msFilter: Function for filtering abundance data set.

In MSPrep: Package for Summarizing, Filtering, Imputing, and Normalizing Metabolomics Data

Description

Filters compounds to those found in specified proportion of samples.

Usage

msFilter(
  data,
  filterPercent = 0.8,
  compVars = c("mz", "rt"),
  sampleVars = c("subject_id"),
  colExtraText = NULL,
  separator = NULL,
  missingValue = NA,
  returnToSE = FALSE,
  returnToDF = FALSE
)

Arguments

data	Data set as either a data frame or 'SummarizedExperiement'.
filterPercent	Decimal value indicating filtration threshold. Compounds which are present in fewer samples than the specified proportion will be removed.
compVars	Vector of the columns which identify compounds. If a 'SummarizedExperiment' is used for 'data', row variables will be used.
sampleVars	Vector of the ordered sample variables found in each sample column.
colExtraText	Any extra text to ignore at the beginning of the sample columns names. Unused for 'SummarizedExperiments'.
separator	Character or text separating each sample variable in sample columns. Unused for 'SummarizedExperiment'.
missingValue	Specifies the abundance value which indicates missing data. May be a numeric or 'NA'.
returnToSE	Logical value indicating whether to return as 'SummarizedExperiment'
returnToDF	Logical value indicating whether to return as data frame.

Value

A data frame or 'SummarizedExperiment' with filtered abundance data. Default return type is set to match the data input but may be altered with the 'returnToSE' or 'returnToDF' arguments.

Examples

# Load example data set, summarize replicates
data(msquant)

summarizedDF <- msSummarize(msquant,
                            compVars = c("mz", "rt"),
                            sampleVars = c("spike", "batch", "replicate", 
                            "subject_id"),
                            cvMax = 0.50,
                            minPropPresent = 1/3,
                            colExtraText = "Neutral_Operator_Dif_Pos_",
                            separator = "_",
                            missingValue = 1)

# Filter the dataset using a 80% filter rate
filteredDF <- msFilter(summarizedDF,
                       filterPercent = 0.8,
                       compVars = c("mz", "rt"),
                       sampleVars = c("spike", "batch", "subject_id"),
                       separator = "_")

MSPrep documentation built on Nov. 8, 2020, 5:07 p.m.