plotFilterImpact: Plot Peptide Elution Profiles per Protein without and with...

In heuselm/mocode: Integrates MS-based-proteomics Data Analysis Code

Plot Peptide Elution Profiles per Protein without and with Filters Applied

Description

Native elution profiling data can be noisy. To suppress noise and select for the high quality signals, filters can be applied. This function wraps the filtering functions filterConsecutiveIdStretches() and filterByPeptideCorrelation() and visualizes their impact on protein elution profiles by combined plots of all peptides of a protein over the elution fraction number.

Usage

plotFilterImpact(
  traces,
  traces.sf = NULL,
  sf_setting = 3,
  traces.cf = NULL,
  cf_setting = 0.2
)

Arguments

traces	A traces object containing $peptide.profiles data.table with protein_id and peptide_id col
traces.sf	A traces object containing stretch-filtered $peptide.profiles as generated by filterConsecutiveIdStretches(). data.table with protein_id and peptide_id col. If not provided, it is generated.
sf_setting	min_stretch_length setting that is used to generate the stretch-filtered peptide traces data if not provided. Defaults to 3.
traces.cf	A traces object containing correlation-filtered $peptide.profiles as generated by filterByPeptideCorrelation() data.table with protein_id and peptide_id col. If not provided, it is generated.
cf_setting	average_corr_cutoff setting that is used to generate the correlation-filtered peptide traces data if not provided. Defaults to 0.2.

Value

A data.table with the number of proteins and peptides remaining after filtering. Generates a FilterImpact.pdf in the working folder.

Examples

# NOT RUN:
# filterImpactNumbers <- plotFilterImpact(peptide.traces)

heuselm/mocode documentation built on Oct. 23, 2023, 8:43 a.m.