Hi HiTMaP team,
I was trying to run the code using my data and encountered an error not sure how to fix it. any help would be greatly appreciated.
my code
preprocess = list(force_preprocess=TRUE,
use_preprocessRDS=FALSE,
smoothSignal=list(method = c("Disable", "gaussian", "sgolay", "ma")[1]),
reduceBaseline=list(method = c("Disable", "locmin", "median")[1]),
peakPick=list(method=c("diff", "sd", "mad", "quantile", "filter", "cwt")[3]),
peakAlign=list(tolerance=5, units="ppm", level=c("local","global")[1], method=c("Enable","Disable")[1]),
normalize=list(method=c("Disable","rms","tic","reference")[1], mz=NULL)
)
imaging_identification(
==============Choose the imzml raw data file(s) to process make sure the fasta file in the same folder
==============The parameters for Cluster imaging. Specify the annotations of interest, the program will perform a case-insensitive search on the result file, extract the protein(s) of interest and plot them in the cluster imaging mode
plot_cluster_image_grid=TRUE,
ClusterID_colname="Protein",
componentID_colname="Peptide",
Protein_desc_of_interest= ".",
Rotate_IMG=NULL,
)
This is the output
4 Cores detected, 4 threads will be used for computing
1 files were selected and will be used for Searching
uniprotkb_proteome_UP000005640_AND_revi_2024_11_07.fasta was selected as database. Candidates will be generated through Proteomics mode
Hi HiTMaP team, I was trying to run the code using my data and encountered an error not sure how to fix it. any help would be greatly appreciated. my code preprocess = list(force_preprocess=TRUE, use_preprocessRDS=FALSE, smoothSignal=list(method = c("Disable", "gaussian", "sgolay", "ma")[1]), reduceBaseline=list(method = c("Disable", "locmin", "median")[1]), peakPick=list(method=c("diff", "sd", "mad", "quantile", "filter", "cwt")[3]), peakAlign=list(tolerance=5, units="ppm", level=c("local","global")[1], method=c("Enable","Disable")[1]), normalize=list(method=c("Disable","rms","tic","reference")[1], mz=NULL) )
imaging_identification(
==============Choose the imzml raw data file(s) to process make sure the fasta file in the same folder
==============specify the digestion enzyme specificity
==============specify the range of missed Cleavages
==============Set the target fasta file
==============Set the possible adducts and fixed modifications
==============The decoy mode: could be one of the "adducts", "elements" or "isotope"
==============The pre-processing param
==============Set the parameters for image segmentation
==============Set the Score method for hi-resolution isotopic pattern matching
==============Summarise the protein and peptide features across the project the result can be found at the summary folder
==============The parameters for Cluster imaging. Specify the annotations of interest, the program will perform a case-insensitive search on the result file, extract the protein(s) of interest and plot them in the cluster imaging mode
4 Cores detected, 4 threads will be used for computing
1 files were selected and will be used for Searching
uniprotkb_proteome_UP000005640_AND_revi_2024_11_07.fasta was selected as database. Candidates will be generated through Proteomics mode
Found enzyme: trypsin
Found rule: ""
Found customized rule: ""
Candidate list has been loaded.
uniprotkb_proteome_UP000005640_AND_revi_2024_11_07.fasta was selected as database Spectrum intensity threshold: 0.50% mz tolerance: 5 ppm Segmentation method: spatialKMeans Manual segmentation def file: None Bypass spectrum generation: FALSE
Found rotation info
Loading raw image data for statistical analysis: 20241023-sharat-52059-dhb-500shot.imzML
Preparing image data for statistical analysis: 20241023-sharat-52059-dhb-500shot.imzML
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Warning message: “no pending processing steps to apply” Using image data: 20241023-sharat-52059-dhb-500shot.imzML
Segmentation in progress...
Performing forced peak alignment before segmentation...
preprocess$peakAlign$tolerance set as 5
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Error in data.frame(Component = 1:length(PCA_imdata@model[["sdev"]]), : no slot of name "model" for this object of class "PCA2" Traceback: