Filter data by abundance (with user-input percentile cutoff) of missing values (with user-input percent cutoff). Missing values are commonly found in metabolomics data.
FilterData(
inputData,
analyteType1perc = 0,
analyteType2perc = 0,
analyteMiss = 0,
suppressWarnings = FALSE,
cov.cutoff = 0
)filtData IntLimData object with input data after filtering
IntLimData object (output of ReadData()) with analylte levels and associated meta-data
percentile cutoff (0-1) for filtering analyte type 1 (e.g. remove analytes with mean values < 'analyteType1perc' percentile) (default: 0)
percentile cutoff (0-1) for filtering analyte type 2 (default: no filtering of analytes) (default:0)
missing value percent cutoff (0-1) for filtering both analyte types (analytes with > 80% missing values will be removed) (default:0)
whether or not to print warnings. If TRUE, warnings will not be printed.
percentile cutoff (0-1) for the covariances of the anaytes (default: 0.30)