annotate ChipSeqRatioDef.xml @ 25:5dba804e6884 draft

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1 <tool id="chip_seq_ratio_1" name="ChIP-Seq Mapper" version="1.1.1.3">
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2 <stdio>
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3 <exit_code range="1:" level="fatal" description="Error"/>
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4 </stdio>
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5 <description></description>
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6 <requirements>
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7 <requirement type="package">r-base64enc</requirement>
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8 <requirement type="package">r-r2html</requirement>
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9 <requirement type="package">blast</requirement>
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10 <!-- <requirement type="package">chip_seq_ration</requirement> -->
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11 </requirements>
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12 <required_files>
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13 <include type="literal" path="ChipSeqRatioAnalysis.py"/>
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14 <include type="literal" path="ChipSeqRatioAnalysis.R"/>
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15 </required_files>
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16 <command>
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17 python '$__tool_directory__'/ChipSeqRatioAnalysis.py
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18 --ChipSeq=${ChipFile}
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19 --InputSeq=${InputFile}
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20 --Contigs=${ContigFile}
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21 --output=${OutputFile}
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22 --html=${ReportFile}
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23 --max_cl=${MaxCl}
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24 --bitscore=$bitscore
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25 --nproc=16
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26 </command>
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28 <inputs>
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29 <param name="ChipFile" label="Chip reads" type="data" format="fasta" help="Reads in FASTA format"/>
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30 <param name="InputFile" label="Input reads" type="data" format="fasta" help="Reads in FASTA format"/>
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31 <param name="ContigFile" label="Reference - contig sequences" type="data" format="fasta"
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32 help="Contigs from RepeatExplorer clustering (the file &quot;contigs.fasta&quot;)"/>
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33 <param name="MaxCl" label="Number of top clusters to be shown in graph" type="integer" value="200"/>
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34 <param name="bitscore" label="Bit score threshold" type="integer" value="50" help="Similarity hits with lower bit score will not be used for ChIP/Input ratio calculation"/>
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35 </inputs>
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36 <outputs>
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37 <data name="OutputFile" format="tabular"
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38 label="csv table from ChIP-Seq-Mapper on datasets ${InputFile.hid} (Input) ${ChipFile.hid} (ChIP) and ${ContigFile.hid} (reference)"/>
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40 <data name="ReportFile" format="html"
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41 label="HTML report from ChIP-Seq-Mapper on datasets ${InputFile.hid} (Input) ${ChipFile.hid} (ChIP) and ${ContigFile.hid} (reference)"/>
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42 </outputs>
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43
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44 <help>
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45 **What it does**
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46
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47 The ChIP-seq Mapper evaluates the enrichment of repetitive sequences in sequencing data from chromatin
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48 immunoprecipitation experiments, using repeats identified by RepeatExplorer as the reference. The tool
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49 performs BLASTN similarity search of the read sequences to the reference,
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50 and the reads producing hits that passed the user-specified similarity threshold are assigned to the
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51 repeat clusters. The assignment is made to the cluster that produced the best similarity hit, and every
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52 read is assigned to only a single cluster. Following read mapping, the numbers of reads from the
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53 INPUT and ChIP samples are evaluated, and ChIP/INPUT ratios of the normalized read counts are reported
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54 for individual clusters.
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55 ChIP and INPUT reads should be of uniform lengths of at least 40 nt. The bit score threshold value should be
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56 adjusted based on the length of the analyzed reads (the value equal to the read length is recommended for a start).
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57 This method was first used in (`Neumann et al. 2012`__) for
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58 identification of repetitive sequences associated with centromeres:
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61 `PLoS Genet. Epub 2012 Jun 21. Stretching the rules: monocentric chromosomes with multiple centromere domains. Neumann P, Navrátilová A, Schroeder-Reiter E, Koblížková A, Steinbauerová V, Chocholová E, Novák P, Wanner G, Macas J.`__.
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63 .. __: http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1002777
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64 .. __: http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1002777
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65
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66 </help>
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67
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68 </tool>
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