Filter proteins based on missing values — prot.filter

prot.filter_missing filters a proteomics 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

prot.filter_missing(
  se,
  type = c("complete", "condition", "fraction", NULL),
  thr = NULL,
  min = NULL
)

Arguments

se: SummarizedExperiment object, proteomics data parsed with prot.read_data.
type: (Character string) "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 min fraction of valid values in all samples.
thr: (Integer) Sets the threshold for the allowed number of missing values in at least one condition if type = "condition". In other words: "keep proteins that have a maximum of 'thr' missing values in at least one condition."
min: (Numeric) Sets the threshold for the minimum fraction of valid values allowed for any protein if type = "fraction".

Value

A filtered SummarizedExperiment object.