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• MGP Panel: a comprehensive targeted genomics panel for molecular profiling of multiple myeloma patients

  We designed a comprehensive multiple myeloma (MM) targeted sequencing panel to identify common genomic abnormalities in a single assay and validated it against known standards. The panel comprised 228 genes/exons for mutations, 6 regions for translocations, and 56 regions for copy number abnormalities (CNAs). Toward panel validation, targeted sequencing was conducted on 233 patient samples and further validated using clinical fluorescence in situ hybridization (FISH) (translocations), multiplex ligation probe analysis (MLPA) (CNAs), whole genome sequencing (WGS) (CNAs, mutations, translocations) or droplet digital PCR (ddPCR) of known standards (mutations). Canonical IgH translocations were detected in 43.2% of patients by sequencing, and aligned with FISH except for one patient. CNAs determined by sequencing and MLPA for 22 regions were comparable in 103 samples and concordance between platforms was R2=0.969. VAFs for 74 mutations were compared between sequencing and ddPCR with concordance of R2=0.9849. In summary, we have developed a targeted sequencing panel that is as robust or superior to FISH and WGS. This molecular panel is cost effective, comprehensive, clinically actionable and can be routinely deployed to assist risk stratification at diagnosis or post-treatment to guide sequencing of therapies.

  Study EGAS00001006222

• Demographic History and Local Adaptation in Asian Population

  Due to harboring high genetic and cultural diversity of populations, Central Asia is one key area for understanding the recent evolutionary history of humans. In this project, our aims include: (1) to resequence genome sequences with high sequencing depth for Central Asian populations Balti; (2) to discern the genomic diversity, populations structure and demographic history of Balti; (3) to investigate the genetic mechanisms for local adaptations in Balti.

  Study JGAS000238

• Characterization of a novel MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line WXS derived

  The lack of a well-characterized model system for many subtypes of leukemia hinders the development of targeted therapy and immunotherapy. A novel in-house-made pediatric MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line was characterized. This cell line is highly presentative for the major clone of the original material and thus a valuable resource to examine novel therapeutic for MEF2D fused patients.

  Study EGAS00001006801

• Whole-genome sequencing data of human hematopoietic stem and progenitor cells in post-transplant clonal hematopoiesis

  This dataset contains BAM files of whole-genome sequencing data of single human HSPCs after colony expansion, for three individuals who harbor a DNMT3A mutant clonal hematopoiesis clone in their blood system after hematopoietic cell transplantation. 29 samples are present in this dataset; 10 samples for LTHIT005, 10 samples for LTHIT131, and 9 samples for LTHIT069. In the sample name, samples are annotated for being DNMT3A wildtype (wt) or mutant (mut), except for LTHIT069 (wt samples: F13, H4, K2, L16, N12, mut samples: C8, E10, L9, N5). Whole-genome sequencing was performed after standard Illumina WGS library preparation and sequenced on a Novaseq 6000 using 150 bp paired-end sequencing. The sequencing depth is 15x genome coverage, or 50Gbases per sample.

  Dataset EGAD50000001347

• Fastq data for smRNA-Seq assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for smRNA-Seq assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001401

• Multiplexing cortical brain organoids for the longitudinal dissection of developmental traits at single cell resolution

  Dissecting human neurobiology at high resolution and with mechanistic precision requires a major leap in scalability, given the need for experimental designs to multiple individuals and, prospectively, population cohorts. To lay the foundation for this, we have implemented and benchmarked complementary strategies to multiplex brain organoids by pooling cells from different pluripotent stem cell lines (PSC) either during organoid generation (mosaic models) or before single cell-RNAseq library preparation (downstream multiplexing). We have also developed a new computational method, SCanSNP, and a consensus call to deconvolve cell identities, overcoming current criticalities in doublets prediction and low quality cells identification. We validated both multiplexing methods for charting neurodevelopmental trajectories at high resolution, thus linking specificity to genetic variation. Finally, we modelled their scalability across different multiplexing combinations and showed that mosaic organoids represent an enabling method for high-throughput settings. Together, this multiplexing suite of experimental and computational methods provides a highly scalable resource for disease modelling.

