msi_ion_images: msi_ion_images.xml comparison

comparison msi_ion_images.xml @ 2:b2ad54eabcca draft

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_ion_images commit ed7d3e6f1a09c78c8f71cc1bdc1a20249767f646

author	galaxyp
date	Sun, 11 Mar 2018 10:38:24 -0400
parents	845fee459824
children	616b98c235fb

comparison

equal deleted inserted replaced

-:845fee459824
+:b2ad54eabcca
-<tool id="mass_spectrometry_imaging_ion_images" name="MSI ion images" version="1.7.0.1">
+<tool id="mass_spectrometry_imaging_ion_images" name="MSI ion images" version="1.7.0.2">
 <description>
 mass spectrometry imaging heatmaps
 </description>
 <requirements>
 <requirement type="package" version="1.7.0">bioconductor-cardinal</requirement>
 peakpickinginfo='FALSE'
 } else {
 peakpickinginfo=processinginfo@peakPicking
 }
-#if $massfile:
-### Read tabular file with peptide masses for plots and heatmap images:
+### Read tabular file with peptide masses for heatmap images:
-input_list = read.delim("$massfile", header = FALSE, stringsAsFactors = FALSE)
-if (ncol(input_list) == 1)
+input_list = read.delim("$massfile", header = FALSE, stringsAsFactors = FALSE)
-{
+if (ncol(input_list) == 1)
-input_list = cbind(input_list, input_list)
+{
-}
+input_list = cbind(input_list, input_list)
-### calculate how many input masses are valid:
+}
-inputmasses = input_list[input_list[,1]>minmz & input_list[,1]<maxmz,]
+### calculate how many input masses are valid:
-inputmz = inputmasses[,1]
+inputmasses = input_list[input_list[,1]>minmz & input_list[,1]<maxmz,]
-inputnames = inputmasses[,2]
-#else
+inputmz = inputmasses[,1]
-input_list = data.frame(0, 0)
+inputnames = inputmasses[,2]
-inputmz = 0
-#end if
+if (nrow(input_list) == 1)
+{
+countpixels = sum(spectra(msidata)[features(msidata, mz = inputmz), ] >0)
-countpixels = rowSums(spectra(msidata)[features(msidata, mz=inputmz),]>0)
+}else {
+countpixels = rowSums(spectra(msidata)[features(msidata, mz=inputmz),] >0)
+}
 percentpixels = round(countpixels/pixelcount*100, digits=1)
 valuesdataframe = cbind(inputmz, cbind(countpixels, percentpixels))
 write.table(valuesdataframe, file="$pixel_count", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
 "Normalization",
 "Smoothing",
 "Baseline reduction",
 "Peak picking",
 "Centroided",
-paste0("# valid masses in ", "$massfile.display_name"))
+paste0("# valid masses in \n", "$massfile.display_name"))
 values = c(paste0(maxfeatures),
 paste0(minmz, " - ", maxmz),
 paste0(pixelcount),
 paste0(minimumx, " - ", maximumx),
 ]]></configfile>
 </configfiles>
 <inputs>
 <param name="infile" type="data" format="imzml,rdata,analyze75" label="Inputfile as imzML, Analyze7.5 or Cardinal MSImageSet saved as RData"
 help="Upload composite datatype imzml (ibd+imzML) or analyze75 (hdr+img+t2m) or regular upload .RData (Cardinal MSImageSet)"/>
-<param name="filename" type="text" value="" label="Title" help="will appear in the quality report. If nothing given it will take the dataset name."/>
+<param name="filename" type="text" value="" label="Title" help="will appear in the quality report. If nothing given it will take the dataset name"/>
 <param name="massfile" type="data" format="tabular" label="Text file with masses and names"
 help="first column mass (m/z), second column mass name, tab separated file"/>
-<param name="image_contrast" type="select" label="Select a contrast enhancement function for the heatmap images." help="The 'histogram' equalization method flatterns the distribution of intensities. The hotspot 'suppression' method uses thresholding to reduce the intensities of hotspots">
+<param name="image_contrast" type="select" label="Select a contrast enhancement function for the heatmap images" help="The 'histogram' equalization method flatterns the distribution of intensities. The hotspot 'suppression' method uses thresholding to reduce the intensities of hotspots">
