imaging_Spatial_Quant: imaging_Spatial_Quant

In MASHUOA/HiTMaP: A collection of tools for imaging MS data processing

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
                       )

MASHUOA/HiTMaP documentation built on April 5, 2024, 5:48 p.m.