MSstatsSelectFeatures: Feature selection before feature-level data summarization

In MeenaChoi/MSstats: Protein Significance Analysis in DDA, SRM and DIA for Label-free or Label-based Proteomics Experiments

Feature selection before feature-level data summarization

Description

Feature selection before feature-level data summarization

Usage

MSstatsSelectFeatures(input, method, top_n = 3, min_feature_count = 2)

Arguments

input	data.table
method	"all" / "highQuality", "topN"
top_n	number of features to use for "topN" method
min_feature_count	number of quality features for "highQuality" method

Value

data.table

Examples

raw = DDARawData 
method = "TMP"
cens = "NA"
impute = TRUE
MSstatsConvert::MSstatsLogsSettings(FALSE)
input = MSstatsPrepareForDataProcess(raw, 2, NULL)
input = MSstatsNormalize(input, "EQUALIZEMEDIANS")
input = MSstatsMergeFractions(input)
input = MSstatsHandleMissing(input, "TMP", TRUE, "NA", 0.999)
input_all = MSstatsSelectFeatures(input, "all") # all features
input_5 = MSstatsSelectFeatures(data.table::copy(input), "topN", top_n = 5) # top 5 features
input_informative = MSstatsSelectFeatures(input, "highQuality") # feature selection

head(input_all)
head(input_5)
head(input_informative)

MeenaChoi/MSstats documentation built on Nov. 10, 2024, 2:43 p.m.