Mercurial > repos > galaxyp > cardinal_preprocessing
view macros.xml @ 4:141a9288be9c draft
planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/cardinal commit ecdc3a64aa245d80dbc5487b2bf10a85a43adc6d
author | galaxyp |
---|---|
date | Fri, 22 Mar 2019 08:12:42 -0400 |
parents | 1b875f0b8024 |
children | 5bf056c0354e |
line wrap: on
line source
<macros> <token name="@VERSION@">1.12.1</token> <xml name="requirements"> <requirements> <requirement type="package" version="@VERSION@">bioconductor-cardinal</requirement> <requirement type="package" version="3.5.1">r-base</requirement> <yield/> </requirements> </xml> <xml name="print_version"> <version_command><![CDATA[ echo $(R --version | grep version | grep -v GNU)", Cardinal version" $(R --vanilla --slave -e "library(Cardinal); cat(sessionInfo()\$otherPkgs\$Cardinal\$Version)" 2> /dev/null | grep -v -i "WARNING: ") ]]></version_command> </xml> <token name="@INPUT_LINKING@"><![CDATA[ #if $infile.ext == 'imzml' ln -s '${infile.extra_files_path}/imzml' infile.imzML && ln -s '${infile.extra_files_path}/ibd' infile.ibd && #elif $infile.ext == 'analyze75' ln -s '${infile.extra_files_path}/hdr' infile.hdr && ln -s '${infile.extra_files_path}/img' infile.img && ln -s '${infile.extra_files_path}/t2m' infile.t2m && #else ln -s $infile infile.RData && #end if ]]></token> <token name="@READING_MSIDATA@"><![CDATA[ ## importing MSI data files ## function to read RData files independent of filename loadRData <- function(fileName){ load(fileName) get(ls()[ls() != "fileName"]) } #if $infile.ext == 'imzml' #if str($processed_cond.processed_file) == "processed": msidata <- readImzML('infile', mass.accuracy=$processed_cond.accuracy, units.accuracy = "$processed_cond.units", attach.only=TRUE) centroided(msidata) = $centroids #else msidata <- readImzML('infile', attach.only=TRUE) centroided(msidata) = $centroids #end if #elif $infile.ext == 'analyze75' msidata = readAnalyze('infile', attach.only=TRUE) centroided(msidata) = $centroids #else msidata = loadRData('infile.RData') #end if ]]></token> <token name="@DATA_PROPERTIES@"><![CDATA[ ## Number of features (mz) maxfeatures = length(features(msidata)) ## Range mz minmz = round(min(mz(msidata)), digits=2) maxmz = round(max(mz(msidata)), digits=2) ## Number of spectra (pixels) pixelcount = length(pixels(msidata)) ## Range x coordinates minimumx = min(coord(msidata)[,1]) maximumx = max(coord(msidata)[,1]) ## Range y coordinates minimumy = min(coord(msidata)[,2]) maximumy = max(coord(msidata)[,2]) properties = c("Number of m/z features", "Range of m/z values", "Number of pixels", "Range of x coordinates", "Range of y coordinates") values = c(paste0(maxfeatures), paste0(minmz, " - ", maxmz), paste0(pixelcount), paste0(minimumx, " - ", maximumx), paste0(minimumy, " - ", maximumy)) property_df = data.frame(properties, values) ]]></token> <token name="@READING_MSIDATA_INRAM@"><![CDATA[ ## importing MSI data files ## function to read RData files independent of filename loadRData <- function(fileName){ load(fileName) get(ls()[ls() != "fileName"]) } #if $infile.ext == 'imzml' #if str($processed_cond.processed_file) == "processed": msidata <- readImzML('infile', mass.accuracy=$processed_cond.accuracy, units.accuracy = "$processed_cond.units") centroided(msidata) = $centroids iData(msidata) = iData(msidata)[] #else msidata <- readImzML('infile') centroided(msidata) = $centroids #end if #elif $infile.ext == 'analyze75' msidata = readAnalyze('infile') centroided(msidata) = $centroids #else msidata = loadRData('infile.RData') #end if ]]></token> <token name="@DATA_PROPERTIES_INRAM@"><![CDATA[ ########################### QC numbers ######################## ## including intensity calculations which need data in RAM ## Number of features (mz) maxfeatures = length(features(msidata)) ## Range mz minmz = round(min(mz(msidata)), digits=2) maxmz = round(max(mz(msidata)), digits=2) ## Number of spectra (pixels) pixelcount = length(pixels(msidata)) ## Range x coordinates minimumx = min(coord(msidata)[,1]) maximumx = max(coord(msidata)[,1]) ## Range y coordinates minimumy = min(coord(msidata)[,2]) maximumy = max(coord(msidata)[,2]) ## Range of intensities minint = round(min(spectra(msidata), na.rm=TRUE), digits=2) maxint = round(max(spectra(msidata), na.rm=TRUE), digits=2) ## Number of intensities > 0, for if conditions npeaks= sum(spectra(msidata)>0, na.rm=TRUE) ## Number of NA in spectra matrix NAcount = sum(is.na(spectra(msidata))) ## Number of NA in spectra matrix infcount = sum(is.infinite(spectra(msidata))) ## Number of duplicated coordinates dupl_coord = sum(duplicated(coord(msidata))) properties = c("Number of m/z features", "Range of m/z values", "Number of pixels", "Range of x coordinates", "Range of y coordinates", "Range of intensities", "Number of NA intensities", "Number of Inf intensities", "Number of duplicated coordinates") values = c(paste0(maxfeatures), paste0(minmz, " - ", maxmz), paste0(pixelcount), paste0(minimumx, " - ", maximumx), paste0(minimumy, " - ", maximumy), paste0(minint, " - ", maxint), paste0(NAcount), paste0(infcount), paste0(dupl_coord)) property_df = data.frame(properties, values) ]]></token> <token name="@CARDINAL_DESCRIPTION@"><![CDATA[ Cardinal is an R package that implements statistical & computational tools for analyzing mass spectrometry imaging datasets. `More information on Cardinal <http://cardinalmsi.org/>`_ ]]></token> <token name="@MSIDATA_INPUT_DESCRIPTION@"><![CDATA[ **Input data** - MSI data: 3 types of input data can be used: - imzml file (upload imzml and ibd file via the "composite" function) `Introduction to the imzml format <https://ms-imaging.org/wp/imzml/>`_ - Analyze7.5 (upload hdr, img and t2m file via the "composite" function) - Cardinal "MSImageSet" data saved as .RData ]]></token> <token name="@MZ_TABULAR_INPUT_DESCRIPTION@"><![CDATA[ - Optional tabular file with m/z values: - One column with numeric m/z values (without empty fields or letters) - The file is allowed to have any column names as header (in this case set "Tabular file contains a header line" to yes) - m/z features outside the m/z range of the input file are ignored :: m/z 100.0 100.01 100.02 ... ... ]]></token> <token name="@MZ_2COLS_TABULAR_INPUT_DESCRIPTION@"><![CDATA[ - Tabular file with m/z values: - One column with numeric m/z values (without empty fields or letters), another column with names for the m/z (m/z column can also be used as name) - The file is allowed to have any column names as header (in this case set "Tabular file contains a header line" to yes) - m/z features outside the m/z range of the input file are ignored :: m/z name 100.0 analyte1 100.01 analyte2 100.02 analyte3 ... ... ]]></token> <token name="@SPECTRA_TABULAR_INPUT_DESCRIPTION@"><![CDATA[ - Optional file with pixel coordinates and annotation: - Tabular file: One column with x values, one column with y values and one column with annotations - The file is allowed to have any column names as header (in this case set "Tabular file contains a header line" to yes) - Pixel with coordinates outside the coordinates of the input file are ignored :: x_coord y_coord annotation 1 1 healthy 2 1 healthy 3 1 disease ... ... ]]></token> <xml name="reading_msidata"> <param name="infile" type="data" format="imzml,rdata,analyze75" label="MSI data" help="Input file as imzML (composite upload), Analyze7.5 (composite upload) or Cardinal MSImageSet saved as RData (regular upload)"/> <param name="centroids" type="boolean" label="Centroided