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• Targeted proteomics for endotyping of chronic rhinosinusitis

  To identify biomarkers allowing for the distinction between different chronic rhinosinusitis patient groups and disease controls (n=20 of each DC, CRSsNP, CRSwNP and N-ERD), we use high-throughput targeted proteomics (Olink Multiplex platform) in nasal secretions and serum samples.

  Study EGAS50000000907

• A fast, affordable and minimally-invasive diagnostic test for Cancer of Unknown Primary (CUP) using DNA methylation profiling

  CUP diagnosis on FFPE tissue and liquid biopsies (blood, pleural and peritoneal effusions) using cfRRBS (cell-free reduced representation bisulfite sequencing), a technique that allows for identification of the methylation profile starting from minimal amounts of highly fragmented DNA.

  Study EGAS50000000257

• Scywalker: scalable end-to-end data analysis workflow for nanopore single-cell transcriptome sequencing

  Existing nanopore single-cell data analysis tools showed severe limitations in handling current data sizes. We developed novel scalable methods for cell barcode demultiplexing and single-cell isoform calling and quantification and incorporated these in an easily deployable package called scywalker.

  Study EGAS50000000537

• BLUEPRINT RNA-seq data for rare cells in the haematopoietic lineages, from adult and cord blood samples.

  RNA-seq data for rare cells in the haematopoietic lineages, from adult and cord blood samples.

  Study EGAS00001000284

• Breast implant-associated anaplastic large cell lymphoma shallow whole genome sequencing for copy number analysis and Whole exome sequencing data.

  Breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) shallow whole genome sequencing of 29 BIA-ALCL patients for copy number analysis and 24 Alk-negative ALCL samples as control cohort. 7 Whole exome sequencing BIA-ALCL samples.

  Study EGAS00001003962

• Cell type-specific transcriptomics of esophageal adenocarcinoma as a scalable alternative for single cell transcriptomics

  We developed a protocol for the separation of esophageal carcinoma tissue into leukocytes (using CD45 as a marker), epithelial cells (EpCAM), and fibroblasts (two out of PDGFRA, CD90, anti-fibroblast) by fluorescence-activated cell sorting followed by RNA-sequencing

  Study EGAS00001004053

• FACS sorting of ploidy populations in an undifferentiated soft tissue sarcoma for RRBS

  Groups of cells belonging to different ploidy populations (based on PI staining) were collected from an undifferentiated soft tissue sarcoma. The different ploidy populations underwent RRBS, after which copy number signatures for the ploidy-sorted populations and the bulk population were extracted.

  Study EGAS00001006143

• RRBS of 25 pleural mesothelioma samples (Single-end)

  The dataset contains RRBS data (bam files) for 25 pleural mesothelioma samples.The samples were sequenced on NovaSeq6000 (Illumina, San Diego, CA) in single-end 150bp mode. RRBS raw reads were trimmed for adaptor sequences using trim galore (v. 0.6.5) (http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) and filtered for low-quality sequences using fastQC (v. 0.11.8) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). High quality trimmed reads were mapped to the Human reference genome (UCSC genome assembly GRCh38/hg38) using Bismark (v. 0.22.3) with default parameters.

  Dataset EGAD50000002130

• Genetic data of a monozygotic twin pair discordant for ALS

  We performed whole exome sequencing of a monozygotic twin pair discordant for ALS. This dataset contains two VCF files: one of the healthy twin and one of the ALS twin. Library was prepared according to Agilent SureSelectQXT Kit protocol and processed using Illumina NextSeq 550 sequencer). Fastq files were aligned on the reference human genome hg19 (GRCh37) and, for each patient, a list of variations in a VCF format file (Variant Call Format) was produced by GATK software and annotated by wAnnovar.

  Dataset EGAD50000001329

• stem cell-derived beta cells from cell lines RC9 and HUES8

  stem cell-derived beta cells differentiated using two different cell lines: HUES8 (non-clinical grade) and RC9 (clinical grade). iPSC stem cell lines were differentiated to pancreatic islets using differentiation protocol as detailed by Rajaei et al. (2025, Science Translational Medicine, accepted for publication). scRNAseq was done at stage 7 of differentiation (day 30) using 10X genomics 3' sequencing. Cells were annotated then subsetted for beta cells for downstream analysis

  Dataset EGAD50000001322

• Transcriptomic analysis of LINE1 expression in the human brain

  Twist Bioscience probes were designed to LINE1 and HERV sequences for targeted amplification. Enriched cDNA libraries were then sequenced on the PacBio Sequel II, 4 samples/SMRTcell. The available files have undergone ccs (using the default parameters except for --min-rq 0.9, which was a recommended parameter for Iso-Seq) and barcode demultiplexing. Recommended analysis follows https://isoseq.how/, starting at the primer removal and demultiplexing step with lima.

  Dataset EGAD50000000265

• BLUEPRINT September 2016, ChIP-Seq for thymocyte from thymus, on Genome GRCh38

  ChIP-Seq data for 5 sample(s) for thymocyte from thymus, on Genome GRCh38. 17 run(s), 17 experiment(s), 17 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002947

• BLUEPRINT September 2016, ChIPmentation for memory B cell from venous blood, on Genome GRCh38

  ChIPmentation data for 2 sample(s) for memory B cell from venous blood, on Genome GRCh38. 6 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002923

• BLUEPRINT September 2016, ChIPmentation Acute Lymphocytic Leukemia for precursor B cell from bone marrow, on Genome GRCh38

  ChIPmentation data for 7 sample(s) Acute Lymphocytic Leukemia for precursor B cell from bone marrow, on Genome GRCh38. 13 run(s), 13 experiment(s), 13 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002928

• BLUEPRINT September 2016, ChIPmentation for germinal center B cell from tonsil, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for germinal center B cell from tonsil, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002932

• BLUEPRINT September 2016, ChIPmentation Acute Myeloid Leukemia for blast cell from bone marrow, on Genome GRCh38

  ChIPmentation data for 2 sample(s) Acute Myeloid Leukemia for blast cell from bone marrow, on Genome GRCh38. 12 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002935

• BLUEPRINT September 2016, ChIPmentation Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38

  ChIPmentation data for 5 sample(s) Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38. 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002936

• BLUEPRINT September 2016, ChIPmentation for naive B cell from tonsil, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for naive B cell from tonsil, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002937

• BLUEPRINT September 2016, ChIPmentation for conventional dendritic cell from cord blood, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for conventional dendritic cell from cord blood, on Genome GRCh38. 4 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002940

• BLUEPRINT September 2016, ChIPmentation for regulatory T cell from venous blood, on Genome GRCh38

  ChIPmentation data for 2 sample(s) for regulatory T cell from venous blood, on Genome GRCh38. 14 run(s), 9 experiment(s), 9 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002942

• Metastatic breast cancer targeted gene screen (2017-05-11)

  The samples will be sequenced for a targeted panel of cancer relevant genes (n ~ 370) and analysed for somatic mutations. This dataset contains all the data available for this study on 2017-05-11.

  Dataset EGAD00001003330

• Genome Diversity in Africa Project - GemCode libraries (2017-07-05)

  High depth whole genome sequencing from GemCode (10x Genomics) DNA libraries containing long range linkage information for one Baganda trio and one Baganda child (parent already sequenced at high depth). This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ This dataset contains all the data available for this study on 2017-07-05.

  Dataset EGAD00001003426

• Genetic screening of GPI-anchor protein synthesis (2018-08-13)

  This study will analyse the guide sequence which were used for making mutations in the Cas9-expressing cells. We used GeCKO v2 library which were released by Feng Zhang, 2014. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2018-08-13.

  Dataset EGAD00001004294

• Contribution of Retrotransposition to Developmental Disorders

  Variants and WGS data for Gardner et al. 2018 (biorxiv 471375). One VCF each for Alu, L1, and SVA. Flat text file and WGS for processed pseudogenes.

  Dataset EGAD00001004586

• Metastatic breast cancer targeted gene screen (2014-09-24)

  The samples will be sequenced for a targeted panel of cancer relevant genes (n ~ 370) and analysed for somatic mutations. This dataset contains all the data available for this study on 2014-09-24

  Dataset EGAD00001001018

• IBD Whole Genome Sequencing (2019-04-01)

  We will sequence at 15X coverage the genomes of 1536 IBD patients. These samples are currently onsite at Sanger and made available for sequencing via our collaboration with the UK IBD Genetics consortium. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004880

• Oceanian and American population sequencing and phasing (2019-04-11)

  Whole-genome sequencing of human individuals from Polynesian and Native American populations, as well as 10x Genomics Chromium data from Polynesian, Native American and Aboriginal Australian populations, allowing for experimental phasing of haplotypes. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-04-11.

