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Filter SummarizedExperiment on missing values or formula

filter_se.Rd

filter_se filters a SummarizedExperiment object based on missing values in assay and provides formula. The dataset is filtered for proteins that have a maximum of 'thr' missing values in at least one condition; or a maximum of 'missnum' in all samples; or a filter_formula

Usage

filter_se(
  se,
  thr = NULL,
  missnum = NULL,
  fraction = NULL,
  filter_formula = NULL,
  rowsum_threshold = NULL,
  return_keeprows = FALSE
)

Arguments

se

SummarizedExperiment, Proteomics data (output from make_se() or make_se_parse()).

thr

Integer(1), Sets the threshold for the allowed max number of missing values in at least one condition. At least in one condition, missing values number < or = 'thr'.

missnum

Integer(1), Sets the threshold for the allowed max number among all samples, missing values number < or = 'missnum' in each row.

fraction

A numeric from 0 to 1, threshold of missing occupancy of each row

filter_formula

Formula or character(1). A filter expression, written as a formula.

rowsum_threshold

A numeric, row sum of intensity(abundance) must larger than it.

return_keeprows

Logical(1), default FALSE, return the trimmed object. If TURE return the rows number that pass through filter.

Value

A filtered SummarizedExperiment object, or a vector of keep rows if return_keeprows is TRUE

Examples

# Load example
data(Silicosis_pg)
data <- Silicosis_pg
data_unique <- make_unique(data, "Gene.names", "Protein.IDs", delim = ";")

# Make SummarizedExperiment
ecols <- grep("LFQ.", colnames(data_unique))
se <- make_se_parse(data_unique, ecols, mode = "delim", sep = "_")

# Filter
stringent_filter <- filter_se(se, thr = 0, filter_formula = ~ Reverse != "+" & Potential.contaminant!="+")
#> filter base on missing number is <= 0 in at least one condition.
#> filter base on giving formula 
less_stringent_filter <- filter_se(se, thr = 1, missnum = 2, filter_formula = ~ Reverse != "+" & Potential.contaminant!="+")
#> filter base on missing number <= 2
#> filter base on missing number is <= 1 in at least one condition.
#> filter base on giving formula 
keep_rows <- filter_se(se, thr = 0, filter_formula = ~ Reverse != "+" & Potential.contaminant!="+", return_keeprows = TRUE)
#> filter base on missing number is <= 0 in at least one condition.
#> filter base on giving formula