 <option value="none" selected="True">none</option>
 <option value="suppression">suppression</option>
 <option value="histogram">histogram</option>
 </param>
-<param name="image_smoothing" type="select" label="Select an image smoothing function for the heatmap images." help="The 'gaussian' smoothing method smooths images with a simple gaussian kernel. The 'adaptive' method uses bilateral filtering to preserve edges.">
+<param name="image_smoothing" type="select" label="Select an image smoothing function for the heatmap images" help="The 'gaussian' smoothing method smooths images with a simple gaussian kernel. The 'adaptive' method uses bilateral filtering to preserve edges">
 <option value="none" selected="True">none</option>
 <option value="gaussian">gaussian</option>
 <option value="adaptive">adaptive</option>
 </param>
 <param name="plusminus_dalton" value="0.25" type="float" label="Mass range" help="plusminus mass window in Dalton"/>
 <param name="massfile" value="inputpeptides.tabular" ftype="tabular"/>
 <param name="plusminus_dalton" value="0.25"/>
 <param name="filename" value="Testfile_imzml"/>
 <param name="image_contrast" value="histogram"/>
 <output name="plots" file="Heatmaps_imzml.pdf" compare="sim_size" delta="20000"/>
+<output name="pixel_count" file="tabular_imzml.tabular"/>
 </test>
 <test>
 <param name="infile" value="" ftype="analyze75">
 <composite_data value="Analyze75.hdr"/>
 <composite_data value="Analyze75.img"/>
 <composite_data value="Analyze75.t2m"/>
 <param name="massfile" value="inputpeptides2.tabular" ftype="tabular"/>
 <param name="plusminus_dalton" value="0.5"/>
 <param name="filename" value="Testfile_analyze75"/>
 <param name="image_smoothing" value="gaussian"/>
 <output name="plots" file="Heatmaps_analyze75.pdf" compare="sim_size" delta="20000"/>
+<output name="pixel_count" file="tabular_analyze75.tabular"/>
 </test>
 <test>
 <param name="infile" value="preprocessing_results1.RData" ftype="rdata"/>
 <param name="massfile" value="inputpeptides.tabular" ftype="tabular"/>
 <param name="plusminus_dalton" value="0.1"/>
 <param name="filename" value="Testfile_rdata"/>
 <output name="plots" file="Heatmaps_rdata.pdf" compare="sim_size" delta="20000"/>
+<output name="pixel_count" file="tabular_rdata.tabular"/>
 </test>
 <test>
 <param name="infile" value="LM8_file16.rdata" ftype="rdata"/>
 <param name="massfile" value="inputpeptides2.tabular" ftype="tabular"/>
 <param name="plusminus_dalton" value="0.1"/>
 <param name="filename" value="Testfile_rdata"/>
 <output name="plots" file="Heatmaps_LM8_file16.pdf" compare="sim_size" delta="20000"/>
+<output name="pixel_count" file="tabular_LM8file16.tabular"/>
 </test>
 </tests>
 <help><![CDATA[
 Heatmaps for different masses in mass-spectrometry imaging data as pdf output.
 - Analyze7.5 (upload hdr, img and t2m file via the "composite" function)
 - Cardinal "MSImageSet" data (with variable name "msidata", saved as .RData)
 tabular file with masses:
 - tab separated file (.tabular), datatype in Galaxy must be tabular (if Galaxy auto-detection was wrong, datatype can be changed by pressing the pen button)
+- first column must contain masses (separate point numbers by point, not comma)
+- optionally a second column with names for the masses can be provided
 - no empty fields or letters are allowed (tool crashes with empty fields and a single letter prohibits generation of images)
-- separate point numbers by point (a single number with comma prohibits generation of images)
 Trouble shooting:
 - no heatmaps are plotted when tabular file contains letters or point numbers with commas or when the input MSI file had no intensities > 0
 - contrast enhance functions need masses with intensities > 0 in about 1.5% of all pixels - tool crashes when contrast enhance is used on too few intensities

Mercurial > repos > galaxyp > msi_ion_images

comparison msi_ion_images.xml @ 2:b2ad54eabcca draft