  Dataset EGAD00001004951

• Colon Cancer Organoid Cultures and Tumors Whole Exome Sequencing Data

  Five hundred fifty nanograms of genomic DNA were input for library preparation after fragmentation by Covaris S2, following the KAPA Hyper Prep Kit (KR0961-V1.14) protocols, with selection for a library size range of 250-450 bp. Three hundred nanograms per library DNA each from 12 samples were normalized and combined into a single pool for exome capture using the xGen Lockdown Probes and Reagents based on their standard protocols

  Dataset EGAD00001005754

• RNA Sequencing datasets - Project "Multi-omics analysis of Parkinson’s disease midbrains"

  The dataset contains FASTQ files referring to the study "Multi-omics analysis of Parkinson’s disease midbrains". For this project, RNA was isolated from human postmortem midbrain tissue (PD and Control samples). Libraries were prepared with the TruSeq Small RNA library prep (Small RNA Seq) and the TruSeq Stranded Total RNA Kit (for transcriptomics), both from Illumina. Sequencing for both experimental setups was conducted in the Illumina HiSeq4000.

  Dataset EGAD00001006883

• Genome-wide Association Study for Non-syndromic Clefts in the African Population: CIDR

  The focus of this project is to identify genetic variants that are associated with orofacial clefts in African populations in sub-Saharan Africa. Most genetic studies of CLP (including the vast majority of GWAS) have been conducted in populations of European origin with only a few focused on Asian or African populations. We choose to study the genetics of these complex traits in African populations because, African populations have the greatest genetic variation amongst the various populations in the world by virtue of being the primary ancestral population to modern humans (Cavalli-Sforza and Feldman, 2003; Ramsay et al., 2011). Therefore, the potential for finding novel loci for CLP is quite high. To date 6 genome wide association studies (GWAS) for cleft lip with or without cleft palate (CL/P) have been conducted and 18 risk loci identified (Birnbaum et al., 2009; Grant et al., 2009 ; Beaty et al., 2010; Mangold et al., 2010; Ludwig et al., 2012; Sun et al., 2015). All these studies have either been conducted in European populations, Asian populations or both. There is currently no published GWAS for clefts in African populations. African populations represent a novel and richly productive populations for genetic and environmental exposure studies for CL/P. Investigating the presence of genetic variants in diverse population groups can identify novel variants and candidate genes that are population specific. Environmental factors may also increase the risks in certain population groups due to genetic susceptibility and/or specific exposures. Understanding the role these susceptibility genes play in the effects of environmental risk factors can inform strategies designed towards reducing the outcome of these complex traits, e.g. through the modification of the environmental influences. The study population comprises a large number of individuals (3205 individuals) from Africa (Ghana, Ethiopia and Nigeria). There are cases, case triads (nuclear families), as well as controls with no history of OFC nor other developmental defects.

  Study phs001090

• National Institute on Aging - Late Onset Alzheimer's Disease Family Study: Genome-Wide Association Study for Susceptibility Loci

  Alzheimer disease is the most common neurodegenerative disorder of the elderly affecting an estimated five million Americans. Genetic factors contribute to the risk for disease with heritability estimates ranging from 57% to 79%. More than a decade ago, the ε4 variant of APOE was identified and remains the most consistently replicated genetic variant influencing the risk of late onset Alzheimer disease. A segregation analysis suggests there may be four additional genes influencing the age-at-onset of Alzheimer disease. In 2007 there were 968 association studies in 398 candidate genes reported, but none replicated consistently. There are many reasons for the lack of consistency, but one important reason for the lack of progress is the paucity of a sufficient number of well characterized families and patients available to the entire scientific community. The extensive effort and expense required to ascertain such a population has been addressed by the NIA-LOAD Family Study. Its goal is to identify and recruit families with two or more siblings with the late-onset form of Alzheimer's disease and a cohort of unrelated, non-demented controls similar in age and ethnic background, and to make the samples, the clinical and genotyping data and preliminary analyses available to qualified investigators world-wide. Genotyping by the Center for Inherited Disease Research (CIDR) was performed using the Illumina Infinium II assay protocol with hybridization to Illumina Human 610Quadv1_B Beadchips. This genotyping represents the largest collection of families ever assembled with Alzheimer's disease combining the NIA-LOAD Genetics Initiative Multiplex Family Study, the National Cell Repository for Alzheimer's Disease (NCRAD) with additional controls from the University of Kentucky. These genotyping results will serve as a focal point for future research that will identify all of the remaining genetic variants in Alzheimer's disease.

  Study phs000168

• Local In Time Statistics for processual research

  Background: Functional genomics in a processual analysis cover the time-dependent changes in transcriptomics and epigenetics before diagnosis of a disease, reflecting the changes in both life style and disease processes. The aim of this paper is to explore the dynamic, time-dependent mechanisms of the metastatic processes, using blood transcriptomics and including time in a continuous manner. For achieving this goal we develop new statistical methods based on statistics that are local in time. Methods: The new statistical method, Local In Time Statistics (LITS), is based on calculating statistics in moving windows and randomization. The method has been tested for the analysis of a dataset that collectively provides information on the blood transcriptome up to eight years before breast cancer diagnosis. The dataset from the NOWAC Post-genome Cohort consists of 467 case-control pairs matched on birth year and time of blood sampling. The data for a pair is the difference in log2 gene expression between the case and control. The stratified analyses are based on important biological differences like metastatic versus non-metastatic cancer, and the mode of cancer detection, i.e. screening detected versus clinically detected cancers. The dataset was used for examining whether the gene expression profile varies between cases and controls, with time, or between cases with and without metastases. Results: The null hypotheses of no differences between cases and controls, no time-dependent changes, and no differences between different strata were all rejected. For screening detected cancers the probability of correct prediction of metastasis status was best in year 1 before diagnosis compared to year 3 and 4 before diagnosis for clinically detected cancers. The predictor was not very sensitive to the number of genes included.Conclusions: Using a new statistical method, LITS, we have demonstrated time-dependent changes of the blood transcriptome up to eight years before breast cancer diagnosis.

  Study EGAS00001002520

• Best Practices for DACs

  Best Practices Data access committees (DACs) are institutional safeguards responsible for ensuring a balance between data protection and accessibility. However, there are no procedural standards that apply across DACs, which can lead to inconsistencies in their reviews and compromise their quality and effectiveness. Standardising DAC processes can foster trust and mutual recognition, paving the way for greater coordination, collaboration, and delegation between DACs and other oversight bodies to improve the efficiency of data access without sacrificing protection. To provide guidance, the following are suggestions for actions a DAC might take upon receiving a data access request: Aim to respond to all initial requests in less than 2 weeks. Failure to do so may result in follow-up emails from the EGA, journals, and ultimately dataset withdrawal. First, check that the data/EGAD number is consistent with your data submission. In other words, ensure that the requester has contacted the correct DAC. Verify that the user will be using the data within the terms of consent by asking them to sign up to the terms within the DAA. Ensure that data users who are granted access to the data comply with the terms of a Data Access Agreement (DAA) and to use the data only in approved ways. Look for an institutional email address for the requester. Search for evidence that the requester is "appropriately qualified/bona fide" for using the data, for example on PubMed, Research Gate, LinkedIn, etc. Confirm that the affiliated organisation is real and that the requester still works there. Inquire with the requester about who should have accounts created at the EGA under the terms of the agreement. If a negative decision is made, promptly communicate it to the requester and support it with the terms of the Data Access Policy that the requester has not met or cannot meet. Keep the information in the DAC up to date. If you leave your institution and are unable to manage data access requests on their behalf, you should add your replacement as a new contact in the DAC. Assist with data access requests for any further questions related to your data. The EGA can only check information that has been deposited in the repository. If the user has a specific question that the EGA cannot answer, we will redirect the user to the DAC. All the EGA studies and datasets referenced in a publication under your DAC must be publicly searchable on the EGA website before the paper is released. If possible, describe the permitted purposes for subsequent research projects, including associated limits and conditions, for all resources hosted in a repository using a common ontology, such as the GA4GH Data Use Ontology (DUO). It is considered best practice to try and release data only to those with an institutional email address. This gives reassurance to the EGA, research participants, and the general public that an appropriate individual is accessing and using the data. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security.

  Documentation access/data-access-committee/best-practices

• Cancer Registry of Norway - NIPH Data Access Committee for CRCbiome datasets

  The Cancer Registry of Norway - NIPH appointed Data Access Committee for the CRCbiome datasets - The microbiome as a colorectal cancer screening biomarker. https://www.mn.uio.no/sbi/english/groups/rounge-group/crcbiome/.

  Dac EGAC50000000121

• DAC for "HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling"

  This is the DAC for the study "HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling" of PD Dr. Aurélie Ernst (a.ernst@dkfz.de) B420, DKFZ.

