promoting the standard analysis, management and sharing of harmonized genomic and phenotypic data. The EGA led tasks on defining data flows and preparing an adapted infrastructure for long-term data storage and sharing. One of the key contributions was the conception of the EGA communities, offering standard and interoperable solutions for data discovery, processing, and sharing to projects and institutions that would like to manage and share data in the context of the EGA ecosystem. What's Next? The participation in projects such as CINECA, EUCANCan, and euCanSHare provide us with experience for future projects. We are happy to enhance data sharing and reuse, vital for advancing clinical and genomic research. The Discovery Portal is a wonderful proof of concept for the Beacon network. Next, we will finalise both the network and the user interface, and make sure it can be applied to more clinically-centred settings like hospitals. Most data hosted at the EGA are about cancer research. Currently, we contribute to building tools and infrastructure to empower oncology research in several European projects such as EUCAIM, EUCANIMAGE and EOSC4Cancer. We also do not lose sight of initiatives in the field such as the International Cancer Genome Consortium (ICGC) with the project ARGO, whose data model was adopted in EUCanCan.

Blog cineca-eucancan-and-eucanshare-were-concluded-in-june

Short and long-read genome sequencing methodologies for somatic variant detection; genomic analysis of a patient with diffuse large B-cell lymphoma

Recent advances in throughput and accuracy mean that the Oxford Nanopore Technologies (ONT) PromethION platform is a now a viable solution for WGS. New bioinformatic methods have been developed to take advantage of this long read data, however much of the validation of these tools has focussed on calling germline variants (both SNVs and structural variants). Somatic variants are outnumbered many-fold by germline variants and their detection is further complicated due to their frequency varying depending on tumour purity/subclonality. Here, we evaluate the extent to which Nanopore WGS enables genome-wide detection and analysis of somatic variation. We do this through sequencing tumour and germline genomes for a patient with diffuse B-cell lymphoma. We examine the capability of currently available tools for calling somatic variants in ONT data by comparing the data with results from 150bp short-read sequencing of the same samples. We then conduct a detailed analysis of the performance of multiple long-read mappers and structural variant callers for calling large, somatic structural variants (SVs) in ONT data. Our protocol achieved yields of up to 96 mapped Gb per PromethION flow cell with average read lengths of ~5kb. Calling germline SNVs from these data achieved good specificity and sensitivity. However, results of somatic SNV calling highlight the need for the development of specialized joint calling algorithms. Our analysis of structural variants shows that the comparative performance of different tools varies significantly between SV types, and suggest long reads are especially advantageous for calling large somatic deletions and duplications. Finally, we highlight the utility of long reads for phasing clinically relevant variants by using the ONT data to confirm that a somatic 1.6Mb deletion and a p.(Arg249Met) mutation involving TP53 are oriented in trans.

Study EGAS00001004266

Somatic copy number alteration and fragmentation analysis in circulating tumor DNA for cancer screening and treatment monitoring in colorectal cancer patients

Background: Analysis of circulating free DNA (cfDNA) is a promising tool for personalized management of colorectal cancer (CRC) patients. Untargeted cfDNA analysis using whole-genome sequencing (WGS) does not need a priori knowledge of the patient´s mutation profile. Methods: Here we established LIquid biopsy Fragmentation, Epigenetic signature and Copy Number Alteration analysis (LIFE-CNA) using WGS with ~6x coverage for detection of circulating tumor DNA (ctDNA) in CRC patients as a marker for CRC detection and monitoring. Results: We describe the analytical validity and a clinical proof-of-concept of LIFE-CNA using a total of 259 plasma samples collected from 50 patients with stage I-IV CRC and 61 healthy controls. To reliably distinguish CRC patients from healthy controls, we determined cutoffs for the detection of ctDNA based on global and regional cfDNA fragmentation patterns, transcriptionally active chromatin sites, and SCNAs. We further combined global and regional fragmentation pattern into a machine learning classifier to accurately predict ctDNA for cancer detection. By following individual patients throughout their course of disease, we show that LIFE-CNA enables the reliable prediction of response or resistance to treatment up to 3.5 months before commonly used CEA. Conclusion: In summary, we developed and validated a sensitive and cost-effective method for untargeted ctDNA detection at diagnosis as well as for treatment monitoring of all CRC patients based on genetic as well as non-genetic tumor-specific cfDNA features. Thus, once sensitivity and specificity have been externally validated, LIFE-CNA has the potential to be implemented into clinical practice. To the best of our knowledge, this is the first study to consider multiple genetic and non-genetic cfDNA features in combination with ML classifiers and to evaluate their potential in both cancer detection and treatment monitoring.

Study EGAS00001006490

WTCCC case-control study for Hypertension - Combined Controls

WTCCC genome-wide case-control association study for Hypertension (HT) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

Study EGAS00000000010

Development of a rapid and comprehensive genomic profiling test supporting diagnosis and research for gliomas

Targeted sequencing dataset used for the paper entitled "Development of a rapid and comprehensive genomic profiling test supporting diagnosis and research for gliomas". The cohort includes 53 cases of targeted DNA squencing, 15 of them have matched control sequences. The capture panel was made by Agilent SureSelect and the sequence was performed using DNBSEQ or Illumina sequencer.

Dataset EGAD50000000979

Exome sequencing data for the DIRECT study.

This dataset contains all available fastq files for gemline, baseline plasma/biopsy, and response assessment patient samples for the DIRECT study. The total number of samples was 729 (188 germline, 190 baseline plasma, 159 baseline biopsy, and 192 response assessment). The dataset files were generated from targeted (exome) Illumina sequencing performed on paired biopsy tissue and plasma cell free DNA.

Dataset EGAD50000001409

Metadata and count matrix

The dataset contains metadata for all cells before scRNA-seq quality control and for cells passing quality control. It also contains a count matrix with Salmon gene counts for all cells passing quality control, and reconstructed B-cell receptor sequences using the computational tool BraCeR. The scRNA-seq data was generated using the Smart-seq2 protocol and sequenced on Illumina NextSeq500.

