qc_summary_data() summarizes the quality control results of the input dataset.
It can handles both long and wide dataframes. The function checks the column types,
calculates the percentage of NAs in each column and row, performs a normality test,
calculates the protein-protein correlations, and creates a heatmap of the correlations.
The user can specify the reporting protein-protein correlation threshold.
Usage
qc_summary_data(
wide_data,
sample_id,
unique_threshold = 5,
cor_threshold = 0.8,
cor_method = "pearson",
verbose = TRUE
)Arguments
- wide_data
A dataset in wide format and sample_id as its first column.
- sample_id
The name of the column containing the sample IDs.
- unique_threshold
The threshold to consider a numeric variable as categorical. Default is 5.
- cor_threshold
The threshold to consider a protein-protein correlation as high. Default is 0.8.
- cor_method
The method to calculate the correlation. Default is "pearson".
- verbose
Whether to print the summary. Default is TRUE.