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• 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

• Rapid Acceleration of Diagnostics - Digital Health Technologies (RADx-DHT): Digital Health Solutions for COVID-19: COVID Community Action and Research Engagement (COVID-CARE)

  Vibrent Health will expand the Vibrent Digital Health Solutions Platform (DHSP) implementation to additional populations among diverse user groups for additional validation of the technology's performance, usability, and reliability in refinement of analytics generating predictive algorithms for infection and that support individual, organizational, community and societal-level decision-making in the COVID-19 pandemic response. This includes the aims to innovate a technology that can differentiate between COVID-19 and flu (or other respiratory illness); develop and test a novel WIFI-based contact tracing tool using a University’s enterprise WIFI system and software release of augmented contact tracing capabilities in Vibrent's DHSP; and develop a full technical integration approach and strategy to support data exchange between this solution and the NCI data hub.DOI: https://rapids.ll.mit.edu/10.57895/ravs-1b57

  Study phs002533

• A Human Lymphoma Organoid Model for Evaluating and Targeting the Follicular Lymphoma Tumor Immune Microenvironment

  Heterogeneity in the tumor microenvironment (TME) of follicular lymphoma (FL) can affect clinical outcomes. We developed a new organoid culture method for cultivating patient-derived lymphoma organoids (PDLOs), which include cells from the native FL TME. We generated organoids from 12 FL patients at diagnosis, clinical progression, or relapse. These organoids were profiled with targeted DNA sequencing and mRNA sequencing. We evaluated the stability of organoids in culture at serial weekly timepoints (D0, D7, D14, D21). We treated organoids with CD19:CD3 or CD20:CD3 bispecific antibodies or unconjugated anti-CD20, anti-CD19, and anti-CD3 as a control, and profiled DNA/RNA at D11 to evaluate treatment response. This system is intended as a platform for advancing precision medicine efforts in FL through patient-specific modeling, high-throughput screening, TME signature identification, and treatment response evaluation.

  Study phs003410

• RNA-seq as a tool for evaluating human embryo competence

  The majority of embryos that are created through IVF do not implant. It seems plausible that rates of implantation would improve if we had a better understanding of molecular factors affecting embryo competence. Currently, the process of selecting an embryo for uterine transfer utilizes an ad-hoc combination of morphological criteria, the kinetics of development, and genetic testing for aneuploidy. However, no single criterion can ensure selection of a viable embryo. In contrast, RNA-sequencing of embryos could yield highly dimensional data, which may provide additional insight and illuminate the discrepancies among current selection criteria. Indeed, recent advances enabling the production of RNA-sequencing (RNA-seq) libraries from single cells have facilitated the application of this technique to the study of some transcriptional events in early human development. However, these studies have not assessed the quality of their constituent embryos relative to commonly used embryological criteria. Here, we perform proof-of-principle advancement to clinical selection procedures by generating high quality RNA-seq libraries from a trophectoderm biopsy as well as the remaining whole embryo. We combine state-of-the-art embryological methods with low-input RNA-seq to develop the first transcriptome-wide approach for use in future predictive embryology studies. Specifically, we demonstrate the capacity of RNA-seq as a promising tool in preimplantation screening by showing that biopsies of an embryo can capture valuable information content available in the whole embryo from which they are derived. Furthermore, we show that this technique can be used to generate a RNA-based digital karyotype, and to identify candidate competence-associated genes. Together, these data establish the foundation for a future RNA-based diagnostic in IVF.

  Dataset EGAD00001005044

• scRNAseq of colonic organoids derived from biopsies taken from healthy human individuals treated with IL22

  scRNAseq dataset of colonic organoids derived from epithelium from biopsies taken from three healthy human individuals. The organoids have either been grown in standard conditions (control) or treated with IL22 (treated). Includes 6 samples in total, one control from each individual (ctrl1, ctrl2, ctrl3) and one treated from each (treat1, treat2, treat3). The samples have been multiplexed using the antibody hashing technique. The 6 samples have been pooled into the one organoids sample. In order to analyse the raw files, they have to be demultiplexed first. Information necessary for demultiplexing, as well as which files belong to which sample, can be found in the map_file.csv, attached to each sample. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into HTO (hashtag) and RNA (transcriptome) files. HTO has one index (I1) and two read (R1, R2) files and RNA has two index (I1, I2) and two read (R1, R2) files. The fastq files are for the pooled (organoids) sample and need to be demultiplexed. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Since count matrices have been created after the demultiplexing step, there’s one matrix for each of the 6 individual samples. scRNA-seq data from human colon organoids was analysed in the same manner as for the Colitis dataset, apart from the following changes. Data was generated with the Cell Hashing technique, which uses oligo-tagged antibodies against surface proteins to barcode single cells. This allows for samples to be multiplexed together and run in a single experiment. The data was demultiplexed using the HTODemux() function from Seurat (Hao et al., 2021).

