In need of a suitable function to perform the chi-squared test of Hardy-Weinberg-equillibrium in my study poppulation, I ended up writing my own. It also contains a few summarise functions. This is actually the function I am most proud of, as it represents an actual universal test for both bi- and triallelic sustems in non-sexcromosome genes.
### Genotype distribution testing
- hwe_allele.R -- requires input in the form of two vectors with alleles listed
- hwe_geno.R -- requires input as numbers of each genotype (mm, mn, nn for biallelic systems and mm, mn, nn, mo, no, oo for triallelic)
- hwe.sum.R -- summarising tests for genotypes grouped by af factor. Performs HWE test for each group and returns neatly formatted distribution for easy copy-pasting to print. No comparisons of groups. Use the oddsratio or chisq.test.
### Formatting large data frames
- col_fact.R -- formatting columns as factor for names containing text elements of a vector provided. Labels or levels can be provided.
- col_num.R -- formatting columns as numeric for names containing text elements of a vector provided.
### Bivariate logistic regression analyses
- rep_glm.R -- for a stepwise gating regression approach this provides several bivariate logistic regression analyses for columns of a dataframe specified by af vector of the format c(). Use the dput() to obtain names of dataframe in correct format.