Dataset EGAD00001006435

BLUEPRINT WP10 Quantitative Trait Loci (QTLs) Phase 2 Full Summary Statistics

BLUEPRINT WP10 Quantitative Trait Loci (QTLs) Phase 2 full summary statistics data include five molecular traits (eQTL, hQTL(H3K27ac), hQTL(H3K4me1), mQTL, and psiQTL) for three primary blood cells (Monocytes, Neutrophils, and T-cells). Each full summary statistics file contains the associations for all tested variants for each phenotype ID.

Dataset EGAD00001005199

Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

Development of a novel machine learning guided ctDNA detection platform for use in liquid biopsy detection and therapeutic monitoring of solid tumors in several clinical contexts. Included are WGS alignments from our study.

Study EGAS00001007306

Sequencing data for the Genomic Autopsy Study

The .cram files of the Trio or Quad sequencing data used for generation of the genomic autopsy study. This contains a mix of genome sequencing and exome sequencing data for probands and their parents. A subset of families (n=32) did not provide consent to publicly sharing their data.

Dataset EGAD00001009737

Dataset of transcriptomic, whole genome and whole exome sequencing to identify predictive biomarkers in pediatric solid tumors

This Dataset contains whole genome sequencing data for 148 sample, transcriptome sequencing for 66 samples and exome sequencing for 123 samples from pediatric solid tumors. Sequencing was performed on Illumina NovaSeq 6000 and Illumina HiSeq 4000. The sequencing was paired.

Dataset EGAD00001015701

Smoking and the Vaginal Microbiome

The focus of this study was to better understand the effects of cigarette smoking on the vaginal microbiome. There were two phases of the study, cross-sectional and longitudinal, conducted at the Center for Health Behavior Research at the University of Maryland School of Public Health. In the cross-sectional phase, 20 smokers and 20 non-smokers collected mid-vaginal swabs, measured their vaginal pH, prepared a vaginal smear on a slide for Nugent Gram stain analysis, and completed questionnaires about demographics, tobacco use, and reproductive and sexual health history. Smoking status was confirmed through self-report, carbon monoxide exhalation and saliva cotinine measures. Secretions from the mid-vaginal swabs were tested for presence/absence of HPV strains and GC-MS was used to quantify the levels of over 600 metabolites. In the longitudinal phase, 7 participants who were current smokers and motivated to quit smoking were recruited and followed for up to 12 weeks. On a daily basis, participants collected mid-vaginal swabs, measured their vaginal pH, and prepared a mid-vaginal smear on a slide for Nugent Gram stain analysis, and completed daily diaries on tobacco use and reproductive health. Carbon monoxide exhalation and saliva cotinine measures were collected at weekly clinical visits. In addition, participants had weekly behavioral counseling sessions about smoking cessation and used Nicoderm CQ patches to aid in quitting smoking. The self-collected vaginal swabs were used for DNA extractions,16s rRNA sequencing and measurement of metabolites in vaginal fluid.

Study phs001386

The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis

In this study, we characterized 24 rheumatoid arthritis (RA) synovial tissue chromatin classes (i.e., cell states defined by chromatin accessibility) across 5 cell types (T, B/plasma, myeloid, stromal, and endothelial). We also investigated the transcription factors that may regulate these chromatin classes, their connections to transcriptional cell states in a proposed superstate model, and their interplay with RA pathology through associations with histological parameters and risk variants.As part of the Accelerating Medicines Partnership (AMP) network, we obtained 18 synovial tissue samples from 14 RA and 4 osteoarthritis (OA) patients for this study. Samples were collected from 7 clinical sites. We performed a 10x single cell ATAC-seq experiment on each sample.We further collected synovial tissue samples from 11 RA patients and 1 OA patient from 2 clinical sites; each sample was used for a 10x single cell multimodal ATAC and Gene Expression experiment.For additional support of the proposed superstate model, we also collected peripheral blood mononuclear cells (PBMCs) from 4 RA patients, sorted for 4 populations (CD4+CD127-CD25hi Tregs, CD4+CD127-CD25int Tregs, CD4+CD25-PD1+CXCR5- TPH, CD4+CD25-PD1+CXCR5+ TFH), tagged each population with a hashing antibody, and pooled populations for one multimodal sequencing run.The FASTQ files are available for controlled access via dbGaP. Additional data can be found on Synapse.The presence of pooled subjects inflates the automatically-generated subject count; the actual consented subject count for this data is 34.

Study phs003417

Biopsy-Derived Organoids in Personalised Early Breast Cancer Care: Challenges of Tumour Purity and Normal Cell Overgrowth Cap Their Practical Utility

The ability to establish organoids composed exclusively of tumour rather than healthy cells is essential for their implementation into clinical practice. Organoids have in recent years emerged as a powerful tool to expand patient material in culture and generate modifiable 3D models derived from humans or animal models. For translational research, they enable the creation of model systems for an ever-increasing number of cell types and diseases. And in personalised medicine, they potentially allow for functional drug testing with high predictive power in certain settings. We found that using biopsy material from untreated, early-stage primary breast cancer patients poses significant challenges for consistently culturing tumour cells as organoids. Specifically, we observed frequent outgrowth of genetically normal, non-cancerous epithelial cells. We analysed >100 biopsy samples from early-stage breast cancer and present our large collection of >70 organoid lines. We also show methods of assessing successful tumour cell culture in a time and cost-efficient manner, proving a high rate (>85%) of normal cell overgrowth in early-stage breast cancer organoids. Finally, we show a number of successful attempts to culture cancer organoids from mastectomy-derived tissue of advanced, metastatic breast cancer. We conclude that the usefulness of organoids from early breast cancer for translational research and personalised medicine, especially guidance of adjuvant or post-surgical maintenance therapy, is strongly limited by the low success rate of culturing cancerous cells under organoid conditions.