input" help="Choose Yes if peak detection has already been done." truevalue="TRUE" falsevalue="FALSE"/> <conditional name="processed_cond"> <param name="processed_file" type="select" label="Processed imzML file" help="Choose no if your input is an Analyze7.5 or continuous imzML file"> <option value="no_processed" selected="True">no</option> <option value="processed">yes</option> </param> <when value="no_processed"/> <when value="processed"> <param name="accuracy" type="float" value="50" label="Mass accuracy to which the m/z values will be binned" help="This should be set to the native accuracy of the mass spectrometer, if known"/> <param name="units" display="radio" type="select" label="Unit of the mass accuracy" help="either m/z or ppm"> <option value="mz" >mz</option> <option value="ppm" selected="True" >ppm</option> </param> </when> </conditional> </xml> <xml name="pdf_filename"> <param name="filename" type="text" value="" label="Title" help="Will appear in the pdf output, if nothing given it will take the dataset name"> <sanitizer invalid_char=""> <valid initial="string.ascii_letters,string.digits"> <add value="_"/> <add value=" "/> </valid> </sanitizer> </param> </xml> <xml name="sanitizer_multiple_digits"> <sanitizer invalid_char=""> <valid initial="string.digits"> <add value=":" /> <add value="," /> </valid> </sanitizer> </xml> <xml name="reading_1_column_mz_tabular" token_label="Tabular file with m/z features"> <param name="mz_tabular" type="data" format="tabular" label="@LABEL@" help="Only numeric m/z values are allowed"/> <param name="feature_column" data_ref="mz_tabular" label="Column with features" type="data_column"/> <param name="feature_header" type="boolean" label="Tabular file contains a header line" truevalue="TRUE" falsevalue="FALSE"/> </xml> <xml name="reading_2_column_mz_tabular" token_optional="false"> <param name="calibrant_file" type="data" optional="@OPTIONAL@" format="tabular" label="m/z of interest (e.g. internal Calibrants)" help="one column with m/z values, optional second column with names (m/z values can also be selected as name)"/> <param name="mz_column" data_ref="calibrant_file" optional="@OPTIONAL@" label="Column with m/z values" type="data_column"/> <param name="name_column" data_ref="calibrant_file" optional="@OPTIONAL@" label="Column with name of m/z values" type="data_column"/> <param name="calibrant_header" type="boolean" optional="@OPTIONAL@" label="Tabular file contains a header line" truevalue="TRUE" falsevalue="FALSE"/> </xml> <xml name="reading_pixel_annotations"> <param name="annotation_file" type="data" format="tabular" label="Tabular file with pixel coordinates and annotation" help="Tabular file with three columns: x values, y values and pixel annotations"/> <param name="column_x" data_ref="annotation_file" label="Column with x values" type="data_column"/> <param name="column_y" data_ref="annotation_file" label="Column with y values" type="data_column"/> <param name="column_names" data_ref="annotation_file" label="Column with pixel annotations" type="data_column"/> <param name="tabular_header" type="boolean" label="Tabular file contains a header line" truevalue="TRUE" falsevalue="FALSE"/> </xml> <xml name="citations"> <citations> <citation type="doi">10.1093/bioinformatics/btv146</citation> </citations> </xml> <xml name="infile_analyze75"> <param name="infile" value="" ftype="analyze75"> <composite_data value="Analyze75.hdr"/> <composite_data value="Analyze75.img"/> <composite_data value="Analyze75.t2m"/> </param> </xml> <xml name="infile_imzml"> <param name="infile" value="" ftype="imzml"> <composite_data value="Example_Continuous.imzML"/> <composite_data value="Example_Continuous.ibd"/> </param> </xml> </macros>