  Dac EGAC50000000452

• Massachusetts General Hospital Cancer Center DAC for high-throughput microfluidic enrichment from whole leukopak for CTC-based liquid biopsy

  Whole genome sequencing and whole exome sequencing data of circulating tumor cells isolated from patients with metastatic prostate cancer and liver cancer.

  Dac EGAC50000000423

• Targeted Capture DNA Sequencing

  We performed targeted capture DNA sequencing for 29 genes in extranodal NK/T-cell lymphoma, nasal type (n=67).

  Study JGAS000548

• WTCCC2 Schizophrenia study

  A WTCCC2 project genome-wide case-control association study for schizophrenia (SP) in individuals from Ireland.

  Study EGAS00000000118

• shallow Whole-Genome sequencing of 14 TNBC tumor in the MATADOR trial - for in silico spike-in experiment

  14 TNBC tumors with tumor percentage ~90% were selected for in silico spike-in experiment

  Dataset EGAD50000001863

• Single-cell Full Transcriptome RNA sequencing

  Single cell full transcriptome sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD50000000201

• Array data for oesophageal and related samples – Ganguli et al (methylation array)

  Array data for oesophageal and related samples – Ganguli et al (methylation array)

  Dataset EGAD00010002682

• Severe acne GWAS meta-analysis

  Summary statistics of a GWAS meta-analysis for severe acne. A total of 7,441,713 genotyped and imputed variants were used for 5,602 European severe acne cases and 21,120 matched population controls.

  Dataset EGAD00001004419

• RNASeq files for Newman MAP3K8 melanoma

  RNASeq files for MAP3K8 melanoma paper titled "Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas"

  Dataset EGAD00001004567

• Bam files for the whole exome sequencing from the study on Spatial homogeneity in pediatric brain tumors.

  Bam files for the whole exome sequencing from the study on Spatial homogeneity in pediatric brain tumors.

  Dataset EGAD00001001055

• RNA-Seq for PTPN1 project (EGAS00001000554)

  Fastq files corresponding to RNA-Seq dataset for PTPN1 project (EGAS00001000554)

  Dataset EGAD00001001646

• Exome sequencing data for Mesothelioma

  Exome sequencing data for Mesothelioma

  Dataset EGAD00001001913

• RNA-Seq data for Mesothelioma.

  RNA-Seq data for Mesothelioma.

  Dataset EGAD00001001915

• Sequencing data for Murtaza et al. Nature Communications 2015 (doi:10.1038/ncomms9760)

  Exome and targeted amplicon sequencing data for tumor, germline and plasma samples from a patient with metastatic breast cancer.

  Dataset EGAD00001002108

• DATA FILES FOR MULLIGHAN MEF2D RNASEQ STRANDED

  DATA FILES FOR MULLIGHAN MEF2D RNASEQ STRANDED

  Dataset EGAD00001002692

• DATA FILES FOR MULLIGHAN MEF2D RNASEQ UNSTRANDED

  DATA FILES FOR MULLIGHAN MEF2D RNASEQ UNSTRANDED

  Dataset EGAD00001002704

• Whole exome sequencing study for 8 pairs of primary NSCLCs and distant metastases

  Whole exome sequencing study for 8 pairs of primary NSCLCs and distant metastases. This dataset includes a total of 30 samples.

  Dataset EGAD00001005764

• RNASeq files for Mullighan Leventaki ALCL Project

  RNASeq files for Mullighan Leventaki ALCL Project paper titled "Integrative molecular analysis of pediatric Anaplastic large cell lymphoma reveals subtypes with distinct immune suppression signatures."

  Dataset EGAD00001005951

• MT sequencing reads from WGS of 10 Egyptian individuals

  This data set contains for 10 Egyptian individuals the WGS reads mapping to chrM. These were subsequently used for haplogroup assignment.

  Dataset EGAD00001006038

• Single-cell Full Transcriptome RNA sequencing

  Single cell full transcriptome sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006325

• Single cell targeted RNA sequencing

  Single cell hybrid-capture targeted sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006327

• 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

• A98294A

  Whole genome sequencing for single cells for library A98294A 994 samples; filetype=bam

  Dataset EGAD00001008266

• Additional RNASeq files for Roussel MBPRP

  Additional RNASeq files for Roussel paper titled "Combination of CDK4/6 with BET-bromodomain and PI3K/mTOR inhibitors in medulloblastoma in vitro and in vivo"

  Dataset EGAD00001009394

• WES for Patient 1 to 8 of NIBIT-M4 clinical trial

  WES for Patient 1 to 8 of NIBIT-M4 clinical trial

  Dataset EGAD00001009701

• consHLA extra samples for comparison with clinical HLA types

  Samples not in other datasets for the paper titled; consHLA: a Next Generation Sequencing Consensus-based HLA Typing Workflow

  Dataset EGAD00001015625

• Helse Bergen HF Data Access Committee for the "Diettstudien" trial study dataset submitted to Federated EGA Norway

  This Data Access Committee is appointed by Helse Bergen HF to administer access requests for the "Diettstudien" trial study dataset, submitted to Federated EGA Norway.

  Dac EGAC50000000522

• Akershus University Hospital Data Access Committee for Immunoglobulin Heavy-Chain locus in Multiple Sclerosis datasets in FEGA Norway

  This is the Data Access Committee appointed by Akershus University Hospital (AHUS) for datasets from Immunoglobulin Heavy-Chain locus in Multiple Sclerosis studies.

  Dac EGAC50000000659

• Serrated Colorectal Cancer: An Emerging Disease Subtype

  This dataset represents two combined study populations. Serrated Colorectal Cancer: An Emerging Disease Subtype (called the Advanced Colorectal Cancer of Serrated Subtype Study or ACCESS Study) was a grant awarded to investigate a newly-recognized, biologically-distinct subtype of colorectal cancer (CRC) called “serrated CRC.” The objective of this project was to characterize factors related to the genetic predisposition, clinical presentation, and prognosis of serrated CRC. The study recruited incident invasive CRC cases diagnosed between April 2016 and December 2018, aged 20-74 years at diagnosis. Cases were identified through the Surveillance, Epidemiology and End Results (SEER) cancer registry serving 13 counties in western Washington State. Eligibility for all individuals was limited to those who were English-speaking and could consent. Participation included completing a baseline epidemiologic questionnaire shortly after diagnosis, optional donation of a saliva sample for genetic analysis, and optional consent to release of medical records and tissue specimens related to their diagnosis. Tumor specimens were tested for serrated CRC-defining molecular characteristics. Further, we have vital status on all participants and cause of death on those that have died since enrollment. Hormones and Colon Cancer: Epigenetic Subtypes, Risks, and Survival (called the Post-Menopausal Hormones Study or PMH Study) was a grant awarded to investigate the impact of post-menopausal hormone use on colon cancer risk, tumor molecular characteristics, and outcomes. Eligible cases were females, newly diagnosed with invasive colorectal adenocarcinoma between October 1998 and February 2002, aged 50 to 74 years. Cases were residents of 10 out of the 13 counties in western Washington State served by the Surveillance, Epidemiology and End Results (SEER) cancer registry. Eligibility for all individuals was limited to those who were English-speaking with available telephone numbers, in which they could be contacted. Unrelated population-based controls were randomly selected according to age distribution (in 5-year age intervals) of the eligible cases by using lists of licensed drivers from the Washington State Department of Licensing (for individuals aged 50 to 64 years) and rosters from the Health Care Financing Administration (now the Centers for Medicare and Medicaid, for individuals older than 64 years). Participation included completing a baseline epidemiologic questionnaire, optional donation of a saliva sample for genetic analysis, and (for cases only) optional consent to release of medical records and tissue specimens related to their diagnosis. Tumor specimens were tested for epigenetic and other molecular characteristics. The ACCESS study was supported by funding from the National Cancer Institute of the National Institutes of Health (NCI/NIH) (R01CA196337, PI: Newcomb, PA), as was the PMH Study (R01CA076366, PI: Newcomb, PA). Additional support for the PMH Study came from the Seattle site of the Colon Cancer Family Registry (SCCFR) (U01CA167551, PI: Jenkins, M, and U01/U24CA074794, PI: Newcomb, PA). Additional support for case ascertainment was provided by the Cancer Surveillance System of the Fred Hutchinson Cancer Center, which is funded by Contract Number HHSN261201300012I; NCI Control Number: N01 PC-2013-00012; Contract Number HHSN261201800004I; and NCI Control Number: N01 PC-2018-00004 from the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute with additional support from the Fred Hutchinson Cancer Center and the State of Washington. This research was also supported by the Genomics and Bioinformatics, Comparative Medicine, Specialized Pathology, Collaborative Data Services, and Experimental Histopathology Shared Resources of the Fred Hutch/University of Washington Cancer Consortium (P30 CA015704).Tumor marker testing was performed using formalin-fixed paraffin-embedded diagnostic tumor tissue specimens, and DNA extracted from those specimens. Testing for microsatellite instability (MSI) was based on either a 10-gene panel (BAT25, BAT26, BAT40, MYCL, D5S346, D17S250, ACTC, D18S55, D10S197, BAT34C4) or a 4-marker immunohistochemistry panel of DNA mismatch repair proteins (MLH1, MSH2, MSH6, PMS2). CpG island methylator phenotype (CIMP) testing was based on a validated quantitative DNA methylation assay using a five-gene panel (CACNA1G, IGF2, NEUROG1, RUNX3, SOCS1) or eight-gene panel (CACNA1G, IGF2, NEUROG1, RUNX3, SOCS1, MLH1, CRABP1, CDKN2A). Somatic p.V600E BRAF mutation status was tested for using a fluorescent allele-specific PCR assay. KRAS mutations in codons 12 and 13 were also assessed through forward and reverse sequencing of amplified tumor DNA. DNA was extracted from blood/saliva samples using conventional methods. The genotyping panel completed was the Build37 OncoArray500K-C, including 1%-6% blinded duplicates to monitor the quality of the genotyping. Quality control procedures were performed to 1) make sure that there were no patterns of missing data by batch, study, or plate, 2) check for gender discrepancies and kinship, 3) complete Principal Component Analysis, and 4) test for Hardy-Weinberg equilibrium (HWE). Samples were excluded based on call rate, heterozygosity, unexpected duplicates, gender discrepancy, and unexpectedly high identity-by-descent or unexpected genotypic concordance (>65%) with another individual. In addition, variants were excluded based on call rate (98%), lack of HWE in controls (P

