View source: R/chromatogram_manip.R
smoothXICs | R Documentation |
Smoothing methods are Savitzky-Golay, Boxcar, Gaussian kernel and LOESS. Savitzky-Golay smoothing is good at preserving peak-shape compared to gaussian and boxcar smoothing. However, it assumes equidistant points that fortunately is the case for DIA data. This requires a quadratic memory to store the fit and slower than other smoothing methods.
smoothXICs(
XICs,
type = "none",
samplingTime = NULL,
kernelLen = 9L,
polyOrd = NULL
)
XICs |
(A list) A list of dataframe that consists of two columns. First column must be monotonically increasing. |
type |
(char) must be either sgolay, boxcar, gaussian, loess or none. |
samplingTime |
(numeric) Time difference between neighboring points. |
kernelLen |
(integer) Number of data-points to consider in the kernel. |
polyOrd |
(integer) Order of the polynomial to be fit in the kernel. |
A list.
Shubham Gupta, shubh.gupta@mail.utoronto.ca
ORCID: 0000-0003-3500-8152
License: (c) Author (2020) + GPL3 Date: 2020-02-21
https://terpconnect.umd.edu/~toh/spectrum/Smoothing.html, https://rafalab.github.io/dsbook/smoothing.html
data("XIC_QFNNTDIVLLEDFQK_3_DIAlignR")
XICs <- XIC_QFNNTDIVLLEDFQK_3_DIAlignR[["hroest_K120808_Strep10%PlasmaBiolRepl1_R03_SW_filt"]][["4618"]]
newXICs <- smoothXICs(XICs, type = "sgolay", samplingTime = 3.42, kernelLen = 9,
polyOrd = 3)
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