CPMFD: An algorithm for Classification of Point Mutations together with Frameshift Determination in related mRNA sequences

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Abstract Mutations are responsible for the genetic origin of various diseases. Existing techniques for mutation identification often fails to detect the full spectrum of mutations in complex genomes hindering progress in diagnosis, treatment and prevention of diseases. Here we propose an algorithm to identify the location and type of mutation occurring in a mutated string with respect to a reference mRNA sequence. In addition to identifying insertion and deletion, by constructing suitable rational combinations of the prime numbers, our algorithm is able to classify point mutations in a novel way by distinguishing missense mutation from silent mutation. Moreover, the method allows to locate regions in the sequence undergoing frameshift. This algorithm turns out to be efficient when applied on simulated dataset. Application of this framework to two haplotypes of the Plasmodium falciparum datasets exhibit different mutation profile to develop similar chloroquine resistance. We investigate the β-globin genes found in pygmy and common chimpanzee to identify mutations of all sort distinguishing the two species. Additionally, in Alzheimer datasets, our method meticulously identifies true variations in the related genes.
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CPMFD: An algorithm for Classification of Point Mutations together with Frameshift Determination in related mRNA sequences | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article CPMFD: An algorithm for Classification of Point Mutations together with Frameshift Determination in related mRNA sequences Probir Mondal, Pratyay Banerjee, Krishnendu Basuli This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5920108/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Mutations are responsible for the genetic origin of various diseases. Existing techniques for mutation identification often fails to detect the full spectrum of mutations in complex genomes hindering progress in diagnosis, treatment and prevention of diseases. Here we propose an algorithm to identify the location and type of mutation occurring in a mutated string with respect to a reference mRNA sequence. In addition to identifying insertion and deletion, by constructing suitable rational combinations of the prime numbers, our algorithm is able to classify point mutations in a novel way by distinguishing missense mutation from silent mutation. Moreover, the method allows to locate regions in the sequence undergoing frameshift. This algorithm turns out to be efficient when applied on simulated dataset. Application of this framework to two haplotypes of the Plasmodium falciparum datasets exhibit different mutation profile to develop similar chloroquine resistance. We investigate the β-globin genes found in pygmy and common chimpanzee to identify mutations of all sort distinguishing the two species. Additionally, in Alzheimer datasets, our method meticulously identifies true variations in the related genes. Bioinformatics Molecular Biology Mutation Identification Frameshift prime number Amino acid mRNA sequence Full Text Additional Declarations The authors declare no competing interests. Supplementary Files SupplementaryFileCPMFD.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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