annotate predict/predict_RNAs.xml @ 42:128fcc5aedde draft

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<tool id="predict_pipeline" name="RNA structure prediction" version="1.0">
	<description></description>
	<command interpreter="python">predict_RNAs.py $rna_list $reference_file $reactivity_file $output </command>
        <requirements>
                <requirement type="package" version="1.61">biopython</requirement>
                <requirement type="package" version="1.7">numpy</requirement>
                <requirement type="package" version="1.2.1">matplotlib</requirement>
        </requirements>
	<inputs>
        <param name="rna_list" type="data" format="txt" label="List of RNA ids to predict"/>
        <param name="reference_file" type="data" format="fasta" label="Reference genome/transcriptome"/>
        <param name="reactivity_file" type="data" optional = "true" label="Reactivity"/>
	
	</inputs>
	<outputs>
		<data name="output" format=".tgz"/>
	</outputs>
    <tests>
        <test>
            <param name="rna_list" value="id_list_test.txt" />
	        <param name="reference_file" value="cdna.txt" />
            <param name="reactivity_file" value="mRNA_react_test2.txt" />
	        <output name="output" file="structures.out" />
        </test>
    </tests>
	<help>


**TIPS**:

-----

**Input**:

* 1. A file with transcript Ids (Max num. 20), (each ID one line)
* 2. Reference file (fasta) used to map the reads
* [Optional]:
* 1. A reactivity file with structural reactivity for each nucleotide on the sequence provided

-----

**Output**:

* 1. .ct files with predicted RNA structures [transciptID.ct]
* 2. .ps files which depict the predicted RNA structures [[transciptID.ps]
* [Optional]
* 3. .png files that shows the distribution of the reactivity of each nucleotide on the transcripts of interest. [transciptID.png]
* 4. A .txt file that includes the reactivities of all the nucleotides on the transcripts of interest. [transciptID.txt]

-----

**Attention**

Make sure any of the transcript Ids does not contain "|" or space!	



	</help>
</tool>