findComplexFeaturesSW: Detect subgroups of proteins within a matrix of protein...

In CCprofiler/CCprofiler: Complex feature detection using SEC protein chromatograms.

Description

Detect subgroups of proteins within a matrix of protein intensity traces by sliding a window across the SEC dimension. Within each window proteins with traces that correlate well are clustered together.

Usage

findComplexFeaturesSW(trace.mat, corr.cutoff, window.size, with.plot = F,
  min.sec = 1)

Arguments

trace.mat	A matrix of all traces in a complex hypothesis with small perturbations added to all 0 values for correlation calculation.
corr.cutoff	The correlation value for chromatograms above which proteins are considered to be coeluting.
window.size	Size of the window. Numeric.
with.plot	T (TRUE) or F (FALSE) whether to plot the correlation tree.
min.sec	The lowest SEC number in the sample.
noise.quantile	The quantile to use in estimating the noise level. Intensity values that are zero are imputed with random noise according to the noise estimation.

Value

An object of type complexFeaturesSW that is a list containing the following:

• feature data.table containing complex feature candidates in the following format:

  • subgroup The protein_ids of the feature separated by semi-colons.

  • left_sw The left boundary of the sliding-window feature.

  • right_sw The right boundary of the sliding-window feature.

  • score The intra-sliding-window-feature correlation.

• window.size The window.size used when running this function.

• corr.cutoff The corr.cutoff used when running this function.

Examples

# NOT RUN:
# protein.ids <- corum.complex.protein.assoc[complex_id == 181, protein_id]
# traces <- subset(protein.traces[protein_id %in% protein.ids],
#                  select=-protein_id)
# sw.res <- findComplexFeaturesSW(traces, protein.ids, protein.mw.conc)

CCprofiler/CCprofiler documentation built on May 19, 2021, 7:40 p.m.