  Study phs002171

• NIDDK IBD Genetics Consortium Repository Exome Chip

  The Illumina Infinium HumanExome+ BeadChip contains putative functional exonic variants selected from individual exome and whole-genome sequences from diverse populations. It includes nonsynonymous variants, splice variants and stop-altering variants. It also includes tags for previous GWAS-identified loci, ancestry informative markers, markers designed for identity by descent analyses, synonymous variants, fingerprint SNPs common to major genotyping platforms, mitochondrial SNPs, chromosome Y SNPs, and HLA tag SNPs. For more information as well as a detailed description of the variant calling and QC procedures, see Li et al. (2016). Li, D., et al. (2016) A pleiotropic missense variant in SLC39A8 is associated with Crohn's disease and human gut microbiome composition. Gastroenterology, 151, 1-9. PMID: 27492617.

  Study phs001723

• Whole-Exome Sequencing and Targeted DNA Sequencing of Matched Ocular Melanocytosis and Uveal Melanoma

  Ocular melanocytosis is the most important predisposing condition for the eye cancer uveal melanoma (UM). Here we used whole-exome and deep targeted sequencing to identify for the first time a clonal Gq pathway mutation in ocular melanocytosis, which gave rise to UM. Additionally, we elucidated the order in which canonical genetic aberrations were acquired during tumor evolution. These findings provide a mechanistic explanation for the well-known clinical association of ocular melanocytosis with UM, and they provide new insights into UM tumor evolution. Reprinted from: Durante MA, Field MG, Sanchez MI, Covington KR, Decatur CL, Dubovy SR, Harbour JW. Genomic evolution of uveal melanoma arising in ocular melanocytosis, with permission from Cold Spring Harbor Molecular Case Studies.

  Study phs001835

• VCRC Genetic Repository One Time DNA Protocol

  The purpose of this study is to identify genes that increase the risk of developing vasculitis, a group of severe diseases that feature inflammation of blood vessels. Better methods are needed to recruit patients with these rare diseases into cohorts of adequate size for high-quality genetics studies, and the existing infrastructure of the Vasculitis Clinical Research Consortium (VCRC) provides the means for such recruitment. Results of these studies will provide vasculitis researchers with insight into the causes of these diseases and generate new ideas for diagnostic tests and therapies, and will be of great interest to the larger communities of researchers investigating vasculitis and other autoimmune, inflammatory, and vascular diseases. This study will enhance the VCRC Data and Specimen Repository.

  Study phs001712

• Multi-Modal Single-Cell and Whole-Genome Sequencing of Small, Frozen Clinical Specimens

  Clinical application of single-cell sequencing technologies has been hampered by their need for quick processing of relatively large, fresh specimens. Here, we benchmarked the performance of a new technique for single-cell sequencing from snap-frozen clinical samples, vs. sequencing from fresh samples, on 5 samples from cutaneous melanoma brain metastasis, 6 samples from NSCLC brain metastasis, and 3 from uveal melanoma primary tumor. Additionally, we performed frozen sample sequencing of 20 uveal melanoma liver metastasis samples, and 3 cutaneous melanoma extracranial metastasis samples. Finally, for selected groups of the above-mentioned samples, we also performed TCR sequencing, SlideSeqV2 spatial transcriptomics, ultra-shallow whole-genome sequencing, and whole-exome sequencing, to present a comprehensive multi-modal profiling of all datasets.

  Study phs003097

• Autism Genome Project (AGP) Consortium - Whole Genome Association Study of over 1,500 Parent-Offspring Trios - Stage I and II

  Autism spectrum disorders (ASDs) are highly heritable (~90%), yet the underlying genetic determinants are largely unknown. To understand the genetic and phenotypic heterogeneity in ASDs, we analyzed 2,611 strictly defined ASD families with over 1,000,000 single nucleotide polymorphisms (SNPs), and applied multiple analytical strategies to examine these families for SNPs and Copy Number Variation (CNVs) affecting risk for ASDs. Secondary analyses examined associations in more homogenous subgroups. Furthermore, the use of large control datasets permitted contrasting case and control samples and addressed the potential increased burden of rare CNVs in ASD. Our data have allowed us to discern key features of the ASD genomic architecture, find new susceptibility loci, and chart a course for future studies in ASDs.

  Study phs000267

• Gene-Specific RNA Sequencing in PLCG2-Associated Immune Dysregulation with Cold Urticaria

  This study utilized gene-specific RNA-sequencing of PLCG2 to screen for disease causing in-frame exon-skipping transcripts of PLCG2 in a collection of 9 subjects with cold urticaria, 2 subjects with known PLCG2-associated antibody deficiency and immune dysregulation (PLAID)-causing deletions of PLCG2 (positive controls) and 3 healthy subjects (negative controls). Full length cDNA of PLCG2 was generated using gene specific reverse transcription of peripheral blood mononuclear cell RNA. The full length PLCG2 cDNA was used as the template to create Illumina sequencing libraries. To identify the underlying genetic basis for the exon-skipping transcripts, trio-based whole genome sequencing was performed for probands in whom in-frame exon-skipping transcripts of PLCG2 were identified.

  Study phs003807

• Single-Cell ATAC and RNA Sequencing of Human Breast Cancer Reveals Salient Cancer-Specific Enhancers

  Matched single-cell chromatin accessibility sequencing (scATAC-seq) and single-cell transcriptomic sequencing (scRNA-seq) were performed for 12 human breast tumor samples, 4 normal human mammary reduction samples, and 4 human breast cancer cell lines (HCC1143, SUM149PT, MCF7, and T47D). Both scATAC-seq and scRNA-seq assays resolved the underlying cellular heterogeneity in chromatin accessibility and transcriptional output for each patient sample. In this work, we quantitatively linked variation in chromatin accessibility to gene expression across malignant and non-malignant cell types from patient samples. We then showed that our findings were recapitulated in the breast cancer cell line samples. These data will serve as an important resource for the single-cell genomics and breast cancer research communities.

  Study phs003253

• Establishment and genomic analysis of mixed phenotypic acute leukemia cell lines

  Among acute leukemias, mixed phenotype acute leukemias (MAPL; mixed phenotype acute leukemiae), which have both acute myeloid and acute lymphocytic leukemia traits, are generally considered resistant to chemotherapy, especially those with t(9;22) MPAL has a poorer prognosis than other forms of MPAL and is a challenge to overcome. MPAL accounts for less than 1% of all acute leukemias, and the rarity of this disease makes it difficult to conduct clinical studies to develop treatments for the disease. Therefore, we planned to establish cell lines based on acute leukemia cells (JMPAL-1) obtained from MPAL patients, and to analyze information such as gene mutations related to disease development based on these cell lines for therapeutic purposes.

  Study JGAS000721

• Investigation of a method for generating cells for regenerative medicine using comprehensive nucleic acid analysis of iPS cell-derived cardiomyocytes.

  Regenerative medicine for heart failure is expected to restore cardiac function by using human iPS cells (hiPSCs). In our laboratory, it was shown that transplantation of cardiomyocytes (CMs) derived from hiPSCs into a pig model of myocardial infarction improves the disease condition. However, the instability of differentiation efficiency and tumorigenicity after transplantation are still issues to be resolved. We attempt to identify and analyze the genes and DNA methylation associated with the induction of differentiation of hiPSCs into CMs with the aim of achieving stable induction of CMs differentiation. Furthermore, we aim to analyze genes involved in tumorigenesis in CMs, and to develop a predictive marker for tumorigenesis to ensure the safety of cells before transplantation.

