- I have removed all scripts to redevelop and redeploy this repository as a one-stop, organized, updated, and simple-to-follow GWAS tutorial.
- It will contain the tips and tricks that I have accumulated throughout my experience in analyzing highly diverse African populations.
WATCH OUT FOR UPDATES!!!
- Model: Logistic (95% confidence interval), 1df Chi square allelic test (adjusted to assess the genomic control inflation factor - λ).
- Mode of inheritance (MOI): Additive, Recessive, HetHom, Allelic and Genotypic,
- Tools: PLINK1.9, SNPTEST, R
- Identification of individuals with discordant sex information.
- Identification of individuals with high missing values or outlying heterozygosities.
- Identification of duplicate or related individuals or individuals of divergent ancestry
- Tools: QCTOOL, PLINK1.9, R
- Identification of SNPs with excessive missing genotype
- Exclusion of rare SNPs (MAF < 1%)
- Identification of SNPs demonstrating significant deviation from HWE
- Identification of SNPs with significant differential genotyping call rate between cases and controls
- Tools: PLINK1.9, R
- Multidimensional scaling (eliminate population outliers)
- Principal component analysis with 10 axes of genetic variation (principal components)
- Fst and Haplotype based fine structure analysis
- Tools: Plink1.9, EIGENSOFT, fsStructure, ChromoPainter, GLOBETROTTER, R
- SHAPEIT2, Eagle2
- IMPUTE2, PBWT, MINIMACH
- Models: Logistic regression, Linear mixed models (LMM)
- Modes of inheritance: dominant, recessive, heterozygous, additive, allelic
- Tools: PLINK1.9, SNPTEST2, R
- Phasing with IMPUTE2 MCMC approach
- Imputation with IMPUTE2
- Models: Logistic regression, Linear mixed models (LMM)
- Modes of inheritance (MOI): dominant, recessive, heterozygous, additive, allelic
- Tools: PLINK1.9, SNPTEST2, R
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