Study EGAS50000000605

Geriatric Oncology Database of genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients to establish truly effective treatment strategy

Owing to the advent of super-aged society, cancer mortality in Japan is forecasted to become an all-time high. The management of elderly patients with cancer is a serious health issue and the need for specific care guidelines for this population is critical in Japan. The significant individual differences in comorbidity, physical and mental functioning, and social problems among aging individuals are obstacles to the progress. The response to cancer treatment varies significantly among patients, even in the same stage of the same type of cancer. Older aged patients are still less likely to be offered participation in clinical trials, thus the number of clinical evidences is limited. The molecular mechanisms regulating the physiological process of ageing and senescence, and cancer are far from understood. To establish a truly effective treatment algorithm, we attempted to develop a geriatric oncology database for genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients in this retrospective study. The genomic analysis was performed in 62, 106, and 173 cases, respectively for gastric, colon and lung cancers. The clinical data and survey results on psychosocial and physical conditions were collected from 166, 313, and 344 patients respectively for gastric, colon and lung cancers, and also collected from 357, 49, and 300 benign cases respectively for cardiovascular disorder, respiratory dysfunction, diabetes and nephropathy as the analysis control.

Study JGAS000061

Partner-independent fusion gene detection by multiplexed CRISPR/Cas9 enrichment and long-read Nanopore sequencing

Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment possibilities. The promiscuity of fusion genes with respect to partner choice and exact breakpoint-positions restricts their detection in the diagnostic setting, even for known and recurrent fusion gene configurations. To accurately identify these gene fusions in an unbiased manner, we developed FUDGE: a FUsion gene Detection assay from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for enrichment and detection of fusion gene drivers (e.g. BRAF, EWSR1, KMT2A/MLL) - without prior knowledge of fusion partner or breakpoint-location - to long-read Nanopore sequencing. FUDGE encompasses a dedicated bioinformatics approach (NanoFG) to detect fusion genes from Nanopore sequencing data. Our strategy is flexible with respect to target choice and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in a single sequencing run. We observe on average a 508-fold on-target enrichment and identify fusion breakpoints at nucleotide resolution - all within two days. We demonstrate that FUDGE effectively identifies fusion genes in cancer cell lines, tumor samples and on whole genome amplified DNA irrespective of partner gene or breakpoint-position in 100% of cases. Furthermore, we show that FUDGE is superior to routine diagnostic methods for fusion gene detection. In summary, we have developed a rapid and versatile fusion gene detection assay, providing an unparalleled opportunity for pan-cancer detection of fusion genes in routine diagnostics.

Study EGAS00001003964

Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

Study EGAS00001003973

Whole Exome Sequencing for Colorectal Cancer

This project was designed to use next generation sequencing technology to screen the protein coding regions of the genome for low frequency variants in a panel of high-risk colorectal adenocarcinoma cases. Blood and cell-line DNA for colorectal cancer patients and a subset of quality control samples that had existing whole exome sequence data were analyzed using Illumina HiSeq sequencers. Samples from this project were from participants in the Women's Health Initiative (WHI) and the Diet, Activity, and Lifestyle Study (DALS).

Study phs000410

Circulating Tumor DNA Sequencing Provides Comprehensive Mutation Profiling for Pediatric Central Nervous System Tumors

Tumor molecular profiling is increasingly important for the diagnosis and clinical management of childhood brain tumors, including diffuse midline glioma (DMG). We established a targeted deep sequencing approach using the TruSight Oncology 500 ctDNA exome panel to detect tumor genomic mutations and copy number variations in circulating tumor DNA from children diagnosed with DMG. In this study, we present the sensitivity, specificity, and clinical implications of our liquid biopsy sequencing approach for tumor genome profiling in children with DMG.

Study phs003022

WGS data for EBiSC iPSC lines

The European Bank for Induced Pluripotent stem cells (EBiSC) is designed to address the increasing demand by iPSC researchers for quality-controlled, disease-relevant research grade iPSC lines, data and cell services. In this study Whole Genome Sequencing was performed on a selection of lines from the project.

Study EGAS50000000742

ctDNA multigenic panel for non-small cell lung cancer

Detection of actionable mutations in liquid biopsies constitute an important tool for management of non-small cell lung cancer (NSCLC) patients in the era of oncology precision medicine. We aimed to evaluate the actionable alterations using a commercial multi-gene panel in circulating tumor DNA (ctDNA) derived from plasma samples of treatment naïve and prior-treated non-small cell lung cancer (NSCLC) patients. For this, we analyze plasma samples of 30 subjects with non-small cell lung cancer.

Study EGAS50000000643

A GWAS for cutaneous leishmaniasis in Brazil

Our goal was to identify genetic risk factors for cutaneous leishmaniasis (CL) caused by Leishmania braziliensis. Genotyping 2066 CL cases and 2046 controls using Illumina HumanCoreExomeBeadChips provided data for 4,498,586 imputed single nucleotide variants (SNVs). Genome-wide association testing using linear mixed models took account of genetic diversity/ethnicity/admixture. Post-GWAS positional, expression quantitative trait locus (eQTL), and chromatin interaction mapping was performed in FUMA. Transcriptional data were compared between lesions and normal skin, and cytokines measured using flow cytometry and Bioplex assay.

Study EGAS00001004596

The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

Tumor infiltration by T cells is paramount for effective anti-cancer immune responses. We hypothesized that the T cell receptor (TCR) repertoire of tumor infiltrating T lymphocytes (TIL/Tc) could determine disease course at different stages in cancer progression. We show that the diversity of the TIL/Tc TCR at baseline is prognostic in various cancers, whereas in metastatic melanoma TIL/Tc TCR clonality at baseline is predictive for activity and efficacy of PD1 blockade immunotherapy.

