MSstatsSummarizeSingleTMP {MSstats} | R Documentation

## Tukey Median Polish summarization for a single protein

### Description

Tukey Median Polish summarization for a single protein

### Usage

    MSstatsSummarizeSingleTMP(
      single_protein,
      impute,
      censored_symbol,
      remove50missing
    )

### Arguments

`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 runs which have more than 50% missing values. FALSE is default.

### Value

list of two data.tables: one with fitted survival model, the other with protein-level data

### Examples

    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]])

[Package MSstats version 4.1.1 Index]