Exploratory Population Genetic Analysis of Indian Populations Using PCA and F-statistics

This study presents an explorative population genetic analysis with focus on Indian populations using Principal Component Analysis (PCA) and F-statistic with the goal of investigating genetic structure and admixture patterns. Indian populations have been chosen for this study because they show high genetic diversity due to numerous factors including ancient migration, endogamy and linguistic variations. The analysis was made on genome-wide single nucleotide polymorphism (SNP) datasets from multiple Indian population groups together with individuals from Europe, Middle East and East Asia in order to properly assess historical gene flow between populations. After individual filtering, SNP filtering and linkage disequilibrium pruning, PCA was applied to visualize patterns of genetic clustering and population structure, while f3-statistics were employed to detect admixture signals. The results show gradients of genetic variation consistent with known admixture between Ancestral North Indian (ANI) and Ancestral South Indian (ASI) components, and it has also shown admixture signals that are statistically significant in several populations, supporting historical interactions between caste and regional groups. Finally this study highlights the relevance of population genetics in medical research, in particular in identifying genetic risk factors that are population-specific and understanding the development of complex diseases in Indian populations.