Study EGAS00001005201

Single cell RNA sequencing of normal endometrial derived organoids uncovers novel cell type markers for prognostication

Endometrial carcinoma, the most common gynecologic cancer, develops from endometrial epithelium which is composed of secretory and ciliated cells. Pathologic classification is unreliable and there is a need for prognostic tools. We used single cell sequencing to study organoid model systems derived from normal endometrial endometrium to discover novel markers specific for endometrial ciliated or secretory cells. We performed single cell sequencing on endometrial and ovarian tumors and found both secretory-like and ciliated-like tumor cells.

Study EGAS00001004466

Investigation of different library preparation and tissue of origin deconvolution methods for urine and plasma cfDNA methylome analysis

In this study, a single- and a double-stranded library preparation approach was evaluated with respect to their technical biases when applied on cfDNA from plasma and urine. This study thus outlines potential limitations of double-stranded library preparation for methylation analysis of cfDNA especially for urinary cfDNA. While the double-stranded method allows jagged end analysis in addition to TOO analysis, it leads to significant methylation bias in urinary cfDNA, which single-stranded methods can overcome.

Study EGAS00001007314

Annotated VCF Files for WGS of ASD Cohort with 68 Individuals from 22 families, enriched for recent shared ancestry

We performed whole genome sequencing (WGS) in an ASD cohort of 68 individuals from 22 families enriched for recent shared ancestry. Samples were sequenced using Illumina HiSeq X platform, and Variants (single nucleotide variants (SNVs) and insertions or deletions (indels)) were detected using GATK with HaplotypeCaller. Quality control checks for (i) duplicate samples, (ii) samples per platform, (iii) genome call rate, (iv) missingness rate, (v) singleton rate, (vi) heterozygosity rate, (vii) homozygosity rate, (viii) Ti/Tv ratio, (ix) inbreeding coefficient, and (x) sex inference were performed as previously described. Variant call format (VCF) files for SNVs and indels were annotated with ANNOVAR using allele frequencies from the 1000 Genomes project (2015; 1000G), the Genome Aggregation Database (gnomAD), and the Greater Middle East Variome Project (GME).

Dataset EGAD00001008634

cfDNA methylation dataset for colon cancer

Enzymatic conversion-based methylation sequencing data (EM-seq) for colon cancer used in the MESA study

Dataset EGAD50000000075

PASCAL-MID Data Access Committee

DAC for the center of Personalized Approach to Genome Editing of Stem Cells for Autotransplantation of Monogenic Immunodeficiencies (PASCAL-MID) at Aarhus University and Aarhus University Hospital

Dac EGAC50000000680

Pancreatic Cancer NGS WGS data

Whole genome sequencing data for Pancreatic Cancer Samples exploring the tandem duplicator phenotype

Study EGAS50000001078

V4_Colorectal_panel_test

Targeted gene screen of cell line tumours for testing the new V4 Colorectal gene panel.

Study EGAS00001001807

ChIP-Seq files for PCGP ATRX study

ChIP-Seq files for PCGP ATRX study paper titled "MYCN Amplification and ATRX Mutations are Incompatible in Neuroblastoma"

Dataset EGAD00001004429

A98269B

Whole genome sequencing for single cells for library A98269B 1609 cells; filetype=bam

Dataset EGAD00001006947

A96217B

Whole genome sequencing for single cells for library A96217B 1616 cells; filetype=bam

Dataset EGAD00001006945

WGBS data for Glioblastoma (EGAS00001003953, H016)

Whole Genome Bisulfite data for human glioblastoma patients, EGAS00001003953. 68 human samples

Dataset EGAD00001006546

PACA-CA RNASeq fastq files

Fastq files for PACA-CA RNA Seq analysis, for DCC release 27

Dataset EGAD00001003972

Dataset for B-ALL scRNA-seq

10x Genomics 5' library scRNA-seq data for 85 B-ALL patients with different subtypes

Dataset EGAD00001011327

KiCS cancer panel academic only data

This data set contains KiCS cancer panel data for academic and for-profit use.

Dataset EGAD00001009733

Comparison of Custom Capture for Targeted Next Generation DNA Sequencing

Targeted, capture-based DNA sequencing is an economical way to sequence a customized region of the genome. Several targeted sequencing kits are available, but the efficacies of these kits have not been compared. We appraised four targeted DNA technologies for next generation sequencing, considering on-target sequencing, uniformity, and single nucleotide variation and copy number variation discovery. The technologies which utilized sonication to fragment genomic material showed impressive uniformity of capture. The other two had shorter preparation times, but sacrificed uniformity. One of those technologies, which needs transposase to fragment genomic material, has a weakness that requires all samples be pooled and the final one, which uses restriction enzyme digestion, is limited depending on restriction enzymes digest sites. Naturally, all technologies showed some concordance for calling SNVs, the kits that used restriction enzymes or transposase missed several SNVs, due, in large part, to lack of coverage. All technologies showed high integrity for copy number variant calling when compared to SNP arrays. This study aids laboratories in their decision of the proper technology to use for their intended applications.

Study phs000811

A Multi-Gene Mutation Classification of 468 Colorectal Cancers Reveals a Prognostic Role for APC

Colorectal cancer (CRC) is a highly heterogeneous disease, for which prognosis has been relegated to clinic-pathologic staging for decades. There is a need to molecularly stratify subpopulations of CRC to better predict outcome and assign therapies. Here we report targeted exome sequencing of 1,321 cancer-related genes on 468 tumor specimens, which identified a subset of 17 genes that best classify CRC, with APC (Gene ID: 324) playing a central role in predicting overall survival. APC may assume 0, 1, or 2 truncating mutations, each with a striking differential impact on survival. Tumors lacking any APC mutation carry a worse prognosis than single APC mutation tumors, but tumors with two APC mutations and KRAS (Gene ID: 3845) and TP53 (Gene ID: 7157) mutations confer the poorest survival among all the subgroups examined. Our study demonstrates a substantial prognostic role for APC and suggests that sequencing of APC may have clinical utility in the routine staging and potential therapeutic assignment for CRC.