  Study EGAS50000000698

• Data Use Ontology (DUO) at EGA

  For those of you that follow the updates of GA4GH you will have seen the unanimous approval of the steering committee for DUO to be included in its suite of technical standards for the sharing of genomic and health related data. DUO has three main features: Each term has been generated by the community and includes a human readable definition that can be expanded where necessary. It is a machine-readable file that encodes how that data can be used and how a researcher intends to use the data. Can be implemented alongside an advanced search algorithm which would allow authenticated users to query and gain access to datasets pertaining to their research. e.g., an industry researcher working on cancer could potentially be matched to any dataset that is allowed for commercial use and for cancer research and offered the opportunity to fetch them automatically. So, what does this mean for EGA? EGA as a driver project has adopted this standard and will be utilizing it for two main purposes in the first instance. i) It will allow EGA users to instantly identify what terms they will need to agree to as part of any Data Access Agreements. This will save valuable time for both applicants and Data Access Committees alike - as you will be able to see if you are likely to be able to access the data based on your research intentions and working background. ii) In the future it will allow users to be able to search for data based on Data Use Ontology terms e.g., you could search for all data that can be used for General Research Use (GRU). As EGA moves forwards submitters will be asked to align their data access policies with DUO so that their dataset(s) can be tagged appropriately on our web pages. If you would like to add DUO to any of your existing datasets, or to any future datasets, do please just let us know.

  Blog data-use-ontology

• Whole genome sequencing of patients with or at risk for HCC

  Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection.

  Study EGAS00001007249

• Circulating tumor cells for comprehensive and multiregional non-invasive genetic characterization of multiple myeloma (arrays set)

  Multiple myeloma (MM) patients undergo repetitive bone marrow (BM) aspirates for genetic characterization. Circulating tumor cells (CTCs) are detectable in peripheral blood of virtually all MM cases and are prognostic, but their applicability for non-invasive screening has been poorly investigated. Here, we used next-generation flow cytometry to isolate matched CTCs and BM tumor cells from 42 patients and compare their genetic profile. In 8 cases, tumor cells from extramedullary plasmacytomas were also sorted and whole-exome sequencing performed in the three spatially-distributed clones. Noteworthy, ≥84% mutations present in BM and extramedullary clones were detectable in CTCs. Concordance between BM tumor cells and CTCs was high for chromosome arm-level copy-number alterations (≥94%) though not for translocations (43%). All high-risk genetic abnormalities except one t(4;14) were detected in CTCs whenever present in BM tumor cells. Altogether, these results support CTCs for non-invasive risk-stratification of MM patients based on their numbers and genetic profile.

  Study EGAS00001004314

• Long-read Nanopore and Ion Torrent sequencing data for BRCA1/2 variant detection

  This dataset contains long-read sequencing data generated using Oxford Nanopore Technologies for the analysis of BRCA1 and BRCA2 variants in individuals referred for hereditary breast cancer genetic testing. The study includes samples previously analyzed using Ion Torrent sequencing, enabling comparison between short-read and long-read sequencing approaches.

  Study EGAS50000001783

• Cambridge_INTERVAL_SomaLogic_pQTLs

  This dataset contains four data files relating to the Cambridge Interval SomaLogic pQTL study to go with the corresponding genetic data: (1) Genome-wide pQTL summary associations for each analyte. (2) Mapping table for the genetic variants analysed - containing rsID, position and allele information. (3) Normalised quantitative readouts for each analyte, along with covariates used for the pQTL analysis. (4) Table of SOMAmer analytes mapped to their protein targets. Please see the readme file in the dataset for more information.

  Dataset EGAD00001004080

• June 2016 data update for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  June 2016 data update (bam/fastq for CEMT0062, CEMT0068, CEMT0072, CEMT0086, CEMT0087 ChIP-Seq and RNA-Seq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001002239

• NHLBI TOPMed - NHGRI CCDG: Early-onset Atrial Fibrillation in the CATHeterization GENetics (CATHGEN) Cohort

  The CATHeterization GENetics (CATHGEN) biorepository collected biospecimens and clinical data on individuals age ≥18 undergoing cardiac catheterization for concern of ischemic heart disease at a single center (Duke University Medical Center) from 2000-2010; a total of N=9334 individuals were collected. Samples were matched at the individual level to clinical data collected at the time of catheterization and stored in the Duke Databank for Cardiovascular Diseases (DDCD). Clinical data included subject demographics, cardiometabolic risk factors, cardiac history including symptoms, age-of-onset of cardiovascular diseases, coronary anatomy and cardiac function at catheterization, laboratory data, and yearly follow-up for hospitalizations, vital status, medication use and lifestyle factors. AF cases were defined as individuals who had ever had AF based on any ECG available at Duke University or ICD-9 code for AF used for inpatient or outpatient billing.

