msi_ion_images: msi_ion_images.xml comparison

comparison msi_ion_images.xml @ 1:845fee459824 draft

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_ion_images commit edbf2a6cb50fb04d0db56a7557a64e3bb7a0806a

author	galaxyp
date	Thu, 01 Mar 2018 08:25:18 -0500
parents	385e8a4accd9
children	b2ad54eabcca

comparison

equal deleted inserted replaced

-:385e8a4accd9
+:845fee459824
-<tool id="mass_spectrometry_imaging_ion_images" name="MSI ion images" version="1.7.0">
+<tool id="mass_spectrometry_imaging_ion_images" name="MSI ion images" version="1.7.0.1">
 <description>
 mass spectrometry imaging heatmaps
 </description>
 <requirements>
 <requirement type="package" version="1.7.0">bioconductor-cardinal</requirement>
 library(lattice)
 ## Read MALDI Imaging dataset
 #if $infile.ext == 'imzml'
-msidata <- readMSIData('infile.imzML')
+msidata = readMSIData('infile.imzML')
 #elif $infile.ext == 'analyze75'
-msidata <- readMSIData('infile.hdr')
+msidata = readMSIData('infile.hdr')
 #else
 load('infile.RData')
 #end if
-#if $massfile:
-### Read tabular file with peptide masses for plots and heatmap images:
-input_list = read.delim("$massfile", header = FALSE, na.strings=c("","NA", "#NUM!", "#ZAHL!"), stringsAsFactors = FALSE)
-if (ncol(input_list) == 1)
-{
-input_list = cbind(input_list, input_list)
-}
-#else
-input_list = data.frame(0, 0)
-#end if
-colnames(input_list)[1:2] = c("mz", "name")
 ###################################### file properties in numbers ######################
 ## Number of features (mz)
 maxfeatures = length(features(msidata))
 peakpickinginfo='FALSE'
 } else {
 peakpickinginfo=processinginfo@peakPicking
 }
-### calculate how many input masses are valid:
+#if $massfile:
-inputmasses = input_list[input_list[,1]>minmz & input_list[,1]<maxmz,]
+### Read tabular file with peptide masses for plots and heatmap images:
+input_list = read.delim("$massfile", header = FALSE, stringsAsFactors = FALSE)
-inputmz = inputmasses[,1]
+if (ncol(input_list) == 1)
-inputnames = inputmasses[,2]
+{
+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,]
+inputmz = inputmasses[,1]
+inputnames = inputmasses[,2]
+#else
+input_list = data.frame(0, 0)
+inputmz = 0
+#end if
+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="$pixel_count", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
+colnames(input_list)[1:2] = c("mz", "name")
 properties = c("Number of mz features",
 "Range of mz values [Da]",
 "Number of pixels",
 "Range of x coordinates",
 "Range of y coordinates",
 "Normalization",
 "Smoothing",
 "Baseline reduction",
 "Peak picking",
 "Centroided",
-paste0("# valid masses in ", "$filename"))
+paste0("# valid masses in ", "$massfile.display_name"))
 values = c(paste0(maxfeatures),
 paste0(minmz, " - ", maxmz),
 paste0(pixelcount),
 paste0(minimumx, " - ", maximumx),
 paste0(centroidedinfo),
 paste0(length(inputmz), "/", length(input_list[,1])))
 property_df = data.frame(properties, values)
 ######################################## PDF #############################################
 ##########################################################################################
 ##########################################################################################
 grid.table(property_df, rows= NULL)
 if (npeaks > 0)
 {
 if (length(inputmz) != 0)
 {
 for (mass in 1:length(inputmz))
 {
-print(image(msidata, mz=inputmz[mass], strip = strip.custom(bg="lightgrey", par.strip.text=list(col="black", cex=.9)),
-lattice=TRUE, ylim = c(maximumy+1,minimumy-1), plusminus = $plusminusinDalton, contrast.enhance = "histogram",
-main= paste0(mass, ") ", inputnames[mass], " (", round(inputmz[mass], digits = 2)," ± ", $plusminusinDalton, " Da)")))