Study phs001111

The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis (CLEAR)

The Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis (CLEAR) Registry and Repository, supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), was established in 2000 to provide a resource for the scientific community to explore genetic and non-genetic factors affecting rheumatoid arthritis (RA) occurrence and outcomes in African Americans. The long term objective is a database and a repository of 1,100 RA and 550 matched healthy African-American subjects. This CLEAR Registry and Repository has two arms: a longitudinal arm for subjects with early RA (enrollment from 2000 to 2005) and a cross-sectional arm for subjects with any disease duration (enrollment from 2006 to 2012). CLEAR has two components: a database and a repository. The database contains extensive demographic, socioeconomic, clinical and radiographic (radiographs of hands and feet) information and bone mineral density data from DEXA scans. The repository contains genomic DNA, plasma and serum on most of the participants. Participants in CLEAR II had RNA isolated from peripheral blood cells.

Study phs001360

Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

Cohort DescriptionHispanic Community Health Study/Study of Latinos (HCHS/SOL) is an ongoing population-based prospective cohort study of 16,415 community dwelling Hispanic/Latino adults aged 18-74 years at baseline, recruited from four urban field centers with large populations of Hispanics/ Latinos (Bronx, NY; Chicago, IL; Miami, FL; and San Diego, CA). The primary goals of the HCHS/SOL are to describe: (1) the prevalence and incidence of cardiovascular, pulmonary, and other major chronic conditions (2) the risk and/or protective factors associated with these conditions; and (3) the relationships between the initial sociodemographic and health profiles and future health events in the target population. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 9817 HCHS/SOL participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 7536 HCHS/SOL participants in C4R. Derived data includes 43 variables for up to 11182 HCHS/SOL participants in C4R. Phenotype data includes 113 variables for up to 11182 HCHS/SOL participants in C4R.

Study phs002908

Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Northern Manhattan Study (NOMAS)

Cohort Description The Northern Manhattan Study (NOMAS) is a study of the population of Washington Heights in Northern Manhattan. The ongoing study, which began in 1990, has enrolled over 4,400 people, some of whom have suffered a stroke or related neurological syndromes. As the cohort aged, the specific aims grew to include not only vascular determinants of stroke but also cognitive decline, mild cognitive impairment (MCI) and dementia. The overall goal of NOMAS is to investigate stroke risk factors in different race-ethnic groups. NOMAS is also committed to developing better stroke prevention programs to improve the health of the community. The Hispanic population in Northern Manhattan is largely Dominican, along with Puerto Rican, Cuban, and Central and South American components.Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 887 NOMAS participants in C4R Wave 2 questionnaire data includes 448 variables for up to 815 NOMAS participants in C4R Derived data includes 43 variables for up to 995 NOMAS participants in C4R Phenotype data includes 113 variables for up to 995 NOMAS participants in C4R

Study phs003028

The Innate Immune Response as a Therapeutic Target for Cutaneous Leishmaniasis

The overall goal of the proposed project is to identify innate host functions that contribute to cure or failure during antileishmanial drug therapy, and their related biomarkers. Results from this project enabled the identification of host-specific predictive and prognostic signatures of therapeutic responsiveness, and the bases for rational selection of host-targeted therapeutics that redirect inflammation and revert pathogenicity. Through sequential transcriptomic profiling of blood monocytes (Mo), neutrophils (Nφ), and eosinophils (Eφ) over the course of systemic treatment with meglumine antimoniate, we discovered that a heightened and sustained Type I interferon (IFN) response signature is a hallmark of treatment failure (TF) in Cutaneous Leishmaniasis (CL) patients. The transcriptomes of pre-treatment, mid-treatment and end-of-treatment samples were interrogated to identify predictive and prognostic biomarkers of TF. Results from this study instigate the evaluation of Type-I IFN responses as new immunological targets for host-directed therapies for treatment of CL, and highlight the feasibility of using transcriptional signatures as predictive biomarkers of outcome for therapeutic decision making.

Study phs003545

Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer

Determining response to therapy for patients with pancreatic cancer can be challenging. We evaluated methods for assessing therapeutic response using cell-free DNA (cfDNA) in plasma samples from 40 patients with metastatic pancreatic cancer as part of the CheckPAC trial (NCT02866383). Patients were evaluated before and after initiation of therapy using tumor-informed plasma whole-genome sequencing (WGMAF), and genome-wide cfDNA fragmentation profiles and repeat landscapes (ARTEMIS-DELFI). Of those assessed with WGMAF, molecular responders had a median overall survival (OS) of 319 days compared to 126 days for non-responders (HR=0.29, 95% CI=0.11–0.79, p=0.011). For ARTEMIS-DELFI, patients with low scores after therapy initiation had a longer median OS than patients with high scores (233 days versus 172 days, HR=0.12, 95% CI=0.046-0.31, p<0.0001). We validated ARTEMIS-DELFI in a separate cohort of 40 patients with pancreatic cancer who were part of the PACTO trial (NCT02767557). These analyses suggest that non-invasive mutation and fragmentation-based cfDNA approaches can identify therapeutic response of individuals with pancreatic cancer.

Study EGAS50000000923

BAMSE (Swedish abbreviation for Children, Allergy, Milieu, Stockholm, Epidemiology)

The BAMSE (Swedish abbreviation for Children, Allergy, Milieu, Stockholm, Epidemiology) study is an ongoing longitudinal, population-based prospective birth cohort including 4,089 children born between 1994 and 1996 in Stockholm, Sweden. The cohort was initially designed to study risk factors for asthma, allergic diseases and lung function in childhood, and to study factors of importance for prognosis at already established disease.Questionnaires on respiratory symptoms and medication were answered at age of 1, 2, 4, 8 and 16 years. Response rates ranged from 96-82% at each occasion with very minor selection bias over the years. Exposure to air pollutants and other environmental factors has been mapped since birth.At the 8 and 16 year follow-up, spirometry and FeNO measurements were performed and at the latter, impulse oscillometry was measured. Blood samples (including plasma) from around 2,500 children were taken at 4, 8 and 16 years and have been analyzed for different IgE-ab and biomarkers. Genome-wide genetic, global methylation and transcriptomic data exist on a subset of the children.

