view footprint_codons.xml @ 0:f40b0b26e766 default tip

First commit

<tool id="footprint_codon" name="Similarity of observed and expected profiles" version="1">
    <description>(Step 3)</description>
    <requirements>
        <requirement type="package" version="0.1.0">RUST</requirement>
        <requirement type="package" version="0.1.18">samtools</requirement>
    </requirements>
   <command>python \${RUST_PATH}/footprint_codons.py $input $alignment $offset $include_lengths $observed_codon $output1 </command>
   <inputs>
     <param format="fasta" name="input" type="data" label="Transcriptome file" help="A fasta file whose transcripts are used to produce the metafootprint profile."/>
     <param format="bam" name="alignment" type="data" label="Alignment file" help="The alignments of ribo-seq/mRNA-seq reads to the Transcriptome file. This should be a sorted bam file."/>
     <param name="offset" value="17" type="integer" label="Nucleotide offset to A-site"/>
     <param name="include_lengths" type="text"
               label="Lengths of ribosome footprints
             to be included"
            help="Here you can specify the lengths of ribosome footprints to
             be included (28:32 includes reads of length 28,29,30,31,32)."
              value="28:32">
<!--       <validator type="expression" message="Please input correct format">len(value.split(':')) == 2</validator> -->
      </param>           
     <param format="csv" name="observed_codon" type="data" label="Codon metafootprint" help="RUST codon metafootprint analysis">
      </param>           
   </inputs>
   <outputs>
     <data format="csv" name="output1" help="Contains prediction of ribosome profile for transcripts in Transcriptome file that fulfill certain criteria" />
   </outputs>
 

 
   <help>
**What it does**

Uses the observed codon RUST ratios of 12 sites (A-site-6 to A-site+5) to calculate alignment probabilities along the elongation region of each transcript. It then compares the similarity between the expected and observed ribosome profiles using both Spearman's and Pearson's correlation coefficients. This is returned in a csv file.

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**Citation**

Surveying the relative impact of mRNA features on local ribosome profiling read density in 28 datasets.
Patrick O'Connor, Dmitry Andreev, Pavel Baranov
bioRxiv doi: http://dx.doi.org/10.1101/018762

   </help>
 
</tool>