get_peaktable: Convert peak list into an ordered peak table.

In chromatographR: Chromatographic Data Analysis Toolset

Convert peak list into an ordered peak table.

Description

Returns a peak_table object. The first slot contains a matrix of intensities, where rows correspond to samples and columns correspond to aligned features. The rest of the slots contain various meta-data about peaks, samples, and experimental settings.

Usage

get_peaktable(
  peak_list,
  chrom_list,
  response = c("area", "height"),
  use.cor = FALSE,
  hmax = 0.2,
  plot_it = FALSE,
  ask = plot_it,
  clust = c("rt", "sp.rt"),
  sigma.t = NULL,
  sigma.r = 0.5,
  deepSplit = FALSE,
  verbose = FALSE,
  out = c("data.frame", "matrix")
)

Arguments

peak_list	A peak_list object created by get_peaks, containing a nested list of peak tables: the first level is the sample, and the second level is the spectral component. Every component is described by a data.frame where every row is one peak, and the columns contain information on various peak parameters.
chrom_list	A list of chromatographic matrices.
response	Indicates whether peak area or peak height is to be used as intensity measure. Defaults to area setting.
use.cor	Logical. Indicates whether to use corrected retention times (by default) or raw retention times (not advised!).
hmax	Height at which the complete linkage dendrogram will be cut. Can be interpreted as the maximal inter-cluster retention time difference.
plot_it	Logical. If TRUE, for every component a stripplot will be shown indicating the clustering.
ask	Logical. Ask before showing new plot?
clust	Specify whether to perform hierarchical clustering based on spectral similarity and retention time (sp.rt) or retention time alone (rt). Defaults to rt. The sp.rt option is experimental and should be used with caution.
sigma.t	Width of gaussian in retention time distance function. Controls weight given to retention time if sp.rt is selected.
sigma.r	Width of gaussian in spectral similarity function. Controls weight given to spectral correlation if sp.rt is selected.
deepSplit	Logical. Controls sensitivity to cluster splitting. If TRUE, function will return more smaller clusters. See documentation for cutreeDynamic for additional information.
verbose	Logical. Whether to print warning when combining peaks into single time window. Defaults to FALSE.
out	Specify data.frame or matrix as output. Defaults to data.frame.

Details

The function performs a complete linkage clustering of retention times across all samples, and cuts at a height given by the user (which can be understood as the maximal inter-cluster retention time difference) in the simple case based on retention times. Clustering can also incorporate information about spectral similarity using a distance function adapted from Broeckling et al., 2014:

e^{-\frac{(1-c_{ij})^2}{2σ_r^2}}* e^{-\frac{(1-(t_i-t_j)^2}{2σ_t^2}}

If two peaks from the same sample are assigned to the same cluster, a warning message is printed to the console. These warnings can usually be ignored, but one could also consider reducing the hmax variable. However, this may lead to splitting of peaks across multiple clusters. Another option is to filter the peaks by intensity to remove small features.

Value

The function returns a peak_table object, consisting of the following elements:

• tab: the peak table itself – a data-frame of intensities in a sample x peak configuration.

• pk_meta: A data.frame containing peak meta-data (e.g. the spectral component, peak number, and average retention time).

• sample_meta: A data.frame of sample meta-data. Must be added using attach_metadata).

• ref_spectra: A data.frame of reference spectra (in a wavelength x peak configuration). Must be added using attach_ref_spectra

• args: A vector of arguments given to get_peaktable to generate the peak table.

Note

Adapted from getPeakTable function in the alsace package by Ron Wehrens.

Author(s)

Ethan Bass

References

• Broeckling, C. D., Afsar F.A., Neumann S., Ben-Hur A., and Prenni J.E. 2014. RAMClust: A Novel Feature Clustering Method Enables Spectral-Matching-Based Annotation for Metabolomics Data. Anal. Chem. 86:6812-6817. doi: 10.1021/ac501530d

• Wehrens, R., Carvalho, E., Fraser, P.D. 2015. Metabolite profiling in LC–DAD using multivariate curve resolution: the alsace package for R. Metabolomics 11:143-154. doi: 10.1007/s11306-014-0683-5

See Also

attach_ref_spectra attach_metadata

Examples

data(Sa_pr)
pks <- get_peaks(Sa_pr, lambdas = c('210'))
get_peaktable(pks, response = "area")

chromatographR documentation built on Aug. 24, 2022, 9:06 a.m.