romicsOutlierEval: romics_outlier_eval()

In PNNL-Comp-Mass-Spec/RomicsProcessor: omics-oriented package for reproducible and sharable data processing pipelines

romics_outlier_eval()

Description

Plots the the pmartR method for the evaluation of outliers (require the installation of the package pmartR). To remove the outlier below a certain treshold use the function Romics_outlier_remove()

Usage

romicsOutlierEval(
  romics_object,
  seed = 42,
  metrics = c("Correlation", "Proportion_Missing", "MAD", "Skewness"),
  pvalue_threshold = 0.01,
  label = TRUE
)

Arguments

romics_object	A log transformed romics_object created using romicsCreateObject() and transformed using the function log2transform() or log10transform()
seed	An integer of length 1, by default 42 will be used
metrics	A character vector containing the following terms to indicate which parameters to use for the filtering of the data : 'Correlation', 'Proportion_Missing','MAD', 'Skewness'. By defaults all parameters will be used.
pvalue_threshold	A numeric vector of lenght 1 indicating the pvalue threshold to be used.
label	Either TRUE or FALSE to indicate if the labels have to be plotted.

Details

This function requires the package 'pmartR' to be installed and loaded to be excecuted. It will calculate and plot the samples to be filtered out using the function Romics_outlier_eval().

Value

This function will print the pmartR filtering details and will return 2 plots the first one is a scatter plot of the pvalue by log2(Robust Mahalanobis Distance) the second one is a scatter plot of the log2(Robust Mahalanobis Distance) per sample.

Author(s)

Geremy Clair

References

Matzke, M., Waters, K., Metz, T., Jacobs, J., Sims, A., Baric, R., Pounds, J., and Webb-Robertson, B.J. (2011), Improved quality control processing of peptide-centric LC-MS proteomics data. Bioinformatics. 27(20): 2866-2872.

PNNL-Comp-Mass-Spec/RomicsProcessor documentation built on March 18, 2023, 5:14 a.m.