Study EGAS00001002746

A combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancer

The earlier diagnosis of cancer is one of the keys to reducing future cancer deaths. Here we describe our efforts to develop a non-invasive, blood test for the detection of pancreatic ductal adenocarcinoma. We combined blood tests for KRAS gene mutations with carefully thresholded protein biomarkers to determine whether the combination of these markers was superior to any single marker. The cohort tested included 221 patients with resectable pancreatic ductal adenocarcinoma and 185 control patients without known cancers. KRAS mutations were detected in the plasma of 66 patients (30%) and every mutation found in the plasma was identical to that subsequently found in the patients' primary tumor (100% concordance). The use of KRAS in conjunction with two thresholded protein biomarkers (CA19-9 and prolactin) increased the sensitivity to 67%. Only one of the 185 plasma samples from the control cohort were positive for any of the three markers (99.5% specificity). This combinatorial approach may prove useful for the earlier detection of many cancer types.

Study EGAS00001002444

An Isogenic Cell Line Panel for Sequence-based Screening of Targeted Anti-cancer Drugs

We describe the creation and characterization of an isogenic cell line panel representing common cancer pathways, with multiple features optimized for high-throughput screening. More than 1,800 cell lines from three normal human cells were generated using CRISPR-technologies. Surprisingly, we discovered most of these lines did not result in complete gene inactivation, despite integration of sgRNA at the desired genomic site. However, a subset of the lines harbored true, biallelic disruptions of the targeted tumor suppressor gene, yielding a final panel of 100 well-characterize lines covering 19 pathways frequently subject to loss of function in cancers. This panel included genetic markers optimized for sequence-based ratiometric assays for drug-based screening assays. To illustrate the potential utility of this panel, we developed a multiplexed high-throughput screen that identified Wee1 inhibitor MK-1775 as a selective growth inhibitor of cells with inactivation of TP53. These cell lines and screening approach should prove useful for researchers studying a variety of cellular and biochemical phenomena

Study EGAS00001005974

dbGaP Collection: NHLBI Heart Failure Related dbGaP Data (No IRB requirement)

The National Heart, Lung, and Blood Institute (NHLBI) Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research has concluded. The NHLBI will continue to make this collection of data available to the research community.Past information regarding the Data Collection for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research is below.The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), is inviting novel Solutions for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research. The goal of the challenge is to foster innovation in computational analysis and machine learning approaches utilizing large-scale NHLBI-funded datasets to identify new paradigms in heart failure research. The challenge aims to address the need for new open source disease models that can define sub-categorizations of adult heart failure to serve as a springboard for new research hypotheses and tool development in areas of heart failure research from basic to clinical settings. NHLBI has a history of making considerable investments in the creation of deep data resources including: long-standing, deeply-phenotyped epidemiological cohorts, innovative clinical trials, and large-scale precision medicine efforts that have generated whole genome sequencing and "other omics" data for more than one-hundred thousand individuals. To provide challenge participants with streamlined access to data across NHLBI's numerous studies containing heart failure data, the NHLBI has created this dbGaP study collection. Data access for this collection is controlled by NHLBI's Data Access Committee. Challenge participants are required to follow the use restrictions and acknowledgement instructions from the original dataset(s). Please note that the data in this collection are not harmonized across studies or otherwise altered from the original study. The NHLBI Big Data Analysis Challenge: Heart Failure Data Collection contains all NHLBI studies currently in dbGaP that contain data that may be relevant to research on heart failure. The studies in this collection are approved for General Research Use (GRU), Health/Medical/Biomedical Use (HMB), or Disease-Specific Use (DS) that permits research on heart failure. These studies span a variety of study designs, inclusion and exclusion criteria, sample sizes, and provide a wide breadth and depth of phenotype data on study participants. The available genomic data in these studies also varies, including genotyping arrays, sequencing (targeted, exome, whole genome), and additional -omic data (e.g., RNA or metabolite profiles). Please refer to each study's individual accession page to learn more about how study data were collected. Challenge participants are reminded that in addition to dbGaP, NHLBI's Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) contains other studies that have collected data relevant to heart failure and may wish to utilize BioLINCC data in the development of their Solution. Please refer to the individual accession page for each study in this collection to learn more about the history of each study.

Study phs001991

Additional Methylation files for Roussel-ATRT-TM

Additional Methylation files for Roussel-ATRT-TM paper titled "Atypical teratoid/ rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities"

Dataset EGAD00010002495

DAC for TFHL single-cell analysis project at Department of Hematology, University of Tsukuba

DAC for study of tumor heterogeneity and immune-evasive microenvironment in T follicular helper cell lymphomas

Dac EGAC50000000201

COMPASS Next Generation Sequencing WGS data

Whole genome sequencing data for Pancreatic Cancer Samples from the COMPASS clinical trial

Study EGAS50000001091

A95673A

Whole genome sequencing for single cells for library A95673A 1446 cells; filetype=bam

Dataset EGAD00001006941

Data files for CONSERTING

Data files for CONSERTING (WGS)

Dataset EGAD00001001352

Targeted sequencing analysis for MDS with HSCT

Targeted capture sequencing for cases with MDS who were subjected to unrelated bone marrow transplantation via Japan marrow donor program

Dataset EGAD00001003118

RNA data for MMML (EGAS00001002422)

RNA sequencing data for MMML (3 tumor samples and 1 gcbcell)

Dataset EGAD00001003285

Mucosal 16S metadata

Metadata for 16S-V4 rRNA gene sequence data for intestinal biopsies from NCT02749630 trial participants.