  Study JGAS000665

• Cergentis FFPE-TLC

  In this study, formalin-fixed paraffin-embedded targeted locus capture (FFPE-TLC) sequencing is used as a novel technology for targeted detection of tumor-specific genomic structural variants (SVs) in the primary tumor of 29 colorectal cancer patients with metastatic disease. The tumor region was macrodissected and sequenced for 29 patients, and the "normal" region of the same slide was macrodissected and sequenced for 8 of these patients. SVs were found in the common fragile site (CFS)-associated genes MACROD2, PRKN, FHIT and WWOX as well as SVs caused by three LINE transposable elements. Tumor-specificity of selected SVs was independently verified by droplet digital PCR of tumor tissue DNA and their applicability as plasma circulating tumor DNA biomarkers was demonstrated.

  Study EGAS50000000427

• TRAIP promotes DNA damage response during genome replication and is mutated in primordial dwarfism

  DNA lesions encountered by replicative polymerases threaten genome stability and cell cycle progression. Here we report the identification of mutations in TRAIP, encoding an E3 RING ubiquitin ligase, in patients with microcephalic primordial dwarfism/Seckel syndrome. We establish that TRAIP relocalizes to sites of DNA damage where it is required for optimal phosphorylation of H2AX and RPA2 during S-phase in response to UV irradiation, as well as fork progression through UV-induced DNA lesions. TRAIP is necessary for efficient cell cycle progression and mutations in TRAIP therefore limit cellular proliferation, providing a potential mechanism for microcephaly and dwarfism phenotypes. Human genetics thus identifies TRAIP as a novel component of the DNA damage response to replication-blocking DNA lesions.

  Study EGAS00001001501

• Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

  Tumor mutational burden (TMB) has emerged as a predictive biomarker of response to immune checkpoint inhibitors. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Here we evaluate bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples. In CheckMate 026, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne CDx™ assay. TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. Parameter variation can therefore impact TMB calculations, highlighting the need for standardization. Encouragingly, WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90) and differences could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms and centers is achievable.

  Dataset EGAD00001005035

• Kids First and INCLUDE: Down Syndrome, Heart Defects, and Acute Lymphoblastic Leukemia

  This project is a collaboration with the trans-NIH INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE (INCLUDE) Project, which seeks to improve health and quality-of-life for individuals with Down syndrome, and NHLBI's TransOmics for Precision Medicine (TOPMed) program, which seeks to apply omics technologies to improve scientific understanding of the fundamental biological processes that underlie heart, lung, blood, and sleep (HLBS) disorders. The data is also available at the INCLUDE Data Hub. Down syndrome (DS), which occurs due to trisomy 21, is one of the strongest risk factors for both congenital heart disease (CHD) and acute leukemia. For instance, children with DS have a 2000-fold increased risk of atrioventricular septal defects (AVSD) and a 20-fold increased risk of acute lymphoblastic leukemia (ALL). An important and innovative aspect of the Kids First program is understanding the overlap between structural birth defects and childhood cancer. Notably, the background of DS predisposes children to both of these phenotypes, however, the genomic architecture of risk remains largely undiscovered. In this joint Kids First/TOPMed/INCLUDE project, we are currently including >2,000 samples for whole-genome sequencing, including: 1) paired germline-tumor samples from children with DS-ALL; and 2) samples from families with DS-CHD. This work will advance our understanding of the developmental pathways that may lead to both structural birth defects and childhood cancer. The objectives of this study are to determine the genetic variants underlying AVSD and ALL risk in children with DS. Therefore, the aims of our study are: 1) compare whole-genome sequencing (WGS) data between children with documented DS-AVSD and children with DS who have structurally normal hearts to identify genetic variants that perturb heart development; and 2) compare WGS data between children with documented DS-ALL and children (from Aim 1) with DS who do not have a known history of ALL. We will also examine associations between germline mutations and somatic genomic features. This study will address the fundamental question of why children with DS have an elevated risk of AVSD and ALL. Insights into the genes that drive DS-AVSD and DS-ALL may have implications for improved genetic counseling, surveillance, clinical management, and treatment strategies for these children. Additionally, our findings may inform targeted therapies or interventions for children without DS who are at risk for structural birth defects and cancer. Additional Pediatric Cardiac Genetics Consortium (PCGC) data from children affected with Down syndrome and congenital heart disease are accessible through two separate dbGaP studies: phs001138 (Kids First) and phs001194 (TOPMed).

  Study phs002330

• Atezolizumab Plus Personalized Neoantigen Vaccination in Patients with Urothelial Cancer: a Phase 1 Trial

  This is a phase 1 single center clinical trial evaluating a multi-peptide personalized neoantigen vaccine, PGV001, in combination with atezolizumab for patients with urothelial cancer. Patients were enrolled in either the adjuvant or metastatic setting. Those in the adjuvant setting included patients considered high risk of recurrence (pathological stage ypT2-T4 or ypN+ for those treated with prior neoadjuvant chemotherapy or pT3-T4 or pN+ for those not treated with prior neoadjuvant chemotherapy). Those in the metastatic setting included patients progressing after prior chemotherapy or those with at least stable disease after chemotherapy treated as “switch maintenance” therapy. The primary endpoint was feasibility (including the number of neoantigens identified per patient, vaccine production time, the proportion of patients consenting to the vaccine development phase for whom a vaccine product was prepared, and the proportion of patients eligible for the treatment phase who completed the priming cycle 1 of PGV001 plus atezolizumab) and safety. Secondary endpoints included the objective response rate, progression-free survival or disease-free survival, overall survival, and immunomodulatory effects of treatment. Urothelial tumor tissue and normal tissue or peripheral blood specimens were utilized for DNA sequencing. HLA typing was performed utilizing genomic DNA isolated from whole blood, and RNA sequencing was performed utilizing tumor tissue specimens. Neoantigen prediction and final selection for incorporation into the vaccine was determined by the OpenVax computational pipeline. 12 patients were initially enrolled into the vaccine development phase and 10 patients initiated the treatment phase. PGV001 was administered with poly-ICLC and tetanus peptide on subsequent days for up to 10 doses, including an initial priming cycle 1. Atezolizumab was administered every 3 weeks for up to 1 year in the adjuvant setting or 2 years in the metastatic setting. The vaccine was feasible and safe, the median vaccine production time was 20.3 weeks, and 100% of patients that initiated the treatment phase completed the priming cycle. The most common treatment-related adverse events were local grade 1 injection site reactions, fever, and fatigue. Three of the 4 patients in the adjuvant setting remained disease-free at median follow-up of 39.5 months. There was a 40% objective response rate among patients with measurable disease in the metastatic setting. The single patient treated as “switch maintenance” therapy remained with no evidence of disease at 39.4 month follow-up. All patients demonstrated on-treatment neoantigen-specific T cell reactivity, as measured by ELISPOT and flow cytometry assays. Overall, PGV001 plus atezolizumab was feasible, safe, and warrants further investigation. Whole exome sequencing from tumor tissue and normal tissue or whole blood specimens and RNA sequencing from tumor tissue specimens will be available through dbGaP.

  Study phs003922

• Surgery in combination with immune checkpoint therapy as an effective treatment for patients with metastatic cancer.

  Abstract Surgical removal of primary tumors was shown to reverse tumor-mediated immune suppression in pre-clinical models with metastatic disease. However, how cytoreductive surgery in the metastatic setting modulates the immune responses in patients, especially in the context of immune checkpoint therapy (ICT)-containing treatments is not understood. Here, we report the first prospective, non-comparative clinical trial (N=104) using three different ICT-containing strategies plus cytoreductive or “debulking” surgery to remove the primary tumor-bearing kidney or a metastatic lesion as a treatment for patients (N=43) with metastatic clear cell renal cell carcinoma (mccRCC). For those patients (N=61) who were not candidates for cytoreductive surgery, a biopsy was obtained instead for correlative biological studies. Our data demonstrated that the combination of ICT with cytoreductive surgery was safe and feasible in patients with mccRCC. The 2-year overall survival was 84% with a median OS of 54.7 months for patients who received ICT containing regimens plus surgery. Immune-monitoring studies with co-detection by indexing (CODEX) identified distinct tumor spatial conformation of cellular subsets as a novel and improved predictor of response to ICT. Importantly, single-cell RNA-sequencing data demonstrated that surgical removal of the tumor increased antigen-presenting dendritic cell population with a concurrent reduction in KDM6B expressing immune-suppressive myeloid cells in the peripheral blood. Together, this study highlighted the feasibility of combining ICT with cytoreductive surgery in a metastatic setting and demonstrated potential enhancement of immune responses following ICT plus cytoreductive surgery in patients with metastatic disease.

