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Feature Filtering Based on Quality Control Criteria

Source: R/qc-filtering.R
filter_features_qc.Rd

Filters a dataset based on quality control (QC) criteria, including intensity, coefficient of variation (CV), signal-to-blank ratios, D-ratio, response curve properties, and proportion of missing values. Criteria apply to different QC types (BQC, TQC) and measurement variables (concentration, intensity, and normalized intensity).

Usage

filter_features_qc(
  data = NULL,
  replace_existing = TRUE,
  batch_medians = FALSE,
  qualifier.include = FALSE,
  istd.include = FALSE,
  features.to.keep = NULL,
  max.prop.missing.intensity.spl = NA,
  max.prop.missing.normintensity.spl = NA,
  max.prop.missing.conc.spl = NA,
  min.intensity.lowest.bqc = NA,
  min.intensity.lowest.tqc = NA,
  min.intensity.lowest.spl = NA,
  min.intensity.median.bqc = NA,
  min.intensity.median.tqc = NA,
  min.intensity.median.spl = NA,
  min.intensity.highest.spl = NA,
  min.signalblank.median.spl.pblk = NA,
  min.signalblank.median.spl.ublk = NA,
  min.signalblank.median.spl.sblk = NA,
  max.cv.intensity.bqc = NA,
  max.cv.intensity.tqc = NA,
  max.cv.normintensity.bqc = NA,
  max.cv.normintensity.tqc = NA,
  max.cv.conc.bqc = NA,
  max.cv.conc.tqc = NA,
  response.curves.select = NA,
  response.curves.summary = NA,
  min.rsquare.response = NA,
  min.slope.response = NA,
  max.slope.response = NA,
  max.yintercept.response = NA,
  max.dratio.sd.conc.bqc = NA,
  max.dratio.sd.conc.tqc = NA,
  max.dratio.mad.conc.bqc = NA,
  max.dratio.mad.conc.tqc = NA,
  max.dratio.sd.normint.bqc = NA,
  max.dratio.sd.normint.tqc = NA,
  max.dratio.mad.normint.bqc = NA,
  max.dratio.mad.normint.tqc = NA
)

Arguments

data

MidarExperiment object.

replace_existing

Logical. If TRUE, replaces any existing filters; if FALSE, adds new filters on top of existing ones. Default is TRUE.

batch_medians

Logical. If TRUE, uses batch-wise median QC values for filtering. Default is FALSE.

qualifier.include

Logical. If TRUE, includes qualifier features in the filtering process. Default is FALSE.

istd.include

Logical. If TRUE, includes internal standards (ISTDs) in the filtering process. Default is FALSE.

features.to.keep

A vector of feature identifiers to retain, even if they do not meet the filtering criteria.

max.prop.missing.intensity.spl

Maximum proportion of missing intensity values among study samples (SPL). Default is NA.

max.prop.missing.normintensity.spl

Maximum proportion of missing normalized intensity values among study samples (SPL). Default is NA.

max.prop.missing.conc.spl

Maximum proportion of missing concentration values among study samples (SPL). Default is NA.

min.intensity.lowest.bqc

Minimum intensity of the lowest BQC sample. Default is NA.

min.intensity.lowest.tqc

Minimum intensity of the lowest TQC sample. Default is NA.

min.intensity.lowest.spl

Minimum intensity of the lowest study sample (SPL). Default is NA.

min.intensity.median.bqc

Minimum median intensity of BQC samples. Default is NA.

min.intensity.median.tqc

Minimum median intensity of TQC samples. Default is NA.

min.intensity.median.spl

Minimum median intensity of study samples (SPL). Default is NA.

min.intensity.highest.spl

Minimum intensity of the highest intensity study sample (SPL). Default is NA.

min.signalblank.median.spl.pblk

Minimum signal-to-blank ratio for SPL samples and PBLK. Default is NA.

min.signalblank.median.spl.ublk

Minimum signal-to-blank ratio for SPL samples and UBLK. Default is NA.

min.signalblank.median.spl.sblk

Minimum signal-to-blank ratio for SPL samples and SBLK. Default is NA.

max.cv.intensity.bqc

Maximum CV for intensity in BQC samples. Default is NA.

max.cv.intensity.tqc

Maximum CV for intensity in TQC samples. Default is NA.

max.cv.normintensity.bqc

Maximum CV for normalized intensity in BQC samples. Default is NA.

max.cv.normintensity.tqc

Maximum CV for normalized intensity in TQC samples. Default is NA.

max.cv.conc.bqc

Maximum CV for concentration in BQC samples. Default is NA.

max.cv.conc.tqc

Maximum CV for concentration in TQC samples. Default is NA.

response.curves.select

Select specific response curves by ID. Default is NA.

response.curves.summary

Define the method to summarize multiple response curves. Default is NA.

min.rsquare.response

Minimum R-squared value for the response curves. Default is NA.

min.slope.response

Minimum slope for the response curve. Default is NA.

max.slope.response

Maximum slope for the response curve. Default is NA.

max.yintercept.response

Maximum y-intercept of the response curve. Default is NA.

max.dratio.sd.conc.bqc

Maximum allowed D-ratio (SD of BQC / SD of SPL) using standard deviation for BQC samples. Default is NA.

max.dratio.sd.conc.tqc

Maximum allowed D-ratio (SD of TQC / SD of SPL) using standard deviation for TQC samples. Default is NA.

max.dratio.mad.conc.bqc

Maximum allowed D-ratio (MAD of BQC / MAD of SPL) using mean absolute deviation for BQC samples. Default is NA.

max.dratio.mad.conc.tqc

Maximum allowed D-ratio (MAD of TQC / MAD of SPL) using mean absolute deviation for TQC samples. Default is NA.

max.dratio.sd.normint.bqc

Maximum allowed D-ratio (SD of normalized intensity in BQC / SD of SPL) using standard deviation. Default is NA.

max.dratio.sd.normint.tqc

Maximum allowed D-ratio (SD of normalized intensity in TQC / SD of SPL) using standard deviation. Default is NA.

max.dratio.mad.normint.bqc

Maximum allowed D-ratio (MAD of normalized intensity in BQC / MAD of SPL) using mean absolute deviation. Default is NA.

max.dratio.mad.normint.tqc

Maximum allowed D-ratio (MAD of normalized intensity in TQC / MAD of SPL) using mean absolute deviation. Default is NA.

Value

The input MidarExperiment object with the feature filtering criteria applied.

Details

This function implements filtering criteria based on quality control (QC) samples and additional analytical parameters, following recommendations outlined by Broadhurst et al. (2018). The implemented criteria evaluate data quality through analysis of QC samples, blanks, and study samples.

References

Broadhurst, D., Goodacre, R., Reinke, S. N., Kuligowski, J., Wilson, I. D., Lewis, M. R., & Dunn, W. B. (2018). Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in clinical studies. Metabolomics, 14(6), 72. doi:10.1007/s11306-018-1367-3