WHOLE GENOME SEQUENCING DATA ANALYSIS APPROACHES IN MODERN RESEARCH
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Abstract
Whole genome sequencing (WGS) is a powerful tool for studying genetic variation and the underlying mechanisms of disease. Over the past decade, advances in sequencing technology have enabled researchers to rapidly and cheaply generate large amounts of genomic data. This has led to a sharp increase in the application of WGS to modern research, ranging from medical genetics to evolutionary biology. In this review, we discuss current approaches to WGS data analysis, focusing on the most popular methods and the challenges associated with them. We discuss the different types of data generated by WGS, the various analytical steps involved in analyzing the data, and the strategies for interpreting the results. We also discuss the potential applications of WGS data analysis in research, such as population genetics and precision medicine. Finally, we provide an outlook on future developments in WGS data analysis.
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