  Study EGAS00001005667

• Novel Factors for Unexplained Phenotypes of Subclinical Carotid Atherosclerosis

  The overall goal for this study was to determine the genetic factors associated with extreme phenotypes of subclinical atherosclerosis (protective and deleterious). Study participants were selected from the Northern Manhattan Study (NOMAS), a population based cohort study investigating stroke and stroke risk factors in Northern Manhattan. Cases and controls were individuals at the extreme ends of the distribution for carotid intima-media thickness and carotid plaque, with cases defined as individuals with subclinical atherosclerosis that could not be explained by traditional vascular risk factors (USAth) and controls defined as individuals with unexplained protection against atherosclerosis (UPAth).

  Study phs001560

• Biesecker Lab (NHGRI) Whole Genome Medical Sequencing for Gene Discovery

  We aim to use whole-genome medical sequencing (WGMS) to discover causative molecular lesions for a set of rare, severe phenotypes hypothesized to be caused by either somatic mutations, germline de nova heterozygous mutations, germline inherited recessive, or germline inherited dominant mutations in currently unknown or uncharacterized genes. The goal of this research is threefold: to identify causative sequence variants for disorders whose molecular etiology was previously unknown, to apply this insight to both the rare disorders under study and more common phenotypes, and to enhance the study of mutation on a genome-wide level.

  Study phs001348

• Stanford Center for Urologic Genomics: Genomic Analysis of Benign Prostatic Hyperplasia

  Benign prostatic hyperplasia (BPH) entails growth in the central regions of the prostate gland and is common among older men. BPH obstructs urinary outflow, resulting in voiding symptoms for which current treatments that target prostate physiology are only partially effective. A better understanding of BPH may suggest new treatment strategies that target its pathophysiology. The overall goal of the study is to apply next-generation sequencing-based approaches to investigate BPH, to discover new insight into BPH disease processes and new targets for precision therapy, and to determine whether the hyperplasia reflects underlying clonal expansions of prostatic cells.

  Study phs001698

• Development of Novel Synovial Sarcoma Organoids Models for Drug Discovery

  Although synovial sarcoma has been studied using established cell lines and mouse models, effective treatments remain limited. We treated five patients with synovial sarcoma between 2022 and 2023 and established organoid cultures from resected tumor specimens using a modified air-liquid interface method. After serial passaging, organoids were successfully xenografted into NOD-scid IL2Rgnull (NSG) mice in three cases. The established organoids retained SS18-SSX fusion transcripts and demonstrated histological and genetic similarities to the original tumors. These organoid models provide a reliable platform for studying synovial sarcoma biology and hold promise for the development of novel therapeutic strategies.

  Study JGAS000806

• Whole-Genome Shotgun Metagenomic Analysis of Rectal Mucus for Colorectal Cancer Detection

  This study evaluates the use of rectal mucus as a minimally invasive biospecimen for colorectal cancer (CRC) detection through whole-genome shotgun metagenomic sequencing. 408 rectal mucus samples were collected from patients suspected to have colorectal cancer and sequenced. These samples were analyzed to characterize microbial community composition and its association with CRC stage and anatomical site. These data provide insights into tumor-proximal microbiome signatures and demonstrate the potential of rectal mucus sampling for early and accurate CRC diagnosis. This is 1 of 4 sequencing experiments on the same sample type.

  Study EGAS50000001310

• Gut 16S rRNA/FINRISK 2002

  Gut microbiome 16S rRNA raw data for N=7174 FINRISK 2002 participants. FINRISK fecal samples were mailed to the Knight laboratory at the University of California (San Diego, CA), for microbiota sequencing using the standard Earth Microbiome Project protocols (https://earthmicrobiome.org/protocols-and-standards/). DNA was extracted using a magnetic bead-based DNA extraction protocol. Amplicon sequence data for the V4 region of the 16S rRNA gene was generated using 515F (Parada) and 806R (Apprill) primers. For a total of 25μl reaction volume, 13 µl PCR-grade water was combined with 10 µl PCR master mix (Platinum Hot Start PCR Master Mix, 2x, ThermoFisher), 0.5 µl forward primer (10 µM), 0.5 µl reverse primer (10 µM), and 1 µl template DNA. Amplification was performed in triplicate reactions, and triplicate PCR reactions were pooled afterwards. Expected products were visualized on agarose gels (300–350 bp) and quantified with Quant-iT PicoGreen dsDNA kit (Invitrogen). Equal amounts (240 ng) of amplicon were combined for each sample and cleaned (MoBio UltraClean PCR Clean-Up Kit). Cleaned amplicon pools were sequenced with 515F and 806R primers.

  Dataset EGAD50000000287

• Whole-genome sequence data for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  Each tumor sample was cut into three pieces, yielding two end-pieces for cryovials and a middle portion placed in 10% buffered formalin. End pieces were homogenized manually and with a paddle blender (Stomacher). All paraffin-embedded blocks, including formalin-fixed tumor samples and molecular-fixed fallopian tubes, were sectioned and stained with hematoxylin and eosin prior to expert histopathological review to confirm the presence of high grade serous carcinoma. Homogenized end pieces were then flash frozen and later used for WGS. For all tumor and matched normal (peripheral blood) samples, DNA was extracted with the Qiagen AllPrep DNA/RNA kit (tumor samples from patients 25,26,28-32) or the Qiagen Blood and Tissue Extraction Kit (tumor samples from patients 1-4,7,9-17, and all blood samples). For all tumor and normal samples, DNA extraction was followed by library construction and sequencing using Illumina HiSeq2500 whole genome shotgun v4 chemistry with paired-end 125bp reads.

  Dataset EGAD00001003984

• Chromatin accessibility maps of chronic lymphocytic leukemia identify subtype-specific epigenome signatures and transcription regulatory networks

  Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay, and we also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research.

  Dataset EGAD00001002110

• Single-cell gene expression data from CD8+ T cells from two Austrian COVID19 patients stimulated with wildtype and mutant SARS-Cov-2 peptides

  The data contains single-cell gene sequencing data (10x Genomics) from FACS-purified CD8 T lymphocytes from two Austrian patients. The cells were stimulated with one MHC class I peptides obtained from a common (wild type) variant and an emerging mutant variant of the SARS-Cov-2 virus. Then the samples were multiplexed using hashtag oligos. We provide the raw and aligned sequence data for: i. The single-cell experiments ii. The PCR-amplified samples for enrichment of the hashtag oligo multiplexing barcodes iii. The PCR-amplified samples for enrichment of the T Cell Receptor (TCR) VDJ region for immuno-profiling. The samples and libraries were processed and obtained in collaboration between St. Anna Children's Cancer Research Institute (CCRI), CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, and the Medical University of Vienna. The cell barcodes and processed data has been submitted to the GEO database with GEO accession GSE166651.

  Dataset EGAD00001006995

• Adult-type Granulosa Cell Tumour of the Ovary RNA Sequencing

  We analyzed 34 AGCTs (19 primary and 15 recurrent) and the KGN cell line by RNA-Seq. Our cohort comprised of 3 AGCTs WT for FOXL2, 28 heterozygous and 3 homo/hemizygous for the pathogenic variant. Fresh-frozen AGCTs were selected from OVCARE’s Gynecological Tissue Bank in Vancouver, Canada for bulk RNA-seq. RNA was extracted from frozen tissue and sections adjacent to the scrolls submitted for RNA-seq were stained with hematoxylin and eosin (H&E) to evaluate tumour cell purity. Cases with >80% tumour cell purity were selected for sequencing with the majority of cases (29 of 34 patients) containing >90% tumour cells. Ribodepleted RNA libraries were constructed and paired-end sequencing (125 base pair reads) was performed.

