Computational protocol: A Genome-Wide Association Study Provides New Evidence That CACNA1C Gene is Associated With Diabetic Cataract

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Protocol publication

[…] Software SHAPEIT and IMPUTE2 were used to impute nondirectly genotyped single nucleotide polymorphisms (SNP) with reference files from the 1000 genomes phase I datasets (both directly genotyped SNPs and reference files were based on genome assembly National Center for Biotechnology Information b37)., To filter out poorly imputed SNPs, a r2 < 0.3 is applied as it is the lower threshold value recommended by IMPUTE2 and we wanted to maximize the number of SNPs for further analysis.The primary data manipulation software was PLINK and routine quality control steps were frequently applied during data analyses (e.g., removing SNPs with less than 95% genotyping call rate, SNPs with minor allele frequency less than 1%, SNPs that failed Hardy–Weinberg tests P < 0.000001 [based on control samples only], and removing individuals with more than 5% genotype data missing). Single nucleotide polymorphisms on sex chromosomes and mitochondrion were excluded. Multidimensional scaling analysis integrated in PLINK was used to detect population stratification. A lambda value was calculated to indicate the level of stratification. The lambda value should be very close to 1 indicating a minimum ancestry mixture. Samples with pi-hat > 0.125 were discarded due to relatedness. A logistic regression test with multiple covariates was applied to generate P values for SNP associations. A value of P < 5 × 10−8 is considered to be significant.Other GWAS-related software used in our study were: SNPnexus for SNP functional annotation, HaploView for generating Manhattan plots and linkage disequilibrium (LD) blocks, and SNPEVG for generating corresponding quantile-quantile (q-q) plot to evaluate differences between cases and controls caused by potential confounders (different genotyping laboratories, different DNA extraction methods, etc.). Means of age, BMI, cholesterol, triglycerides, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and HbA1c were compared between cases and controls using independent t-test (SPSS 22; IBM Corp., Armonk, NY, USA). Sex difference was compared using a χ2 test. Blood calcium level was compared later using an independent t-test. The whole workflow was shown in . […]

Pipeline specifications

Software tools SHAPEIT, IMPUTE, PLINK, SNPnexus, Haploview, SNPEVG
Application GWAS
Organisms Homo sapiens
Diseases Cataract, Diabetes Mellitus
Chemicals Calcium