MSstatsSummarize {MSstats} | R Documentation

## Feature-level data summarization

### Description

Feature-level data summarization

### Usage

    MSstatsSummarize(
      proteins_list,
      method,
      impute,
      censored_symbol,
      remove50missing,
      equal_variance
    )

### Arguments

`proteins_list` | list of processed feature-level data
`method` | summarization method: "linear" or "TMP"
`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.
`equal_variance` | only for summaryMethod = "linear". Default is TRUE. Logical variable for whether the model should account for heterogeneous variation among intensities from different features. Default is TRUE, which assume equal variance among intensities from features. FALSE means that we cannot assume equal variance among intensities from features, then we will account for heterogeneous variation from different features.

### Value

list of length one with run-level data.

### 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 = MSstatsSelectFeatures(input, "all")
    processed = getProcessed(input)
    input = MSstatsPrepareForSummarization(input, method, impute, cens, FALSE)
    input_split = split(input, input$PROTEIN)
    summarized = MSstatsSummarize(input_split, method, impute, cens, FALSE, TRUE)
    length(summarized) # list of summarization outputs for each protein
    head(summarized[[1]][[1]]) # run-level summary

[Package MSstats version 4.0.1 Index]