Dataset EGAD00001008823

CUTRUN files for Klco-NUP98 data

CUTRUN files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia"

Dataset EGAD00001015478

WGS files for Mullighan_GL_reALL

WGS files for Mullighan_GL_reALL paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

Dataset EGAD00001005506

WXS files for Mullighan_GL_reALL

WXS files for Mullighan_GL_reALL paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

Dataset EGAD00001005509

Gene Expression Signatures in CATHGEN

Case control cohort: The details have been previously published: American Heart Journal. 2010;160:371-379 e372. Briefly, a nested case:control cohort of CATHGEN participants who had experienced death or MI (n = 250) after their index catheterization and age-, sex-, and race-matched controls (n = 250) who were free of death/MI > 2 years after cardiac catheterization was identified as part of the MURDOCK Horizon 1 Cardiovascular Disease Study.21 Sufficient RNA for microarray analysis was available in 447 members of this cohort. Observational cohort: 224 sequential CATHGEN samples were selected for whole blood RNA analysis, of which, 191 had sufficient RNA for microarray analysis.

Study phs000551

Genetics of Pigmentation in Eastern and Southern African Populations Study

The goal of this study was to identify genes and loci associated with pigmentation in African populations. It comprises 1,593 participants from Ethiopia, Tanzania, and Botswana. Sexes are evenly represented (768 males and 825 females) and self reported ages ranged from 18 to 103. Mean age was used for individuals without ages. For each participant, a DSM II color meter was used to measure underarm skin reflectance in triplicate. These measures averaged and converted to a melanin index (MI = 100 x log10(1/(x/255)). All individuals were included in a genome wide scan that accounted for age, sex, and genetic relatedness.

Study phs001396

Estonian Biobank | Estonian Genome Center, University of Tartu

The Estonian Biobank is the population-based biobank of the Estonian Genome Centre of University of Tartu. The biobank is conducted according to the Estonian Gene Research Act and all participants have signed broad informed consent. The cohort size is currently 51,535 people from 18 years of age and up. Metabolite concentrations (over 110; NMR and MS) are available for about 12,000 subjects; metabolic follow-up has been done for more than 2000 donors. GWAS has been performed on 20,000 subjects with different Illumina arrays and 2,500 have whole exomes and 2,400 full sequence. The data for the 2,400 fully sequenced samples is available through dbGaP.

Study phs001230

Sensitive urothelial cancer detection via high volume urine DNA analysis

Cystoscopy and imaging are the gold standard for urothelial cancer (UC) detection and surveillance, but cystoscopy is an uncomfortable procedure associated with adverse effects and a low diagnostic yield as only 10% of hematuria patients have UC. Urine tumor DNA (utDNA) is a non-invasive UC biomarker that has suffered from poor sensitivity for Ta stage tumors (<80%). We hypothesized that high urine volume analysis with a multi-gene panel could overcome these limitations, and developed a 100 mL utDNA laboratory platform (UroScout) that analyzes 25 commonly mutated UC genes and 8 copy number-altered loci for somatic alterations to detect UC.

Study EGAS50000000630

Multimodal cell-free DNA whole-genome TAPS is sensitive and reveals specific cancer signals

This study presents a methodology for detecting circulating tumor DNA (ctDNA) using deep whole-genome TET-Assisted Pyridine Borane Sequencing (TAPS), a less destructive alternative to bisulphite sequencing. The method enables simultaneous analysis of genomic and methylomic data for multi-cancer detection and monitoring minimal residual disease. In a diagnostic accuracy study across various cancer types, it achieved 85.3% sensitivity and 88.8% specificity, with validation done using matched tumour biopsies. Additionally, in silico validation showed strong discrimination at low ctDNA levels. The approach also successfully tracks tumour burden and ctDNA shedding from precancerous lesions post-treatment, making it ready for further clinical testing.

Study EGAS50000000715

Multi-omics analysis of treated cancer samples

We treated patient-derived cell lines with effective drug inhibitors that we discovered. To understand the mechanisms behind how the inhibitor can effectively inhibit tumor growth, we performed a series of RNA-Seq, Histone ChIP-Seq, TF ChIP-Seq and ATAC-Seq profiling for samples with and without treatment with the inhibitor. There are 18 RNA-Seq, 20 ATAC-Seq and 182 ChIP-Seq experiments performed. This includes 2 biological replicates. Novaseq 6000 was used to sequence the samples. Library preparation was performed in house for ChIP-Seq and ATAC-Seq, using NEB indexes, while libraries for RNA-Seq were constructed by the sequencing company hired. Total RNA was sequenced. Sequencing parameters used are PE150, bi-directional sequencing. For ATAC-Seq, sequencing was performed up to 40M reads, for ChIP-Seq, sequencing was performed up to 20M reads and for RNA-Seq, sequencing was performed up to 20M to 40M reads. Fastq files are uploaded here.

Dataset EGAD50000000349

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

ENU_CCK_81_cetuximab_pilot_project

Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC.

Study EGAS00001001743

CONSERTING: integrating copy number analysis with structural variation detection

We developed Copy Number Segmentation by Regression Tree in Next Generation Sequencing (CONSERTING), a novel algorithm for detecting somatic copy number alteration (CNA) using whole-genome sequencing (WGS) data. CONSERTING performs iterative analysis of segmentation by read depth change and localized structural variation detection to achieve high accuracy and sensitivity. Analysis of 43 pediatric and adult cancer genomes revealed novel oncogenic CNAs, complex re-arrangements and subclonal CNAs missed by alternative approaches. This study contains all data for "CONSERTING: an accurate method for detecting somatic DNA copy number alterations in whole genome sequencing data", which was previously split between EGAS00001001202 and EGAS00001001050.

