filter_proteins {DEP} | R Documentation

## Filter proteins based on missing values

### Description

`filter_proteins` filters a proteomic dataset based on missing values. Different types of filtering can be applied, which range from only keeping proteins without missing values to keeping proteins with a certain percent valid values in all samples or keeping proteins that are complete in at least one condition.

### Usage

    filter_proteins(se, type = c("complete", "condition", "fraction"),
      thr = NULL, min = NULL)

### Arguments

`se` | SummarizedExperiment, Proteomics data (output from `make_se()` or `make_se_parse()`).
`type` | "complete", "condition" or "fraction", Sets the type of filtering applied. "complete" will only keep proteins with valid values in all samples. "condition" will keep proteins that have a maximum of 'thr' missing values in at least one condition. "fraction" will keep proteins that have a certain fraction of valid values in all samples.
`thr` | Integer(1), Sets the threshold for the allowed number of missing values in at least one condition if type = "condition".
`min` | Numeric(1), Sets the threshold for the minimum fraction of valid values allowed for any protein if type = "fraction".

### Value

A filtered SummarizedExperiment object.

### Examples

    # Load example
    data <- UbiLength
    data <- data[data$Reverse != "+" & data$Potential.contaminant != "+",]
    data_unique <- make_unique(data, "Gene.names", "Protein.IDs", delim = ";")

    # Make SummarizedExperiment
    columns <- grep("LFQ.", colnames(data_unique))
    exp_design <- UbiLength_ExpDesign
    se <- make_se(data_unique, columns, exp_design)

    # Filter
    stringent_filter <- filter_proteins(se, type = "complete")
    less_stringent_filter <- filter_proteins(se, type = "condition", thr = 0)

[Package DEP version 1.9.0 Index]