Quantitative Genetics Data Analysis

This is the notebook developed in class. It shows how genotype frequencies can be determined using R.

We want to read a dataset with genotype and phenotype information.

s_gen_phen_data <- "https://charlotte-ngs.github.io/lbgfs2022/data/p1_mrk_one_locus.csv"
tbl_gen_phen <- readr::read_csv2(file = s_gen_phen_data)
head(tbl_gen_phen)

The summary of the phenotype column is given by

summary(tbl_gen_phen$Phenotype)

By default the column with phenotypes is interpreted as character data. With the statement below they are converted to numbers.

tbl_gen_phen$Phenotype <- as.numeric(tbl_gen_phen$Phenotype)
head(tbl_gen_phen)

Now the summary of the phenotypes yields a more meaningful result.

summary(tbl_gen_phen$Phenotype)

Genotype Frequencies

Using the function table from the base package

table(tbl_gen_phen$Genotype)

Alternative using the package dplyr

library(dplyr)
gb <- group_by(tbl_gen_phen,Genotype) 
sg <- summarize(gb, geno_count = n())
mutate(sg, geno_freq = geno_count / sum(geno_count))

Using pipes %>% makes it shorter. Remember the convention for pipes: g(f(data)) can be written as data %>% f() %>% g()

tbl_gen_phen %>%
  group_by(Genotype) %>%
  summarize(geno_count = n()) %>%
  mutate(geno_freq = geno_count / sum(geno_count))