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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/metagenomeseq commit c7e28b83e8636a5d11010bea9997a449be1d48e0
author | iuc |
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date | Wed, 12 Apr 2017 17:19:48 -0400 |
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<tool id="metagenomeseq_normalizaton" name="metagenomeSeq Normalization" version="1.16.0-0.0.1"> <description>Cumulative sum scaling</description> <requirements> <requirement type="package" version="1.16.0">bioconductor-metagenomeseq</requirement> <requirement type="package" version="1.2.0">bioconductor-biomformat</requirement> </requirements> <version_command><![CDATA[Rscript -e 'suppressMessages(library("metagenomeSeq"));cat(toString(packageVersion("metagenomeSeq")))']]></version_command> <command detect_errors="exit_code"><![CDATA[ #if "output_r_script" in str( $include_outputs ).split( "," ): cp '${metagenomeseq_normalization_script}' '${output_r_script}' && #end if Rscript '${metagenomeseq_normalization_script}' ]]> </command> <configfiles> <configfile name="metagenomeseq_normalization_script"><![CDATA[#!/usr/bin/env RScript #set $include_files = str( $include_outputs ).split( "," ) library(metagenomeSeq) library(biomformat) #if $input_abundance_file.is_of_type( 'biom1' ): inputMRe = biom2MRexperiment( biomformat::read_biom( "${input_abundance_file}" ) ) #else: ##inputMRe = newMRexperiment( counts, phenoData = NULL, featureData = NULL, libSize = NULL, normFactors = NULL) #raise "Not yet implemented" #end if #if str( $percentile_type.percentile_type_selector ) == 'cumNormStat': p = cumNormStat( inputMRe, qFlag = ${percentile_type.qFlag}, rel = ${percentile_type.rel} ) #elif str( $percentile_type.percentile_type_selector ) == 'cumNormStatFast': p = cumNormStatFast( inputMRe, rel = ${percentile_type.rel} ) #else: p = ${percentile_type.raw_value} #end if inputMRe = cumNorm(inputMRe, p = p ) #if "output_tabular" in $include_files: mat = MRcounts(inputMRe, norm = TRUE, log = ${log2}, sl = ${sl}) exportMat(mat, file = "${output_tabular_dataset}") #end if #if "output_biom" in $include_files: biomformat::write_biom( MRexperiment2biom(inputMRe, id = NULL, norm = TRUE, log = ${log2}, sl = ${sl}, qiimeVersion = TRUE), "${output_biom_dataset}" ) #end if #if "output_stats" in $include_files: exportStats(inputMRe, p = p, file = "${output_stats}") #end if ]]> </configfile> </configfiles> <inputs> <param name="input_abundance_file" type="data" format="biom1" label="Input Matrix" help="BIOM format"/> <conditional name="percentile_type"> <param name="percentile_type_selector" type="select" label="Percentile for which to scale data"> <option value="cumNormStat" selected="True">cumNormStat</option> <option value="cumNormStatFast" selected="False">cumNormStatFast</option> <option value="raw" selected="False">Raw</option> </param> <when value="cumNormStat"> <param name="qFlag" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="True" label="qFlag" help="Flag to either calculate the proper percentile using R's step-wise quantile function or approximate function."/> <param name="rel" type="float" value="0.1" label="rel" help="Cutoff for the relative difference from one median difference from the reference to the next"/> </when> <when value="cumNormStatFast"> <param name="rel" type="float" value="0.1" label="rel" help="Cutoff for the relative difference from one median difference from the reference to the next"/> </when> <when value="raw"> <param name="raw_value" type="float" value=".80" label="Percentile" help="Manual Percentile"/> </when> </conditional> <param name="log2" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="False" label="Log2 transform scaling" help=""/> <param name="sl" type="integer" value="1000" label="The value to scale by." help="(default=1000)"/> <param name="include_outputs" type="select" multiple="True" label="Datasets to create"> <option value="output_tabular" selected="True">Normalized Tabular Matrix</option> <!-- <option value="output_biom" selected="True">Normalized BIOM</option> --> <option value="output_stats" selected="True">Simple Statistics</option> <option value="output_r_script" selected="False">R script</option> </param> </inputs> <outputs> <!-- <data format="biom1" name="output_biom_dataset" label="${tool.name} on ${on_string} (BIOM1)"> <filter>"output_biom" in include_outputs</filter> </data> --> <data format="tabular" name="output_tabular_dataset" label="${tool.name} on ${on_string} (Tabular)"> <filter>"output_tabular" in include_outputs</filter> </data> <data format="tabular" name="output_stats" label="${tool.name} on ${on_string} (Simple Statistics)"> <filter>"output_stats" in include_outputs</filter> </data> <data format="txt" name="output_r_script" label="${tool.name} on ${on_string} (Rscript)"> <filter>"output_r_script" in include_outputs</filter> </data> </outputs> <tests> <test> <param name="input_abundance_file" value="input_1.biom1" ftype="biom1"/> <conditional name="percentile_type"> <param name="percentile_type_selector" value="cumNormStat"/> <param name="qFlag" value="TRUE"/> <param name="rel" value=".1"/> </conditional> <param name="log2" value="FALSE"/> <param name="sl" value="1000"/> <output name="output_tabular_dataset"> <assert_contents> <has_text_matching expression="SAMPLE_2" /> </assert_contents> </output> </test> </tests> <help><![CDATA[ metagenomeSeq Cumulative sum scaling ==================================== Info ---- :: Cumulative sum scaling based upon percentile selection. You can manually specificy the percentile or calculate it using cumNormStat or cumNormStatFast. Inputs ------ :: Requires a BIOM formatted file for input. Outputs ------- :: Creates a normalized and scaled output abundance matrix in Tabular format. Additionally can create simple statistics and the RScript. ]]></help> <citations> <citation type="doi">10.1038/nmeth.2658</citation> </citations> </tool>