  Dataset EGAD00001007812

• Genomic and Functional Profiling of Acral Melanoma from the admixed Brazilian Population Reveals Disease Drivers and Targetable Vulnerabilities

  Acral melanoma, a subtype of melanoma characterized by its occurrence on palms, soles, and beneath the nails, presents unique challenges in diagnosis and treatment due to its distinct genetic and environmental factors. Despite recent advancements in targeted therapies for melanoma, the efficacy of treatments in acral melanoma remains limited, emphasizing the urgent need for a deeper understanding of its genetic landscape. CRISPR-based functional genomics screening has emerged as a powerful tool for uncovering genetic dependencies and potential therapeutic targets in various cancers. In this project, we present the results of CRISPR screening performed on acral melanoma cell lines to identify genes essential for cell survival and proliferation collectively termed “fitness". Through this screening approach, we aim to elucidate the molecular mechanisms underlying the pathogenesis of acral melanoma and identify novel therapeutic vulnerabilities. Our findings reveal key genetic drivers and pathways implicated in acral melanoma progression, offering potential targets for the development of precision therapies tailored to this aggressive subtype of melanoma

  Dataset EGAD00001015690

• Multiomic analysis of CD4+ T cells from blood, lymph node and tumor of NSCLC patients

  This dataset contains data derived from FACS-sorted CD4+ T cells. This dataset contains FASTQ files for: - paired blood, lymph node, and tumor single-cell RNA-seq (scRNA-seq) samples from 5 patients with NSCLC (including scRNA-seq coupled to scTCR-seq for 3 patients), - paired blood, lymph node, and tumor single-cell ATAC-seq (scATAC-seq) samples from 2 patients with NSCLC, - lymph node and tumor bulk RNA-seq and TCR-seq data from CD4+ T cell subsets (Treg-Tfr, Treg-Trm, Treg-Naive, Tconv-Tfh, Tconv-CXCL13, and Tconv-Naive) from 5 patients (one patient has lymph node samples only). In addition, this dataset includes processed analysis files: - Seurat object for scRNA-seq data, - fragment files generated by Cell Ranger for scATAC-seq samples, - contig annotations generated by Cell Ranger for scTCR-seq samples. Sequencing was performed using Illumina NovaSeq, MiSeq, or HiSeq Rapid Run platforms.

  Dataset EGAD50000000424

• LCCC1122: Defining the Triple Negative Breast Cancer Kinome Response to GSK1120212

  In this study the investigators looked at adaptive reprogramming impact on the kinome when a MEK inhibitor called GSK1120212 (trametinib) was administered in a "window of opportunity" trial. GSK1120212 is not yet approved by the FDA for use in breast cancer patients. The investigators gave GSK1120212 for a short period of time (one week) to examine MEK and the other kinase expression in cancer cells both before and after the study drug is given. The investigators gave this drug for research purposes only. The length of time it was given is not intended to treat cancer. Recently researchers at UNC developed a process that can comprehensively profile the majority of the individual kinases in the kinome and examine the impact on kinase expression of kinase inhibitors (Duncan et al, Cell 2012, PMID: 22500798). This can tell us which kinases need to be concurrently blocked to augment responsiveness and prevent acquired resistance so that the investigators can design the best combinations of kinase blocking drugs for triple negative breast cancer. This is especially important for individuals with triple negative breast cancer (TNBC) because there are no targeted drugs available that can block molecules that affect tumor growth. The investigators believe that kinase-blocking drugs have the potential to be a more effective treatment for people with TNBC. In this recently published study (Zawistowski et al, Cancer Discovery 2017, PMID: 28108460), TNBC patients treated with trametinib for 7 days resulted in a transcriptional response characterized by significant reprogramming of the tyrosine kinome, and this adaptive bypass response in human tumors was found to be similar to that seen in preclinical models including TNBC cell lines and mouse xenografts. In this study we also examined whether reprogramming differed between TNBC molecular subtypes, finding that basal-like and claudin-low human TNBC cells and mouse tumor subtypes had different adaptive transcriptional responses to MEK-ERK inhibition. Mechanistically we found that genome-wide enhancer remodeling drove the adaptive transcriptional response, suggesting that epigenetic approaches to reprogramming may be more durable than kinase inhibitor polypharmacology.

  Study phs001405

• Genome-Wide Pleiotropy Scan Across Multiple Cancers

  A whole-exome sequencing (WES) study was conducted in 3,233 cases diagnosed with multiple primary cancers and 3,229 matched cancer-free controls (90% non-Hispanic white, 3% African-American, 3% East Asian, and 4% Latino) selected from individuals in the Kaiser Permanente Research Bank (KPRB) who were members of the Kaiser Permanente Northern California (KPNC) health plan. Cancer-free controls were matched to cases on age at specimen collection (within 2 years), sex, genotyping array (which matched on self-reported race/ethnicity), closest distance using the first two principal components for genetic ancestry, and reagent kit. Cases and controls were drawn from two prospective KPRB cohorts: the Research Program on Genes, Environment and Health (RPGEH) and the ProHealth study. Participants were sequenced by the Regeneron Genetics Center using the Illumina NovaSeq 6000 platform, and sample preparation and quality control were performed using a high-throughput, fully-automated system [PMID: 33087929]. Reads were aligned to the GRCh38 reference genome, and variants were called using WeCall [PMID: 33087929]. Participants with sex discordance, 20x coverage at less than 80% of targeted sites, and/or contamination greater than 5% were excluded. After quality control, we retained n = 6,247 (3,111 cases, 3,136 controls) individuals for downstream analyses. Among participants selected for this WES study, n = 5,432 (2,299 cases; 3,133 controls) consented to deposition of data to the National Institutes of Health (NIH).Further quality control was applied to filter low quality variants. Genotype calls with low depth of coverage (DP) were updated to missing (DP < 7 for SNPs and DP < 10 for indels), after which sites with low allele balance (AB) - variants without at least one sample having AB ≥ 15% for SNPs or AB ≥ 20% for indels - were removed. Lastly, variants with missingness > 10% and Hardy-Weinberg equilibrium p-value < 10-15 were excluded. Further description of quality control and downstream single-variant and gene-based analyses is available in Cavazos et al, 2022 [medRxiv].

  Study phs002809

• TK-EPN862 - Patient-dervied xenograft model of Posterior Fossa A Ependymoma - RNAseq

  Ependymomas (EPN) are the third most common malignant brain cancer in children. Treatment strategies for pediatric EPN have remained unchanged over recent decades, with 10-year survival rates stagnating at just 67% for children aged 0-14 years. Moreover, patients who survive treatment for the most common subtype of pediatric EPN (posterior fossa A (PFA)), often suffer long-term neurological side effects as a result of therapy. It is evident that there is a need for safer, more effective treatments for pediatric EPN patients. There are ten distinct subgroups of EPN, each with their own molecular and prognostic features. To identify and facilitate the testing of new treatments for EPN, in vivo laboratory models representative of the diverse molecular subtypes are required. Here, we describe the establishment of a patient-derived orthotopic xenograft (PDOX) model of PFA EPN, derived from a metastatic cranial lesion. Patient and PDOX tumors were analyzed using immunohistochemistry, DNA methylation profiling, whole genome sequencing (WGS) and RNA sequencing. Both patient and PDOX tumors classified as PFA EPN by methylation profiling, and shared similar histological features consistent with this molecular subgroup. RNA sequencing revealed that gene expression patterns were maintained across the primary and metastatic tumors, as well as the PDOX. Copy number profiling revealed gains of chromosomes 7, 8 and 19, and loss of chromosomes 2q and 6q in the PDOX and matched patient tumor. No clinically significant single nucleotide variants were identified, consistent with the low mutation rates observed in PFA EPN. Overexpression of EZHIP RNA and protein, a common feature of PFA EPN, was also observed. Despite the aggressive nature of the tumor in the patient, this PDOX was unable to be maintained past two passages in vivo. Others who have successfully developed PDOX models report some of the lowest success rates for EPN compared to other pediatric brain cancer types attempted, with loss of tumorigenicity not uncommon, highlighting the challenge in propagating these tumors in the laboratory. Here, we discuss our collective experiences with PFA EPN PDOX model generation and propose potential approaches to improve future success in establishing preclinical EPN models

