{"title":"A Model for Optimal Assignment of Non-Uniquely Mapped NGS Reads in DNA Regions of Duplications or Deletions","authors":"Rituparna Sinha, Rajat K. Pal, R. K. De","doi":"10.1109/CONIT55038.2022.9848131","DOIUrl":null,"url":null,"abstract":"Massively parallel sequencers have enabled genome sequences to be available at a very low cost and price, which opened huge scope on analyzing human genome sequences from different perspectives, thereby the association of diseases with genetic alterations gets further enlightened. However, the sequencing process and alignment of NGS technology based short reads suffer from various sequencing biases which needs to be addressed. In this work, the mappability bias occurring with respect to repeat rich regions of the DNA have been addressed in a novel approach. A model has been designed which considers all non-uniquely mapped reads and performs a pipeline of computations to allocate the reads to an optimal location, due to which the precise detection of breakpoints in the region of duplications and deletions are obtained. In addition, the application of this model for mappability bias correction, prior to the detection of structurally altered regions of the genome, leads to a better sensitivity value.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Intelligent Technologies (CONIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONIT55038.2022.9848131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Massively parallel sequencers have enabled genome sequences to be available at a very low cost and price, which opened huge scope on analyzing human genome sequences from different perspectives, thereby the association of diseases with genetic alterations gets further enlightened. However, the sequencing process and alignment of NGS technology based short reads suffer from various sequencing biases which needs to be addressed. In this work, the mappability bias occurring with respect to repeat rich regions of the DNA have been addressed in a novel approach. A model has been designed which considers all non-uniquely mapped reads and performs a pipeline of computations to allocate the reads to an optimal location, due to which the precise detection of breakpoints in the region of duplications and deletions are obtained. In addition, the application of this model for mappability bias correction, prior to the detection of structurally altered regions of the genome, leads to a better sensitivity value.