  Dataset EGAD00001010168

• Nature and Contribution of Noncoding, Regulatory Mutations in Neurodevelopmental Disorders

  This dbGaP study contains variant call files generated from whole-genome sequencing data of families with autism. The variant callers include FreeBayes, GATK, Platypus, and Strelka2. A family-level VCF file, from each caller, is provided for each family in the study. The families included in this study are from the Simons Simplex Collection (SSC), the Study of Autism Genetics Exploration (SAGE), and The Autism Simplex Collection (TASC); sequencing was performed at the New York Genome Center, as part of the Centers for Common Disease Genomics (CCDG) Consortium. The analysis to generate the variant callsets was supported by a K99 Pathway to Independence grant to Dr. Tychele Turner (1K99MH117165-01). *Access to phenotype data at the individual level for Simons Simplex Collection (SSC) subjects can be requested from SFARI Base: https://www.sfari.org/resource/sfari-base/.

  Study phs001874

• PDAC Prognosis Biomarkers in Genomic and Transcriptomic Molecular Data

  Our study was designed to identify biomarkers related to the prognosis of Pancreatic Ductal AdenoCarcinoma (PDAC) patients using genomic variants and gene expression in coding regions of the human genome (exome). PDAC is the 7th cause of cancer deaths and is among types of cancer having the poorest prognosis. To improve treatment outcomes of PDAC, biomarkers related to PDAC prognosis are needed. The goals of our study are to find genomic and transcriptomic biomarkers, which can classify prognosis subtype of PDAC patients, and eventually to predict subtypes or prognosis for each patient. In this study, we generated Whole Exome Sequencing (WES) and exome capture RNA sequencing data of 450 tumor and matched normal samples from 150 PDAC patients. Our data may be useful for understanding genomic and transcriptomic features, prognosis prediction, and precision medicine for PDAC.

  Study phs002347

• Association Between Telomere Length and Falciparum Malaria Endemicity in Sub-Saharan Africans

  The goal of this study was to identify the genetic and environmental drivers of telomere length variation in an ethnically diverse African cohort. It comprises 1,818 participants from Cameroon, Tanzania, Ethiopia, and Botswana. For each participant, leukocyte telomere length was measured using the Southern blotting of the terminal restriction fragment methodology. 1,758 of the individuals with phenotype data also had genetic data, and these individuals were subjected to a genome-wide association study which accounted for age, sex, and genetic relatedness. Individuals were genotyped on one of two genotyping arrays (Illumina Infinium Omni5 array or Illumina H3Africa consortium array). Genetic datasets were merged, and missing genotypes were imputed for a final genetic dataset of 11,001,107 genetic variants. Correlations between telomere length and a variety of environmental factors, including malaria endemicity, were also examined in this study.

  Study phs003567

• Spatial heterogeneity in medulloblastoma

  Spatial heterogeneity of transcriptional and genetic markers between physically isolated biopsies of a single tumor poses major barriers to the identification of biomarkers and the development of targeted therapies that will be effective against the entire tumor. We analyzed the spatial heterogeneity of multiregional biopsies from 35 patients, using a combination of transcriptomic and genomic profiles. Medulloblastomas (MBs), but not high-grade gliomas (HGGs), demonstrated spatially homogeneous transcriptomes, which allowed for accurate subgrouping of tumors from a single biopsy. Conversely, somatic mutations that affect genes suitable for targeted therapeutics demonstrated high levels of spatial heterogeneity in MB, malignant glioma, and renal cell carcinoma (RCC). Actionable targets found in a single MB biopsy were seldom clonal across the entire tumor,which brings the efficacy of monotherapies against a single target into question. Clinical trials of targeted therapies for MB should first ensure the spatially ubiquitous nature of the target mutation.

  Study EGAS00001001014

• Genetic landscape of inherited retinal dystrophies affected cases in Spain

  Inherited retinal diseases (IRDs), defined by dysfunction or progressive loss of photoreceptors, are disorders characterized by elevated heterogeneity, both at the clinical and genetic levels. Our main goal was to address the genetic landscape of IRD in a Spanish cohort of patients. A retrospective hospital-based cross-sectional study was carried out on IRD affected individuals, referred for genetic testing from all the Spanish autonomous communities. Clinical, demographic and familiar data were collected from each patient, including family pedigree, age of appearance of visual symptoms, presence of any systemic findings and geographical origin. Genetic studies were performed to all families with available DNA using different molecular techniques. Our study provides the general landscape for IRD in Spain and our results have important implications for genetic diagnosis, counselling and new therapeutic strategies to both the Spanish population and other related populations.

