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Title:          IgIDivA: immunoglobulin intraclonal diversification analysis
Subject:        AcademicSubjects/SCI01060, DOI: 10.1093/bib/bbac349, Briefings in Bioinformatics, 23(5), 5, 8 3 2022. Abstract: Intraclonal diversification (ID) within the immunoglobulin (IG) genes expressed by B cell clones arises due to ongoing somatic hypermutation (SHM) in a context of continuous interactions with antigen(s). Defining the nature and order of appearance of SHMs in the IG genes can assist in improved understanding of the ID process, shedding light into the ontogeny and evolution of B cell clones in health and disease. Such endeavor is empowered thanks to the introduction of high-throughput sequencing in the study of IG gene repertoires. However, few existing tools allow the identification, quantification and characterization of SHMs related to ID, all of which have limitations in their analysis, highlighting the need for developing a purpose-built tool for the comprehensive analysis of the ID process. In this work, we present the immunoglobulin intraclonal diversification analysis (IgIDivA) tool, a novel methodology for the in-depth qualitative and quantitative analysis of the ID process from high-throughput sequencing data. IgIDivA identifies and characterizes SHMs that occur within the variable domain of the rearranged IG genes and studies in detail the connections between identified SHMs, establishing mutational pathways. Moreover, it combines established and new graph-based metrics for the objective determination of ID level, combined with statistical analysis for the comparison of ID level features for different groups of samples. Of importance, IgIDivA also provides detailed visualizations of ID through the generation of purpose-built graph networks. Beyond the method design, IgIDivA has been also implemented as an R Shiny web application. IgIDivA is freely available at  
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    Subject: AcademicSubjects/SCI01060, DOI: 10.1093/bib/bbac349, Briefings in Bioinformatics, 23(5), 5, 8 3 2022. Abstract: Intraclonal diversification (ID) within the immunoglobulin (IG) genes expressed by B cell clones arises due to ongoing somatic hypermutation (SHM) in a context of continuous interactions with antigen(s). Defining the nature and order of appearance of SHMs in the IG genes can assist in improved understanding of the ID process, shedding light into the ontogeny and evolution of B cell clones in health and disease. Such endeavor is empowered thanks to the introduction of high-throughput sequencing in the study of IG gene repertoires. However, few existing tools allow the identification, quantification and characterization of SHMs related to ID, all of which have limitations in their analysis, highlighting the need for developing a purpose-built tool for the comprehensive analysis of the ID process. In this work, we present the immunoglobulin intraclonal diversification analysis (IgIDivA) tool, a novel methodology for the in-depth qualitative and quantitative analysis of the ID process from high-throughput sequencing data. IgIDivA identifies and characterizes SHMs that occur within the variable domain of the rearranged IG genes and studies in detail the connections between identified SHMs, establishing mutational pathways. Moreover, it combines established and new graph-based metrics for the objective determination of ID level, combined with statistical analysis for the comparison of ID level features for different groups of samples. Of importance, IgIDivA also provides detailed visualizations of ID through the generation of purpose-built graph networks. Beyond the method design, IgIDivA has been also implemented as an R Shiny web application. IgIDivA is freely available at  
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<dc:creator><rdf:Seq><rdf:li>Zaragoza-Infante  Laura</rdf:li><rdf:li>Junet  Valentin</rdf:li><rdf:li>Pechlivanis  Nikos</rdf:li><rdf:li>Fragkouli  Styliani-Christina</rdf:li><rdf:li>Amprachamian  Serovpe</rdf:li><rdf:li>Koletsa  Triantafyllia</rdf:li><rdf:li>Chatzidimitriou  Anastasia</rdf:li><rdf:li>Papaioannou  Maria</rdf:li><rdf:li>Stamatopoulos  Kostas</rdf:li><rdf:li>Agathangelidis  Andreas</rdf:li><rdf:li>Psomopoulos  Fotis</rdf:li></rdf:Seq></dc:creator>
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   Type: CRC32
  Checksum: 5268bcad83b7fa536dae2fb4ccb64fe4
   Type: MD5
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