Study EGAS00001001202

ENU_NCI_H508_cetuximab_fixed_concentration_project

Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC

Study EGAS00001001744

ENU_NCI_H508_Cetuximab_SecondRound

Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC

Study EGAS00001001745

Genome-wide genetic and epigenetic dataset of pancreatic acinar cell carcinomas

Pancreatic acinar cell carcinoma (ACC) is an aggressive exocrine tumor with largely unknown biology. To identify potential targets for personalized treatment, integrative genome- and epigenome-wide analyses were performed. The results show frequently aberrant DNA methylation, abundant chromosomal amplifications and deletions, and mutational signatures suggesting defective DNA repair. In contrast to pancreatic ductal adenocarcinoma, no recurrent point mutations are known. The tumor suppressors ID3, ARID1A, APC, and CDKN2A are frequently impaired also on the protein level and thus potentially affect ACC tumorigenesis. Consequently, this work identifies potential novel therapeutic targets in ACC for drugs recently approved for precision cancer therapy.

Study EGAS00001002533

WGS___Exploration_of__mutational_processes_in_human_cancer_cell_lines

Approximately 25 cell lines representative of 11 mutation signatures have been selected and will be grown from a single cell, referred to as parental clone, for a period of 3 months to allow accumulation of mutations. Following that period, we will obtain 2 subclones from each of the parental clone for analysis by exome-sequencing . In total we will therefore be sequencing 2 parental clones and 4 subclones per cell line for approximately 25 cell lines. Once the data has been analysed and the potential ongoing mutation processes determined, we will perform whole-genome sequencing of the parental clones and subclones of the candidate cell lines.

Study EGAS00001002680

Enhanced cortical neural stem cell identity through SMAD/WNT inhibition in human cerebral organoids facilitates emergence of outer radial glial cells

For scRNA-Seq, single live cells were suspended in 0.4% BSA in DPBS buffer (1000 cells/µL) and subjected for GEM generation and barcoding. Library preparation was performed according to the recommended procedures of the manufacture Chromium Single Cell 3’ reagent Kit V3.1 chemistry. 10,000 cells were targeted for capturing and 9 cycles were used for cDNA amplification, while 12 cycles were performed for library formation, and sequencing was performed on an Illumina NovaSeq 6000 sequencer. For bulk RNA-Seq, RNA was purified using the miRNeasy™ RNA MiniPrep (Qiagene) and RNA-seq libraries were generated either using the Illumina TruSeq RNA Library Preparation Kits and sequenced on the Illumina HiSeq 2500 sequencer as 76 bp paired-end reads, or using the NEBnext UltraDirectional RNA Library Preparation Kits after rRNA depletion using the NEBNext rRNA depletion kit and sequenced on an Illumina HiSeq 2500 sequencer using 50 cycles of single-end sequencing.

Dataset EGAD00001008609

Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Coronary Artery Risk Development in Young Adults Study (CARDIA)

Cohort Description The Coronary Artery Risk Development in Young Adults (CARDIA) study is a study examining the development and determinants of clinical and subclinical cardiovascular disease and their risk factors. It began in 1985-6 with a group of 5115 black and white men and women aged 18-30 years. The participants were selected so that there would be approximately the same number of people in subgroups of race, gender, education (high school or less and more than high school), and age (18-24 and 25-30 years) in each of 4 centers: Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25), 2015-2016 (Year 30), and 2021-2022 (Year 35). Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 2434 CARDIA participants in C4RWave 2 questionnaire data includes 448 variables for up to 1901 CARDIA participants in C4RDried Blood Spot/Serosurvey data includes 7 variables for up to 1332 CARDIA participants in C4RDerived data includes 43 variables for up to 2723 CARDIA participants in C4RPhenotype data includes 113 variables for up to 2723 CARDIA participants in C4R

Study phs003045

Targeted panel somatic variant sequencing dataset for "Molecular counting enables accurate and precise quantification of methylated ctDNA"

Targeted panel somatic variant sequencing dataset for "Molecular counting enables accurate and precise quantification of methylated ctDNA." This dataset was created by running 60 cfDNA samples from patients with metastatic cancer to the lung through a research-use, tumor-naive, targeted-panel assay for measuring somatic mutations across a panel of 80 genes. All samples were sequenced on Illumina NextSeq 2000 with 150x2 paired end sequencing; files are in fastq.gz format. For the original study, the variant allele fractions of these somatic mutations were compared with the Tumor Methylation Scores calculated from Northstar Response in the same samples.

Dataset EGAD50000001016

SECRETO Oral metagenome study

The main goal of the project is to study the associations between the oral metagenome and young-onset cryptogenic ischemic stroke (CIS). The dataset includes information for n=329 participants who underwent saliva sampling. Participants for the SECRETO Oral study were enrolled between December 2013 and November 2019. Shotgun metagenomic sequencing was performed using the Illumina NovaSeq 6000 platform.

Study EGAS00001007505

Labcorp® Plasma Detect™ assay: whole genome sequencing analyses of plasma cfDNA, white blood cells and FFPE tumor tissue

The dataset "Labcorp® Plasma Detect™ assay: whole genome sequencing analyses of plasma cfDNA, white blood cells and FFPE tumor tissue" includes CRAM and CRAI files derived from WGS of 555x plasma cfDNA, 209x white blood cells (normal DNA) and 209x FFPE tumor tissue (tumor DNA) samples for 209 stage III colorectal cancer patients. WGS (150bp PE) was performed on a NovaSeq 6000 with a target depth of coverage of 80x for tumor DNA, 40x for normal DNA and 30x for cfDNA. Reads were aligned to GRCh37 (plasma cfDNA) or GRCh38 (tumor/normal DNA).

Dataset EGAD50000001180

Analysis of genes related to the oncogenesis, progression or effectiveness of drug therapies of urological tumors .

To clarify the oncogenesis and the progression mechanism of urological tumors, we continuously collect tumor samples of our patients with high quality. Then we used them to comprehensive analyses such as genome sequencing or epi-genome sequencing. Through these analyses, we aim for elucidating the oncogenesis or for developing newly treatment strategies of each cancer.

Study JGAS000737