imaging_Spatial_Quant: imaging_Spatial_Quant

View source: R/Utilities_IMS_processing.R

imaging_Spatial_QuantR Documentation

imaging_Spatial_Quant

Description

This is a spatial quantitation function for maldi imaging data set this function will read the candidate list file and generate quantification result

Usage

imaging_Spatial_Quant(
  datafile = tk_choose.files(filter = matrix(c("imzml file", ".imzML", "Text", ".txt",
    "All files", "*"), 3, 2, byrow = TRUE), caption =
    "Choose single or multiple file(s) for analysis"),
  threshold = 0,
  ppm = 2.5,
  Quant_list = "Metabolites of Interest.csv",
  adducts = c("M-H", "M+Cl"),
  cal.mz = F,
  mzlist_bypass = T,
  IMS_analysis = TRUE,
  Protein_feature_summary = T,
  plot_cluster_image = T,
  plot_style = "fleximaging",
  Peptide_feature_summary = T,
  plot_ion_image = FALSE,
  parallel = detectCores()/2,
  spectra_segments_per_file = 5,
  Smooth_range = 1,
  Segmentation = c("spatialKMeans", "spatialShrunkenCentroids", "Virtual_segmentation",
    "none"),
  Virtual_segmentation_rankfile = tk_choose.files(default =
    "Z:/George skyline results/maldiimaging/Maldi_imaging - Copy/radius_rank.csv",
    caption = "Choose Virtual segmentation rank info file"),
  Spectrum_feature_summary = T,
  Region_feature_summary = T,
  Region_feature_analysis = T,
  plot_each_metabolites = T,
  Cluster_level = "High",
  ClusterID_colname = "Name",
  Region_feature_analysis_bar_plot = T,
  norm_datafiles = T,
  norm_Type = "Median",
  mzrange = "auto-detect",
  BPPARAM = bpparam(),
  Rotate_IMG = NULL,
  ...
)

Arguments

datafile

specify the imzML data files

threshold

specify the intensities threshold (0 to 1 in percentage)to report a identified molecule

ppm

the mz tolerance (in ppm) for peak integration

Quant_list

the quantifiaction candidate list, spatial quantification will go through every datafile and collect the ion intensities for each listed component

adducts

the adducts list to be used for generating the PMF search candidates

cal.mz

If set with "true", the function will recalculate the mz value according to the column named "formular" in the Quant_list and the specified adducts.

mzlist_bypass

Set "true" if you want to bypass the mzlist generating process

Protein_feature_summary

"IMS_analysis" follow-up process that will collect all the identified peptide information and associate them with possible proteins

plot_cluster_image

"Protein_feature_summary" follow-up process that will plot the protein cluster image

plot_ion_image

"Peptide_feature_summarya" follow-up process that will plot every connponents in the "peptide shortlist"

parallel

the number of threads will be used in the PMF search, this option now only works for windows OS

spectra_segments_per_file

optimal number of distinctive regions in the imaging, a virtual segmentation will be applied to the image files with this value. To have a better PMF result you may set a value that in the sweet point of sensitivety and false discovery rate (FDR).

Smooth_range

"Segmentation" pixel smooth range

Segmentation

set as "spatialKMeans" to enable a "spatialKMeans" Segmentation; set as "spatialShrunkenCentroids" to enable a "spatialShrunkenCentroids" Segmentation; If a region rank file was supplied, you can set this as "Virtual_segmentation" to perform a manual segmentation; Set it as "none" to bypass the segmentation.

Virtual_segmentation_rankfile

specify a region rank file contains region information for manualy region segmentation

Peptide_feature_summarya

"IMS_analysis" follow-up process that will summarize all datafiles identified peptides and generats a "peptide shortlist" in the result summary folder

Value

None

Examples

imaging_Spatial_Quant(threshold=0.05, ppm=5,Digestion_site="[G]",
                       missedCleavages=0:1,Fastadatabase="murine_matrisome.fasta",
                       adducts=c("M+H","M+NH4","M+Na"),IMS_analysis=TRUE,
                       Protein_feature_summary=TRUE,plot_cluster_image=TRUE,
                       Peptide_feature_summary=TRUE,plot_ion_image=FALSE,
                       parallel=3,spectra_segments_per_file=5,spatialKMeans=TRUE
                       )


guoguodigit/Metwork documentation built on July 18, 2024, 7:34 p.m.