MSstatsSummarizeSingleTMP | R Documentation |
Tukey Median Polish summarization for a single protein
MSstatsSummarizeSingleTMP(
single_protein,
impute,
censored_symbol,
remove50missing
)
single_protein |
feature-level data for a single protein |
impute |
only for summaryMethod = "TMP" and censoredInt = 'NA' or '0'. TRUE (default) imputes 'NA' or '0' (depending on censoredInt option) by Accelated failure model. FALSE uses the values assigned by cutoffCensored |
censored_symbol |
Missing values are censored or at random. 'NA' (default) assumes that all 'NA's in 'Intensity' column are censored. '0' uses zero intensities as censored intensity. In this case, NA intensities are missing at random. The output from Skyline should use '0'. Null assumes that all NA intensites are randomly missing. |
remove50missing |
only for summaryMethod = "TMP". TRUE removes the proteins where every run has at least 50% missing values for each peptide. FALSE is default. |
list of two data.tables: one with fitted survival model, the other with protein-level data
raw = DDARawData
method = "TMP"
cens = "NA"
impute = TRUE
# currently, MSstats only supports MBimpute = FALSE for linear summarization
MSstatsConvert::MSstatsLogsSettings(FALSE)
input = MSstatsPrepareForDataProcess(raw, 2, NULL)
input = MSstatsNormalize(input, "EQUALIZEMEDIANS")
input = MSstatsMergeFractions(input)
input = MSstatsHandleMissing(input, "TMP", TRUE, "NA", 0.999)
input = MSstatsSelectFeatures(input, "all")
input = MSstatsPrepareForSummarization(input, method, impute, cens, FALSE)
input_split = split(input, input$PROTEIN)
single_protein_summary = MSstatsSummarizeSingleTMP(input_split[[1]],
impute, cens, FALSE)
head(single_protein_summary[[1]])
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