Computational protocol: Genetic variants of SLC12A3 modulate serum lipid profiles in a group of Mongolian pedigree population

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Protocol publication

[…] Four serum lipid variables (TCHO, TG, HDL-C, and LDL-C),which can be used to assess individuals’ metabolism status, were selected as quantitative phenotypes for association analysis. PASW statistics 18 (formerly SPSS Statistics; was used to analyze the characteristics of demographic variables and the features of sample’s serum lipid levels with parental group. The difference of continuous variables (e.g., age, BMI, WHR, TCHO, TG, HDL-C, LDL-C) were analyzed by t test for two groups and ANOVA for three or more groups, and non-parameter test (e.g., Kruskal Wallis test) also performed if variables didn’t meet the normal distribution. The categorical variables (e.g., smoking and drinking) were analyzed by Fisher’s exact Chi-square test. The correlation of demographic variables was evaluated by multiple regression analysis, within parental group. To identify potential Mendelian errors, the PEDCHECK program was used to test the family structure before running the family-based association test []. The pedigrees, which were not consistent with Mendelian inheritance, were excluded from quantitative phenotypic analysis. For single marker, it was analyzed by FBAT program in the additive and dominant models, respectively [], with a null hypothesis of no linkage and no association. Then, the haplotypes created based upon significant association with the individuals’ serum lipid level in both additive and dominant genetic models, were tested using the HBAT extension of FBAT. Both haplotype-specific and a multiallelic (global) test were calculated for haplotypes for which there were a minimum of 10 informative families. The empirical variance estimator option (−e) was used as our primary hypothesis, and P-values generated by permutation tests (default n = 10,000) as correction for multiple testing. The statistical power of this study with the present sample size was also estimated by Quanto 1.2.4 [], under the “case-parent trio” type of study designs, and with a rather lower genetic effect (Rg2 = 0.10) for all SNPs. All testing was performed with a type I error rate of 0.05. […]

Pipeline specifications

Software tools SPSS, PedCheck, FBAT, Quanto
Applications Miscellaneous, GWAS
Organisms Homo sapiens
Diseases Hypertension