Computational protocol: Genetic predisposition of six well‐defined polymorphisms in HMGB1/RAGE pathway to breast cancer in a large Han Chinese population

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Protocol publication

[…] All examined polymorphisms were checked for adherence to Hardy–Weinberg equilibrium by the chi‐squared test to avoid population stratification or genotyping misclassification. The genotype/allele distributions between patients and controls were compared by the chi‐squared test or Fisher's exact test where appropriate. Besides overall comparisons, stratified analyses according to the median values of age and age of menarche among all subjects were also conducted for the genotype/allele distributions between the two groups. The risk prediction for breast cancer was quantified by Logistic regression analyses before and after controlling for confounding factors (age and age of menarche). Effect‐size estimates were expressed as odds ratio (OR) and its 95% confidence interval (95% CI).Considering the fact that the impact of a single polymorphism might be small, the co‐occurrence of unfavourable alleles of multiple polymorphisms can enhance the risk for breast cancer. A genetic score is therefore created on the basis of the number of unfavourable alleles for each subject by assigning zero, one or two unfavourable alleles of each polymorphism and summing them up. Besides per score increment, total genetic score was also collapsed into quartiles, and risk prediction was quantified by Logistic regression analyses before and after controlling for confounding factors. In addition, haplotype analysis is proven to be more informative than studying the role of polymorphisms independently. Haplotype analysis was undertaken within each gene under a generalized linear model by using the HAPLO.STATS program before and after controlling for confounding factors. The HAPLO.STATS program was implemented in the R Project for Statistical Computing version 2.6.2 (available at the website www.r-project.org/).Unless otherwise stated all statistical analyses were carried out by Stata software version 13.0 (StataCorp LP, College Station, TX, USA). The power to reject null association was calculated by the PS: Power and Sample Size Calculation software version 3.0 (Copyright © 1997‐2009 by William D. Dupont and Walton D. Plummer) . […]

Pipeline specifications

Software tools haplo.stats, The R Project for Statistical Computing
Application GWAS
Organisms Homo sapiens