MAFFINNorm: MAFFFIN normalization

View source: R/MAFFINNorm.R

MAFFINNormR Documentation

MAFFFIN normalization

Description

Perform sample normalization using MAFFIN algorithm. MAFFIN algorithm consists of three modules: high-quality feature selection, MS signal intensity correction, and maximal density fold change normalization.

Usage

MAFFINNorm(
  FeatureTable,
  BlankFilter = 2,
  RtRange = c(0, 100),
  QCRSD = 0.25,
  SQCcor = 0.9,
  IntThreshold = 0,
  LR_QC_points = 5,
  QR_QC_points = 7,
  SampleInCol = TRUE,
  output = FALSE
)

Arguments

FeatureTable

Data frame with features in row and samples in column (default).

BlankFilter

A numeric value. High-quality when mean(sample intensities) > mean(blank intensities) * BlankFilter.

RtRange

A numeric vector indicating the range of the defined retention time window, in minute.

QCRSD

A numeric value indicating the relative standard deviation threshold for QC samples.

SQCcor

A numeric value indicating the Pearson's correlation threshold for serial QC samples (recommend: 0.8-0.9).

IntThreshold

A numeric value indicating the feature intensity threshold. Feature is detected when its intensity larger than this value.

LR_QC_points

Minimum serial QC data points for quadratic regression.

QR_QC_points

Minimum serial QC data points for cubic regression.

SampleInCol

TRUE if samples are in column. FALSE if samples are in row.

output

TRUE will output the result table in current working directory.

Details

FeatureTable contains measured signal intensities of metabolic features, with features in row and samples in column (default). The column names should be sample names, and the first row should be sample group names (e.g. control, case).
The first column should be unique feature identifiers. For group names, please use:
"RT" for retention time column;
"QC" for quality control samples between real samples (normal QC samples);
"blank" for blank samples;
"SQC_###" for serial QC samples with a certain loading amount. For example, SQC_1.0 means a serial QC sample with injection volume of 1.0 uL.
An example of FeatureTable is provided as TestingData in this package.

Value

This function will return a list that contains four items if RunEvaluation = TRUE: the normalized feature table, normalization factors, PRMAD of original data, and PRMAD of normalized data. The last two items will not be generated if RunEvaluation = FALSE

References

Yu, Huaxu, and Tao Huan. "MAFFIN: Metabolomics Sample Normalization Using Maximal Density Fold Change with High-Quality Metabolic Features and Corrected Signal Intensities." bioRxiv (2021).

Examples

MAFFINTable = MAFFINNorm(TestingData)

Waddlessss/MAFFIN documentation built on Aug. 5, 2023, 8:10 p.m.