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1 <tool id="minfi_ppquantile" name="Minfi Preprocess Quantile" version="@MINFI_VERSION@">
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2 <description>implements stratified quantile normalization preprocessing</description>
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3 <macros>
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4 <import>macros.xml</import>
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5 </macros>
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6 <expand macro="requirements">
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7 <requirement type="package" version="0.6.0">bioconductor-illuminahumanmethylation450kanno.ilmn12.hg19</requirement>
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8 </expand>
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9 <command detect_errors="exit_code">
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10 <![CDATA[
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11 Rscript '$minfi_pp_script'
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12 ]]>
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13 </command>
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14 <configfiles>
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15 <configfile name="minfi_pp_script"><![CDATA[
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16 require("minfi", quietly = TRUE)
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17 RGSet <- get(load('$rgset'))
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18
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19 GRSet <- preprocessQuantile(RGSet, fixOutliers = TRUE,
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20 removeBadSamples = TRUE, badSampleCutoff = 10.5,
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21 quantileNormalize = TRUE, stratified = TRUE,
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22 mergeManifest = FALSE, sex = NULL)
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23
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24 save(GRSet,file = '$grset')
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25
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26 ]]>
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27 </configfile>
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28 </configfiles>
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29 <inputs>
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30 <param type="data" name="rgset" format="rdata" label="RGChannelSet" help="These classes represents raw (unprocessed) data from a two color micro array; specifically an Illumina methylation array." />
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31 </inputs>
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32 <outputs>
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33 <data name="grset" format="rdata" label="GenomicRatioSet"/>
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34 </outputs>
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35 <tests>
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36 <test>
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37 <param name="rgset" value="RGChannelSet.rdata"/>
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38 <output name="grset" file="QuantileGenomicRatioSet.rdata"/>
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39 </test>
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40 </tests>
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41 <help><![CDATA[
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42 The normalization procedure is applied to the Meth and Unmeth intensities separately. The distribution of type I and type II signals is forced to be the same by first quantile normalizing the type II probes across samples and then interpolating a reference distribution to which we normalize the type I probes. Since probe types and probe regions are confounded and we know that DNAm distributions vary across regions we stratify the probes by region before applying this interpolation.
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43 ]]></help>
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44 <expand macro="citations" />
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45 </tool>
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46
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