+print(image(msidata, mz=inputmz[mass], strip = strip.custom(bg="lightgrey", par.strip.text=list(col="black", cex=.9)),
+lattice=TRUE, ylim = c(maximumy+1,minimumy-1), plusminus = $plusminus_dalton, contrast.enhance = "$image_contrast", smooth.image = "$image_smoothing",
+main= paste0(mass, ") ", inputnames[mass], " (", round(inputmz[mass], digits = 2)," ± ", $plusminus_dalton, " Da)")))
 }
-} else {print("The input masses were outside the mass range")}
+} else {print("The input masses were invalid")}
 dev.off()
 }else{
 print("inputfile has no intensities > 0")
 </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="massfile" type="data" optional="true" format="tabular" label="Text file with masses and names"
+<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="plusminusinDalton" value="0.25" type="float" label="Mass range" help="plusminus mass window in Dalton"/>
+<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.">
+<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"/>
 </inputs>
 <outputs>
 <data format="pdf" name="plots" from_work_dir="heatmaps.pdf" label = "${tool.name} on $infile.display_name"/>
+<data format="tabular" name="pixel_count" label="Number of pixels per mz with intensity"/>
 </outputs>
 <tests>
 <test>
 <param name="infile" value="" ftype="imzml">
 <composite_data value="Example_Continuous.imzML"/>
 <composite_data value="Example_Continuous.ibd"/>
 </param>
-<param name="massfile" value="inputpeptides.csv" ftype="tabular"/>
+<param name="massfile" value="inputpeptides.tabular" ftype="tabular"/>
-<param name="plusminusinDalton" value="0.25"/>
+<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"/>
 </test>
 <test>
 <param name="infile" value="" ftype="analyze75">
 <composite_data value="Analyze75.hdr"/>
 <composite_data value="Analyze75.img"/>
 <composite_data value="Analyze75.t2m"/>
 </param>
-<param name="massfile" value="inputpeptides.txt" ftype="tabular"/>
+<param name="massfile" value="inputpeptides2.tabular" ftype="tabular"/>
-<param name="plusminusinDalton" value="0.5"/>
+<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"/>
 </test>
 <test>
 <param name="infile" value="preprocessing_results1.RData" ftype="rdata"/>
-<param name="massfile" value="inputpeptides.csv" ftype="tabular"/>
+<param name="massfile" value="inputpeptides.tabular" ftype="tabular"/>
-<param name="plusminusinDalton" value="0.1"/>
+<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"/>
 </test>
 <test>
 <param name="infile" value="LM8_file16.rdata" ftype="rdata"/>
-<param name="massfile" value="inputpeptides.txt" ftype="tabular"/>
+<param name="massfile" value="inputpeptides2.tabular" ftype="tabular"/>
-<param name="plusminusinDalton" value="0.1"/>
+<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"/>
 </test>
 </tests>
 <help><![CDATA[
-Heatmaps for different ion masses in mass-spectrometry imaging data.
+Heatmaps for different masses in mass-spectrometry imaging data as pdf output.
-Input data: 3 types of input data can be used:
+Input data:
+3 types of mass-spectrometry imaging data can be used:
 - imzml file (upload imzml and ibd file via the "composite" function) `Introduction to the imzml format <http://ms-imaging.org/wp/introduction/>`_
 - Analyze7.5 (upload hdr, img and t2m file via the "composite" function)
 - Cardinal "MSImageSet" data (with variable name "msidata", saved as .RData)
-The output of this tool contains heatmaps for every ion mass of interest as pdf.
+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)
+- 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
 ]]>
 </help>
 <citations>
 <citation type="doi">10.1093/bioinformatics/btv146</citation>

Mercurial > repos > galaxyp > msi_ion_images

comparison msi_ion_images.xml @ 1:845fee459824 draft