View source: R/MSstatsConvert_core_functions.R
MSstatsBalancedDesign | R Documentation |
Creates balanced design by removing overlapping fractions and filling incomplete rows
MSstatsBalancedDesign(
input,
feature_columns,
fill_incomplete = TRUE,
handle_fractions = TRUE,
fix_missing = NULL,
remove_few = TRUE
)
input |
|
feature_columns |
str, names of columns that define spectral features |
fill_incomplete |
if TRUE (default), ensures that rows with missing data for specific features are added as NA. For example, if the y10 ion of peptideA is measured in the "disease" samples but entirely missing for the "healthy" samples, rows with NA values will be created for the y10 ion of peptideA in the "healthy" group. This process increases the number of rows to account for all possible feature-sample combinations. |
handle_fractions |
if TRUE (default), overlapping fractions will be resolved |
fix_missing |
str, optional. Defaults to NULL, which means no action. If not NULL, must be one of the options: "zero_to_na" or "na_to_zero". If "zero_to_na", Intensity values equal exactly to 0 will be converted to NA. If "na_to_zero", missing values will be replaced by zeros. |
remove_few |
lgl, if TRUE, features with one or two measurements across runs will be removed. |
data.frame of class MSstatsValidated
unbalanced_data = system.file("tinytest/raw_data/unbalanced_data.csv",
package = "MSstatsConvert")
unbalanced_data = data.table::as.data.table(read.csv(unbalanced_data))
balanced = MSstatsBalancedDesign(unbalanced_data,
c("PeptideSequence", "PrecursorCharge",
"FragmentIon", "ProductCharge"))
dim(balanced) # Now balanced has additional rows (with Intensity = NA)
# for runs that were not included in the unbalanced_data table
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