gwaRs

gwaRs visualizes genome-wide association study (GWAS) results by generating SNP-density, quantile-quantile (Q-Q), Manhattan and principal component analysis (PCA) plots to support interpretation of genetic association signals and population structure.

Key Features:

• SNP-Density Plot: Displays the distribution and density of single nucleotide polymorphisms (SNPs) across the genome.
• Quantile-Quantile (Q-Q) Plot: Compares observed versus expected p-values to detect deviations from the null distribution and potential population stratification or systematic bias.
• Manhattan Plot: Visualizes genome-wide significance of associations, highlighting regions with statistically significant SNPs for candidate gene identification associated with traits or diseases.
• Principal Component Analysis (PCA) Plot: Projects genetic variation into principal components to facilitate exploration of population structure.

Scientific Applications:

• Exploratory GWAS analysis: Facilitates visual inspection of association patterns across the genome for hypothesis generation.
• Hypothesis generation: Supports identification of genomic regions and SNPs for downstream investigation.
• Validation studies: Aids visual comparison of association signals during replication and validation efforts.
• Population structure assessment: Enables evaluation of genetic ancestry and stratification effects using PCA and Q-Q diagnostics.
• Interpretation of genetic basis of traits and diseases: Assists in pinpointing candidate loci and assessing their genome-wide context.

Methodology:

Generates SNP-density, quantile-quantile (Q-Q), Manhattan and principal component analysis (PCA) plots from GWAS summary data.