EIC.plot.learn: Plot extracted ion chromatograms based on the machine...

In yufree/apLCMS: Adaptive processing of LC-MS data

Plot extracted ion chromatograms based on the machine learning method output

Description

Given an output object from the function semi.sup.learn(), this function plots the EICs selected by the user.

Usage

EIC.plot.learn(aligned, rows = NA, colors = NA, transform = "none",
                 subset = NA, tol = 2.5e-05, ridge.smoother.window =
                 50, baseline.correct = 0, max.spline.time.points =
                 1000)

Arguments

aligned	An output object from cdf.to.ftr().
rows	A numeric vector selecting which rows of the aligned feature table to be plotted.
colors	The colors (one per profile) the user wishes to use for the plots. The default is NA, in which case a default color set is used.
transform	There are four possible values. "none": the original intensity data is plotted; "log": the intensity data is transformed by log(x+1); "sqrt": the intensity data is square root transformed; "cuberoot": the intensity data is cube root transformed.
subset	The user can choose a subset of the profiles for which the EICs are plotted. It is given as a vector of profile indecies. The default is NA, in which case the EICs from all the profiles are plotted.
tol	The mz tolerance level used in learn.cdf().
ridge.smoother.window	The ridge.smoother.window parameter value used in learn.cdf().
baseline.correct	The baseline.correct parameter value used in learn.cdf().
max.spline.time.points	The maximum number of points to use in the spline fit along the retention time axis.

Details

The function plots a single EIC. It plots intensity against retention time. It uses different color for different profiles.

Value

There is no return value.

Author(s)

Tianwei Yu <[e-mail]>

References

Bioinformatics. 25(15):1930-36. BMC Bioinformatics. 11:559.

yufree/apLCMS documentation built on May 19, 2024, 1:22 p.m.