  Study EGAS00001006844

• EGA metadata schema

  EGA Schemas In this page, you will find information on how the European Genome-phenome Archive (EGA) manages its metadata standards using both XML Schema Definition (XSD) and JavaScript Object Notation (JSON) formats. If you are not sure what this means, you may want to explore our brief metadata introduction. This information may be of your interest if you are planning to learn more about how the EGA is built and how to wrap around it for other processes. Nevertheless, if you are a common user (e.g. submitter or requester), you would not have to worry about these schemas nor their format, since they are implemented in user-friendly ways for you. Metadata standards are rules that define how to format and structure data of metadata objects (i.e. entities), like EGA's samples or experiments in a consistent manner. These objects are the nodes of the metadata model of the EGA (Figure 1). Figure 1. Diagram of EGA's metadata model. The model's building blocks are objects (e.g. sample), which can reference each other (e.g. an experiment referencing the used samples). Once your files are uploaded, they can also be referenced by Runs and Analyses. The submission object is an object itself that compiles many others. At EGA, we inherit our metadata schemas from the European Nucleotide Archive (ENA), and we have expanded them to include bespoke objects such as "Policy", "Dataset", and "DAC" (Data Access Committee) for our specific use-case: handling sensitive human data. See below a list of all our metadata objects and some context for each. Metadata Object EGA accession Description Examples of metadata fields Study EGAS… Information about the study Study type, study title, study abstract… Sample EGAN… Information about the used samples in the experiment or analysis Taxon ID, scientific name, biological sex, phenotype… Experiment EGAX… Information about the performed experiment Used libraries, sequencing platform, reference to the used samples… Analysis EGAZ… Contains information about the analysis Type of analysis, used assembly, reference sequence… Run EGAR… The run holds information about the files containing the raw reads generated in a run of sequencing Platform, spot descriptor, raw file references… DAC EGAC… Contains information about the Data Access Committee (DAC) DAC contacts, contact emails… Policy EGAP… Contains the Data Access Agreement (DAA) and policy which its usage complies with Policy text, data use ontologies (DUO) codes… Dataset EGAD… Contains the collection of runs/analysis to be subject to controlled access Dataset type, compilation of Run's and Analysis' IDs There are two different sets of schemas, based on their formats, in which the EGA accepts metadata: XSDs (for XML files) and JSON Schemas (for JSON files). EGA's XML Schema Definition . When programmatic submissions are pushed through the European Bioinformatics Institute (EBI) system, XML format is used. The schemas that are applied for this format are defined in XML Schema Definition (XSD) files, which can be found at ENA's GitHub repository. You can find more information on how to validate and submit your data programmatically in our programmatic submission documentation. Furthermore, see at our GitHub repository some XML examples with either made-up values (similar to what you would submit) or descriptive values for each field (just for documentation). EGA's JSON Metadata Schemas . When programmatic submissions are pushed through the Centre for Genomic Regulation (CRG) system, JSON format specifications are used instead. See the full JSON specifications for further details. In conclusion, the EGA metadata schemas are crucial for maintaining the quality and consistency of submitted data. By understanding and following the rules outlined in these schemas, you can ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource. Sample checklists Besides the standards in our schemas, we have another layer called Sample checklists. These are another system that the EGA inherits from ENA, and specifies what attributes are required or allowed for a sample object. The EGA uses these checklists to enforce that, for example, a sample object has the three mandatory attributes: subject ID, sex and phenotype of the individual the sample was taken from. When you submit to EGA, our checklist is automatically selected by default.

  Documentation submission/metadata/ega-schema

• Genome-Wide Analysis for Addiction Susceptibility Genes

  Genome wide analysis for addiction susceptibility genes is an affected sibling pair linkage study using subjects who were patients in methadone replacement treatment programs (MMTP). Such patients are highly addicted to opioids and usually to other addicting substances as well. For entry into the programs, patients had to be at least 18 years of age and had to satisfy DSM-IV criteria for opioid dependence. Despite their common substance use disorder diagnosis, patients enrolled in MMTPs generally have a heterogeneous mix of co-morbid psychiatric disorders including anti-social personality disorder, major depression and anxiety disorders, and often satisfy DSM-IV criteria of substance use disorders other than opioid dependence. Genetic analysis was carried out using genotyping data obtained from a 10K SNP array, and non-parametric linkage was assessed using MERLIN. This resulted in the identification of a linkage peak on 14q that overlapped the NRXN3 gene (neurexin 3), which was previously identified as a potential candidate gene for addiction, and subsequently identified as a target gene in other addiction studies and autism. In version 2 of this study, a text file containing 7704 SNPs with large allele frequency discrepancy as compared to 1000 Genomes is included. Users have the option to exlude these 7704 SNPs.

  Study phs001266

• Gabriella Miller Kids First Pediatric Research Program for Infantile Hemangiomas Associated with Multi-Organ Structural Birth Defects

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Infantile hemangiomas are the most common benign vascular tumor in infants, affecting 4-5% of children. Thirty percent of segmental infantile hemangiomas on the face and scalp are associated with birth defects of multiple organs. This condition is known as PHACE, an acronym for posterior fossa brain malformations, segmental facial hemangiomas, arterial anomalies, cardiac defects, eye anomalies, and sternal clefting. Genomic analysis of PHACE will inform treatment and expand knowledge about the causes of birth defects affecting the brain, arteries, heart, eye, midline development and hearing. The knowledge gained in this study will be used to drive strategies for prevention and provide critical targets for treatments for a range of birth defects and infantile hemangiomas.

  Study phs001785

• Center for Common Disease Genomics [CCDG] Neuropsychiatric: Autism Spectrum Disorder (ASD) – Whole Exomes

  The National Human Genome Research Institute (NHGRI) has funded a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Called the Centers for Common Disease Genomics (CCDG), this initiative will explore a range of diseases with the ultimate goal of 1) undertaking variant discovery for enough different examples of disease architectures and study designs to better understand the general principles of the genomic architecture underlying common, complex inherited diseases, 2) understanding how best to design rare variant studies for common disease, and 3) developing resources, informatics tools, and innovative approaches and technologies for multiple disease research communities and the wider biomedical research community. The initial focus of the CCDGs will be in cardiovascular disease (early-onset coronary artery disease, atrial fibrillation, hemorrhagic stroke), neuropsychiatric disease (epilepsy, autism), and autoimmune/inflammatory disease (type 1 diabetes, inflammatory bowel disease). The Broad Institute is one of four selected CCDG project centers. The goal of the Autism Spectrum Disorder (ASD) program is to work together to utilize dramatic new advances in DNA sequencing technology to reveal the genetic architecture of autism through comprehensive examination of the exotic sequence of all genes.

  Study phs002502

• LySeqST: A targeted sequencing assay for robust genomic classification of diffuse large B-cell lymphoma

  Diffuse large B-cell lymphoma (DLBCL) is a biologically heterogeneous disease. Two genomic classification systems, LymphGen and DLBclass, are capable of reproducibly classifying single tumors into subtypes with prognostic relevance in the context of standard-of-care R-CHOP chemoimmunotherapy. Preliminary data from subgroup analyses of clinical trials suggest that the distinct biological features are targetable with drugs that exploit subtype-specific vulnerabilities, and large clinical trials are being designed to test this hypothesis. Although whole exome sequencing (WES) remains the gold standard for each of these classification systems, many laboratories may opt for smaller targeted sequencing panels that reduce costs associated with sequencing, data storage, and processing. Here, we describe the design and validation of a targeted sequencing panel (LySeqST) that captures the genomic features required specifically for LymphGen classification. We perform in silico and real-world validation vs. WES data and demonstrate that LySeqST can be used to accurately classify DLBCL tumors. In an unselected population-based cohort, we determine the real-world proportions and validate the prognostic relevance of LymphGen subtypes, confirming that only tumors expressing the dark zone gene expression signature are consistently associated with inferior outcomes. Our results support the use of LySeqST for accurate genomic classification of DLBCL.

  Study EGAS50000001601

• Rapid identification of somatic genome rearrangements as personalized biomarkers for blood-based cancer monitoring

  Increasing evidence shows the value of circulating tumour DNA (ctDNA) to detect cancer and monitor its progression. Somatic genomic structural variations (SVs) are promising personalized biomarkers for sensitive and specific detection of ctDNA in liquid biopsies. However, accurate, affordable, and fast identification of such SV biomarkers is challenging, which hinders routine use in the clinic. Here, we demonstrate a novel approach - termed SHARC - for rapid discovery of somatic SV breakpoints as personalized tumour biomarkers. SHARC combines low-coverage cancer genome sketching by using Oxford Nanopore portable sequencing with a random forest classification and a dedicated filtering pipeline to enrich for somatic SVs. Our method leverages the real-time and long-read capabilities of Nanopore sequencing to identify somatic SV breakpoints at nucleotide resolution from a tumour biopsy within two days. We applied SHARC to tumour samples of high-grade ovarian and prostate cancer and validated on average 10 somatic SVs per sample with the use of PCR mini-amplicons. Finally, we demonstrate that these somatic SV biomarkers can be used to detect tumour presence from liquid biopsies in a quantitative manner and we retrospectively monitored treatment response in patients with prostate cancer, demonstrating its potential benefit for clinical practice.

  Study EGAS00001003963

• Bisulfite-converted duplexes for the strand-specific detection and quantification of rare mutations

  The identification of mutations that are present at low frequencies in clinical samples is an essential component of precision medicine. The development of molecular barcoding for next generation sequencing has greatly enhanced the sensitivity of detecting such mutations by massively parallel sequencing. However, further improvements in specificity would be useful for a variety of applications. We herein describe a technology (BiSeqS) that can increase the specificity of sequencing by at least two orders of magnitude over and above that achieved with molecular barcoding and can be applied to any massively parallel sequencing instrument. BiSeqS employs bisulfite treatment to distinguish the two strands of molecularly barcoded DNA; its specificity arises from the requirement for the same mutation to be identified in both strands. Because no library preparation is required, the technology permits very efficient use of the template DNA as well as sequence reads, which are nearly all confined to the amplicons of interest. Such efficiency is critical for clinical samples, such as plasma, in which only tiny amounts of DNA are often available. We show here that BiSeqS can be applied to evaluate transversions, as well as small insertions or deletions, and can reliably detect one mutation among >10,000 wild type molecules.

  Study EGAS00001002406