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• Lund HPI data access committee for Inspire

  Phenotype data from human pancreatic islets from 191 donors, Lund University. Processed for the Inspire consortium.

  Dataset EGAD00001005523

• WGS files for Zhang GenomePaint paper

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

  Dataset EGAD00001006679

• WGS data for MMML (EGAS00001002422)

  Whole genome sequencing data for MMML (7 tumors and 8 controls)

  Dataset EGAD00001003286

• HCC.GNE exome dataset

  Exome read sequences for 30 tumor-normal pairs for the study "Diverse modes of genomic alterations in Hepatocellular Carcinoma".

  Dataset EGAD00001000885

• High-throughput 3D engineered paediatric tumour models for precision medicine

  Paired fastqs for DNA and RNA from Illumina TSO500 targeted sequencing from PDX.

  Dataset EGAD00001015753

• PACA-CA Whole Exome Sequence bam files

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

  Dataset EGAD00001003592

• RNASeq files for Roussel-ATRT-TM

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

  Dataset EGAD00001009302

• McGill EMC Release 4 for assay "ChIP-Seq Input"

  McGill EMC Release 4 for assay "ChIP-Seq Input"

  Dataset EGAD00001001293

• 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.

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

  Dataset EGAD00001000037

• Array data for oesophageal and related samples – sj_paper_methyl_barretts_release

  Array data for oesophageal and related samples – 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

• Glioma sequencing data

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

  Study EGAS00001006355

• Acute myeloid leukemia sequencing data

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

  Study EGAS00001006354

• 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

• PACA-CA Whole Genome Sequence bam files

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

  Dataset EGAD00001003591

• 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

• 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

• 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 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 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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