  Study EGAS00001005104

• UCSF Sebaceous Carcinoma DAC for review of sequence data release from manuscript in Nature Communications, based in the UCSF Departments of Dermatology and Pathology

  Dac EGAC00001000850

• Molecular_diagnosis_of_albinism

  Albinism is genetically heterogeneous rare genetic condition affecting 1:17000 in the Western world (but more frequent in Africa) whose main feature is a profound visual impairment, characterised by foveal hypoplasia, abnormal chiasmatic connections, nystagmus and photofobia. All these features result in severly altered visual acuity (<0,1), absent depth perception and poor night vision. People with albinism are primarily visually handicapped. In addition, for some types of albinism, the visual phenotype can be presented with partial or total hypopigmentation, hence resulting in a secondary phenotype which can lead to skin cancer if skin is not adequately protected. Recently a new syndrome has been described, FHONDA, with the same visual abnormalities of albinism but without pigment alteration. The traditional classification differentiates Oculoculatenous albinism (OCA), where hypopigmentation involves hair, skin and eyes versus Ocular Albinism (OA), where hypopigmentation only affects the eyes. These are non-sydrimic types of albinism. Some syndromic forms (Hermansky-Pudlak=HPS, Chediak-Higashi=CHS) affect cells beyond pigment cells, present in the lungs, immune system, platelets and intestines, resulting in more severe phenotypes that can be fatal. Mutations in at least 19 genes are assocaited with the corresponding types of albinism. Most hospitals will only diagnose the most frequent cases using traditional Sanger, MLPA approaches. Some will use CGH arrays. We aim to diagnose all cases of albinism through the Albinochip proposal, which combines a Sequenom first step of known mutations combined with subsequent NGS approaches. In some cases we fail to find a second mutation, these are good candidates for further full exome analyses. 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/

  Study EGAS00001002068

• A benchmarking resource for NGS testing of cancer predisposition genes

  A benchmarking resource of 639 individuals, to assess the analytical sensitivity of cancer predisposition gene (CPG) testing.The dataset includes sequencing data generated using the TruSight Cancer Panel (TSCP) a targeted NGS assay for analysis of CPGs and orthogonally generated data supporting at least one pathogenic variant in a CPG for a total of 645 pathogenic CPG variants.The set of pathogenic CPG variants includes strong representation of some of the most challenging types of pathogenic variants, with 339 indels, including 16 complex indels and 24 insertions or deletions with length greater than 5bp, and 74 exon CNVs, including 23 single exon CNVs. There are 502 pathogenic variants in BRCA1 or BRCA2, making this an important first-line validation dataset for laboratories performing NGS testing of BRCA1 and BRCA2.

  Study EGAS00001002993

• A reference map of potential determinants for the human serum metabolome

  The collection of metabolites circulating in the human blood, termed the serum metabolome, contains a plethora of biomarkers and causative agents. Although the origin of specific compounds is known, we have a poor understanding of the key determinants of most metabolites. Here, we measured the levels of 1251 circulating metabolites in serum samples from a healthy human cohort of 491 individuals, and devised machine learning algorithms to predict their levels in held-out subjects based on a comprehensive profile consisting of host genetics, gut microbiome, clinical parameters, diet, lifestyle, anthropometric measurements and medication data. Notably, we obtained statistically significant predictions for over 76% of the profiled metabolites. Despite using the strict out-of-sample prediction metric, which is a lower bound for the explained variance, diet and microbiome each explained hundreds of metabolites, with over 50% of the variance explained in some metabolites. We further validated the robustness of the microbiome related associations by showing a high replication rate in two geographically independent cohorts that were not available to us when developing the algorithms. We also demonstrate that some of these interactions are causal, as some metabolites we predicted to be positively associated with bread increased in level following a randomized clinical trial of bread intervention. Microbiome-explained metabolites were enriched with unnamed metabolites, and we devised an algorithm that accurately predicts their biological pathway, finding that they mainly include food components, aromatic amino acids and secondary bile acid derivatives. Overall, our results unravel potential determinants of over 800 metabolites, paving the way towards mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating circulating metabolite levels.

