This course provides a comprehensive introduction to the core analytical pipeline for whole‑genome resequencing data. The first chapter covers the principles of resequencing (in contrast to de novo sequencing) and its application scenarios. The second chapter explains the BWA aligner (backtrack, SW, and MEM algorithms), detailed SAM/BAM format specifications (flag, CIGAR, optional fields), and the samtools toolkit (sorting, indexing, statistics). The third chapter focuses on the GATK Best Practices workflow: marking PCR/Optical duplicates, generating gVCFs with HaplotypeCaller, multi‑sample merging (GenomicsDBImport/CombineGVCFs), and joint genotyping, with emphasis on variant quality‑control strategies, including VQSR (requiring known variant sets) and hard filtering (based on thresholds such as QUAL and DP), along with detailed VCF field interpretation (GT, AD, DP, AC, AF, etc.). The fourth chapter introduces snpEff annotation, covering variant type distribution (SNP/MNP/INS/DEL), impact severity (HIGH/MODERATE/LOW/MODIFIER), functional classes (missense/nonsense/silent), and transition/transversion ratios. The fifth chapter addresses structural variant (SV) detection principles (Read‑Pair, Split‑Read, Read‑Depth, and Assembly strategies), compares common tools such as lumpy, manta, and gridss, and emphasizes the necessity of stringent filtering of SV calls. The course integrates theory with practice, providing systematic guidance for large‑scale resequencing data mining.