Bioinformatic Analysis of Whole Exome Data

dc.contributor.authorMd Momin Ali
dc.contributor.supervisorKhetarpal, Preeti
dc.date.accessioned2018-08-31T04:13:44Z
dc.date.accessioned2024-08-14T07:04:06Z
dc.date.available2018-08-31T04:13:44Z
dc.date.available2024-08-14T07:04:06Z
dc.date.issued2018
dc.description.abstractWhole Exome Sequencing (WES) is a capture-based method developed to sequence exome and to identify variants in the coding region of genes that affect protein function. Understanding the exomes of individuals at single base resolution allows the identification of pathogenic variants responsible for causing genetic disease. In this paper we mentioned all the object of the project steps and bioinformatic computational tools involved step by step. The objective of the study was to find all the disease causing heterozygous variants in the proband from the WES data. Using in silico tools SIFT, PolyPhen and ANNOVAR. All the annotated non-synonymous SNPs was arranged and filtered according to the pathogenicity of variants. All the variants were narrowed down to five matching variants. associated with clinical phenotype of the proband. As a conclusion Bioinformatic analysis of WES data proved to be a good tool for finding disease causing variants. Majority of the tools used in the analysis are generally linux based with poor user interface which makes it a challenging experience for a non-computational individual. Future of this field is dependent on software developers, so that more people can understand and help in the progress.en_US
dc.identifier.accessionnoT00670
dc.identifier.citationMd Momin Ali (2018) Bioinformatic Analysis of Whole Exome Dataen_US
dc.identifier.urihttps://kr.cup.edu.in/handle/32116/1891
dc.language.isoen_USen_US
dc.publisherCentral University of Punjaben_US
dc.subjectWhole Exome Sequencingen_US
dc.subjectNext Generation Sequencingen_US
dc.subjectin silicoen_US
dc.subjectSIFTen_US
dc.subjectPolyPhenen_US
dc.subjectANNOVARen_US
dc.titleBioinformatic Analysis of Whole Exome Dataen_US
dc.typeMaster Dissertationen_US

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