Please use this identifier to cite or link to this item: https://dspace.ctu.edu.vn/jspui/handle/123456789/24622
Title: A computational framework to analyze human genomes
Authors: Le, Sy Vinh
Keywords: Human genome sequencing
Bioinformatics
Human genome analyses
Single nucleotide variants
Structural variants
Variant annotation
Issue Date: 2019
Series/Report no.: Journal of Computer Science and Cybernetics;Vol.35(02) .- P.105–118
Abstract: The advent of genomic technologies has led to the current genomic era. Large-scale human genome projects have resulted in a huge amount of genomic data. Analyzing human genomes is a challenging task including a number of key steps from short read alignment, variant calling, and variant annotating. In this paper, the state-of-the-art computational methods and databases for each step will be analyzed to suggest a practical and efficient guideline for whole human genome analyses. This paper also discusses frameworks to combine variants from various genome analysis pipelines to obtain reliable variants. Finally, we will address advantages as well as discordances of widely-used variant annotation methods to evaluate the clinical significance of variants. The review will empower bioinformaticians to efficiently perform human genome analyses, and more importantly, help genetic consultants understand and properly interpret mutations for clinical purposes.
URI: http://dspace.ctu.edu.vn/jspui/handle/123456789/24622
ISSN: 1813-9663
Appears in Collections:Tin học và Điều khiển học (Journal of Computer Science and Cybernetics)

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