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      CovCopCan: An efficient tool to detect Copy Number Variation from amplicon sequencing data in inherited diseases and cancer

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          Abstract

          Molecular diagnosis is an essential step of patient care. An increasing number of Copy Number Variations (CNVs) have been identified that are involved in inherited and somatic diseases. However, there are few existing tools to identify them among amplicon sequencing data generated by Next Generation Sequencing (NGS). We present here a new tool, CovCopCan, that allows the rapid and easy detection of CNVs in inherited diseases, as well as somatic data of patients with cancer, even with a low ratio of cancer cells to healthy cells. This tool could be very useful for molecular geneticists to rapidly identify CNVs in an interactive and user-friendly way.

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          LOWESS: A Program for Smoothing Scatterplots by Robust Locally Weighted Regression

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            Continuous Inspection Schemes

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              p53 gene deletion predicts for poor survival and non-response to therapy with purine analogs in chronic B-cell leukemias.

              Conventional cytogenetic analysis in B-cell chronic lymphocytic leukemia (B-CLL) has been very difficult, and the prognostic significance of specific chromosome aberrations is under discussion. Recent improvements in fluorescence in situ hybridization (ISH) techniques have provided an alternative approach for the detection of chromosome aberrations. Here, an interphase cytogenetic study was performed to analyze the incidence and prognostic significance of a p53 gene deletion in B-CLL and related disorders. We studied mononuclear cells from 100 patients with chronic B-cell leukemias [B-CLL, 90 patients; B-prolymphocytic leukemia (B-PLL), 7; Waldenström's macroglobulinemia (WM), 3] by fluorescence ISH with a genomic p53 DNA probe. In a subset of patients, additional G-banding analysis and single strand conformation polymorphism (SSCP) analysis was performed. Seventeen of the 100 patients [17%; B-CLL, 11 of 90 (12%); WM, 1 of 3; B-PLL, 5 of 7] exhibited a monoallelic p53 gene deletion by ISH. G-banding analysis demonstrated abnormalities of chromosome 17 in 13 of these 17 patients, all leading to loss of band 17p13. SSCP analysis showed aberrant bands in 9 of 14 patients with a p53 gene deletion. None of 12 patients with a p53 gene deletion compared with 20 of 36 patients (56%) without a deletion responded to therapy with fludarabine or pentostatin (P < .001). The difference in survival probabilities from the time of diagnosis and from the start of treatment with purine analogs between the two groups was highly significant (P < .001). In multivariate analysis, p53 gene deletion was the strongest prognostic factor for survival. In conclusion, p53 gene deletion predicts for non-response to therapy with purine analogs and for poor survival in chronic B-cell leukemias.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draft
                Role: ConceptualizationRole: InvestigationRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: InvestigationRole: ValidationRole: Writing – review & editing
                Role: Data curation
                Role: Data curationRole: InvestigationRole: Validation
                Role: InvestigationRole: Validation
                Role: InvestigationRole: Validation
                Role: ConceptualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Project administrationRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                12 February 2020
                February 2020
                : 16
                : 2
                : e1007503
                Affiliations
                [1 ] CHU Limoges, UF de Bioinformatique, Limoges France
                [2 ] CHU Limoges, Service Hématologie Biologique, Limoges, France
                [3 ] Univ. Limoges, UMR CNRS 7276 CRIBL, Limoges, France
                [4 ] Univ. Limoges, MMNP, EA 6309, Limoges, France
                [5 ] CHU Limoges, Service Biochimie et Génétique Moléculaire, Limoges France
                [6 ] CHU Limoges, Service de Cytogénétique, Limoges, France
                [7 ] CHU Limoges, Service Anatomie Pathologie, Limoges, France
                [8 ] Univ. Limoges, EA CAPTur, Limoges, France
                [9 ] Univ. Limoges, UMR-7252X-LIM, Limoges, France
                University of Technology Sydney, AUSTRALIA
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-6509-1578
                Article
                PCOMPBIOL-D-19-00724
                10.1371/journal.pcbi.1007503
                7041855
                32049956
                36620146-f7be-422f-8f59-1f293f3c677d
                © 2020 Derouault et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 13 May 2019
                : 23 October 2019
                Page count
                Figures: 7, Tables: 3, Pages: 13
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Biology and Life Sciences
                Cell Biology
                Chromosome Biology
                Chromosomal Aberrations
                Chromosomal Deletions
                Biology and Life Sciences
                Cell Biology
                Chromosome Biology
                Chromosomal Aberrations
                Chromosomal Duplications
                Biology and Life Sciences
                Cell Biology
                Chromosome Biology
                Chromosomes
                Sex Chromosomes
                X Chromosomes
                Biology and Life Sciences
                Computational Biology
                Genome Complexity
                Copy Number Variation
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Complexity
                Copy Number Variation
                Computer and Information Sciences
                Data Visualization
                Biology and Life Sciences
                Genetics
                Mutation
                Deletion Mutation
                Physical Sciences
                Physics
                Nuclear Physics
                Nucleons
                Protons
                Computer and Information Sciences
                Data Visualization
                Infographics
                Charts
                Custom metadata
                vor-update-to-uncorrected-proof
                2020-02-25
                All relevant data are within the manuscript and its Supporting Information files.

                Quantitative & Systems biology
                Quantitative & Systems biology

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