Building upon basic analyses, this course delves into advanced modules of population genetics. The first chapter covers population demographic history inference, utilizing recombination to break genomic segments and infer effective population size changes over time via the distribution of recent co‑ancestry times. It compares MSMC2 (recommended for ≥20X depth, ≤4 samples per population) with SMC++ (for lower coverage), and emphasizes the need for mutation rate and generation time parameters. The second chapter addresses gene flow and introgression detection, including TreeMix (constructing maximum‑likelihood trees and inferring admixture events), f3‑statistics (testing whether a target population is a mixture of two sources, with negative values indicating significance), RFMix (detecting introgressed segments, requiring a genetic map), and D‑statistics (ABBA‑BABA test for four‑population interspecific gene flow, with |Z| > 3 as significant). The third chapter introduces runs of homozygosity (ROH) analysis, identifying consecutive homozygous SNP regions to assess inbreeding history—longer ROH indicate recent inbreeding, shorter ones reflect distant inbreeding, with links to complex disease studies. Finally, the course clarifies data suitability: qualitative comparisons (population stratification, gene flow, relative LD decay rates, Fst, and Pi trends) can use reduced‑representation data, while quantitative measurements (exact LD distances, precise Pi values, demographic modeling, ROH, and selective sweeps) require high‑quality whole‑genome resequencing data. This course provides essential technical guidance for deep interpretation of evolutionary history and selection signals.