  Study phs001600

• Sex Chromosome Aneuploidy Effects on Human Gene Expression

  Sex chromosome aneuploidy (SCA) syndromes are defined by the presence of a sex chromosome complement other than the typical XX for females and XY for males. SCAs are collectively common and increase risks for diverse immune, metabolic, and neuropsychiatric illnesses. Understanding genome-wide transcriptomic changes in SCAs is critical for clarifying the biological underpinnings of their clinical phenotypes. Assessments of sex chromosome dosage (SCD) effects on gene expression in humans have often been confined to the use of a few SCA subtypes (e.g., XO or XXY) - precluding analysis of the same SCD change in different contexts. Our study used RNA-seq data from lymphoblastoid cell lines in 197 individuals representing diverse SCA karyotypes (49 XX, 24 XXX, 39 XY, 39 XXY, 23 XXYY, 23 XYY) to assess expression changes for 25,075 genes in multiple pairwise SCD group comparisons. The paper reporting our findings has been cited below.

  Study phs003278

• A Phase 2 Study of Lamivudine in Patients with p53 Mutant Metastatic Colorectal Cancer

  This was an open-label, single-arm Phase II study of lamivudine in patients who had progressed on systemic therapy for advanced colorectal cancer with TP53 mutations. The phase II study had a two-stage design, with a target accrual of 20 evaluable patients for the first stage and a total of 32 patients for the whole study. The first 9 patients were treated with lamivudine at 150 mg PO bid continuously for 28-day cycles. Subsequent patients (10-32) received a higher dose of 600 mg PO bid continuously for 28-day cycles. Tumor assessments were performed every 8 weeks until documented disease progression by Response Evaluation Criteria in Solid Tumors (RECIST) or drug intolerance. Whole genome sequencing (WGS) and total RNA-seq were performed on pre- and post- treatment biopsies on this trial.

  Study phs002833

• The Prostate, Lung, Colon, Ovary Screening Trial (PLCO)

  The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial is a large population-based randomized trial designed and sponsored by the National Cancer Institute (NCI) to determine the effects of screening on cancer-related mortality and secondary endpoints in over 150,000 men and women aged 55 to 74. The screening component of the trial was completed in 2006. However, participants have been under follow-up for cancer incidence and mortality since that time. In addition, PLCO included a large biological sample biorepository which has served as a unique resource for cancer research, particularly for etiologic and early-marker studies. As part of these efforts, PLCO has been used for a large number of genome-wide association and exome sequencing studies for different types of cancer. Recently, a blood DNA methylation analysis was conducted in annexes case-controls study of breast cancer.

  Study phs001286

• From matrimonial practices to genetic diversity in Southeast Asian populations: the signature of the matrilineal puzzle

  This project aims at revisiting the "matrilineal puzzle" from a population genetics' point of view. The dataset consists of 719 individuals from 12 populations sampled in continental Southeast Asia and genotyped at 598764 loci. This dataset can only be accessed and used for non-commercial research purposes with a finality complying with the informed consent provided by donors. For accessing the data, please provide: 1. An explicit title for the project you wish to use the data for. 2. A detailed institutional affiliation of all recipients and users of the data. 3. A summary (500 words) of the research project, with emphasis on its scientific and societal finality, and predicted outputs. If access is granted by the DAC, data cannot be shared with a third party not initially involved in the project, without the third party officially applying for accessing the data.

  Study EGAS00001003727

• NGS sequencing for genes from the patients of OU Genome Project

  This research aims to identify disease related HLA alleles by genome analysis for cardiac sarcoidosis.

  Study JGAS000568

• WTCCC case-control study for Tuberculosis

  WTCCC genome-wide case-control association study for Tuberculosis (TB) using the African samples as controls.

  Study EGAS00000000027

• cfDNA dataset with whole genome sequencing for cfDNA cohort

  Cell free DNA sequencing data for 13samples with whole genome sequencing across multiple cancer types for cfDNA cohort

  Dataset EGAD50000000666

• Transcriptomics for the ALTTO study

  Transcriptomics for the ALTTO study by high-throughput sequencing. 386 HER2+ breast cancers treated by trastuzumab were sequenced. Two fastq files are given for each sample.

  Dataset EGAD50000000746

• Microarray_cases

  CASE SAMPLES USING Affymetrix SNP6.0 technology (Thermo Fisher Scientific company): OncoScan FFPE Assay Kit was used for FFPE tissue samples (designed for degraded DNA) and the Cytoscan HD Array Kit was used for the fresh-frozen tissues

  Dataset EGAD00010002034

• RNASeq files for Klco PanAML data

  RNASeq files for paper titled "Proposal of a new genomic framework for categorization of pediatric acute myeloid leukemia associated with prognosis"

  Dataset EGAD00001011294

• WGS files for Klco PanAML data

  WGS files for paper titled "Proposal of a new genomic framework for categorization of pediatric acute myeloid leukemia associated with prognosis"

  Dataset EGAD00001011295

• WXS files for Klco PanAML data

  WXS files for paper titled "Proposal of a new genomic framework for categorization of pediatric acute myeloid leukemia associated with prognosis"

  Dataset EGAD00001011296