the Principal Components Analysis need the data must be transformed

pca_data_tidy(data, id = NULL)

Arguments

data	the input data must be a dataframe or tibble which' rownames is gene id and colnames is sample name
id	the rowid, can be a character or the column number

Value

a dataframe

Examples

test = matrix(rnorm(200), 20, 10)
test[1:10, seq(1, 10, 2)] = test[1:10, seq(1, 10, 2)] + 3
test[11:20, seq(2, 10, 2)] = test[11:20, seq(2, 10, 2)] + 2
test[15:20, seq(2, 10, 2)] = test[15:20, seq(2, 10, 2)] + 4
colnames(test) = paste("Test", 1:10, sep = "")
rownames(test) = paste("Gene", 1:20, sep = "")
annot <- c(rep("KEGG",20))
test <- data.frame(test,annot)
pca_data_tidy(as.data.frame(test)) -> test
#> ... Notice: the input data is a data frame not a tibble
#> ... Problem: the input data vaule in every column must be numberic value
#> ... Problem: the error because the character type value in data
#> ... Successed! the pca data save in the object