Abstract
High-throughput sequencing (HTS) has revolutionized genomics by enabling the rapid generation of large-scale sequencing data. However, the analysis and interpretation of HTS data require advanced bioinformatics tools to handle the vast amounts of data produced. This article reviews the latest bioinformatics tools used for HTS data analysis, including tools for data preprocessing, alignment, variant calling, annotation, and visualization. We also discuss the challenges and future directions in HTS data analysis, including the integration of multi-omics data and the application of machine learning in data interpretation.
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