  Study EGAS00001004512

• National Eye Institute (NEI) Age-Related Eye Disease Study 2 (AREDS2)

  The Age-Related Eye Disease Study 2 (AREDS2) was a multi-center, randomized Phase III clinical trial designed to assess the effects of oral supplementation of high doses of lutein, zeaxanthin, and omega-3 fatty acids (docosahexaenoic acid [DHA] and eicosapentaenoic acid [EPA]) in reducing the risk of progression to late age-related macular degeneration (AMD), progression to cataract surgery, and/or progression to moderate vision loss in high-risk participants. The effect of the study supplements on cardiovascular outcomes and cognitive function were also examined. Other study goals included evaluation of eliminating beta-carotene and/or reducing zinc in the original AREDS formulation on the progression and development of late AMD. AREDS2 sought to validate the AREDS AMD scale developed from the photographic data obtained from AREDS, (Study Accession: phs000001).Eighty-two clinical sites across the United States enrolled 4,203 participants aged 50 to 85 (mean age 74 years) between October 2006 and September 2008. Enrollment was restricted to people at high risk of progression to late AMD with either bilateral large drusen or large drusen in 1 eye and late AMD in the fellow eye. Follow-up assessments in the clinic occurred on an annual basis for an average of 5 years, with telephone calls every six months during each year. Blood or saliva samples were also collected from 2,000+ AREDS2 participants for genetic research. Of these, samples from 1,800+ AREDS2 participants were included in the International Age-Related Macular Degeneration Genomics Consortium - Exome Chip Experiment, and have exome chip data available in the dbGaP (Study Accession: phs001039). In addition, samples from 1300+ AREDS2 participants were included in the International Age-Related Macular Degeneration Genomics Consortium - Whole Genome Sequencing Study in the dbGaP (Study Accession: TBD). Of 1363 AREDS2 participants with whole genome sequencing, 488 previously participated in AREDS.Please see "The Age-Related Eye Disease Study 2 (AREDS2) Research Group" document for a full list of AREDS2 study contributors.

  Study phs002015

• DAC for EGA study: Multi-omic analyses from a randomized phase II study of epigenetic priming followed by nivolumab in previously treated metastatic non-small cell lung cancer

  This is the Data Access Committee for the EGA study: Multi-omic analyses from a randomized phase II study of epigenetic priming followed by nivolumab in previously treated metastatic non-small cell lung cancer (temp ID 800).

  Dac EGAC50000000563

• Saliva Microbiota of Finnish children from the PANIC study

  Saliva Microbiota of Finnish children aged between 6-8 yrs in the PANIC study. Baseline data. Studied for various lifestyle conditions and oral diseases (without caries/with caries).

  Study EGAS50000000708

• Sequencing dataset for the Predictive Endocrine ResistanCe Index (PERCI) in Breast Cancer cases

  Sequencing dataset for the Predictive Endocrine ResistanCe Index (PERCI) in Breast Cancer cases of the WSG-ADAPT trial (NCT01779206). The Oncomine Comprehensive v3 assay (ThermoFisher) and a customized amplicon-based NGS-Panel (DERv2) was performed.

  Dataset EGAD50000001595

• Dataset Rdata segmentations

  This data set contains an .Rdata file for all the processed segmentation profiles from 81 lpWGS samples included used in downstream analyses from Github repository Evo_history_CACRC. Lastly, there is an .Rdata object with 50 segmentations for 50 total samples from 25 sporadic SNP adenomas used in the comparison with colitis samples.

  Dataset EGAD00010001586

• S_CORT_Stratification_in_COloRecTal_cancer_

  Colorectal cancer samples will be submitted for Illumina sequencing using a custom capture of 116 genes implicated in colorectal tumourigenesis. Driver mutations will be detected and ultimately correlated with phenotypic data.

  Study EGAS00001001521

• Organoid_Derivation_Pilot__RNAseq

  Generation of normal and cancer organoids for sequencing as part of the WTSI-CRUK international collaboration with NCI (in HCMI) to generate the next generation of cancer cell lines.

  Study EGAS00001002223

• Patient-derived conditionally reprogrammed cells (CRCs) were established and characterized to assess their biological properties and to apply these to test the efficacies of drugs.

  RNA seq data was used for the characterization and profiling of the created patient-derived cells and in vivo tissue.

  Study EGAS00001001702

• Organoid_Derivation_Project__WGS

  Generation of normal and cancer organoids for sequencing as part of the WTSI-CRUK international collaboration with NCI (in HCMI) to generate the next generation of cancer cell lines

  Study EGAS00001002222

• Colon adenomas and adenocarcinomas and matched mucosae

  Whole exome sequencing in sporadic colorectal cancers (CRC) and advanced adenomas (Ad-As), and their paired healthy mucosa, for a deeper understanding of the biology of this cancer.

  Study EGAS00001007255

• RNA-seq of CD34+ HSPCs from LRMDS patients

  To profile transcriptional alterations of HSPCs in LR-MDS patients, 7AAD−CD45+Lin-CD235a−CD34+ cells were isolated from healthy donors and LR-MDS patients for RNA sequencing.

  Study EGAS00001008182