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1 <tool id="gemini_@BINARY@" name="GEMINI @BINARY@" version="@version@.0">
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2 <description>Filter LoF variants by transcript position and type</description>
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3 <expand macro="requirements" />
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4 <expand macro="version_command" />
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5 <macros>
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6 <import>gemini_macros.xml</import>
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7 <token name="@BINARY@">lof_sieve</token>
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8 </macros>
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9 <command>
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10 <![CDATA[
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11 gemini @BINARY@
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12 "${ infile }"
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13 > "${ outfile }"
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14 ]]>
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15 </command>
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16 <expand macro="stdio" />
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17 <inputs>
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18 <param name="infile" type="data" format="sqlite" label="GEMINI database" />
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19 </inputs>
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20 <outputs>
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21 <data name="outfile" format="tabular" label="${tool.name} on ${on_string}" />
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22 </outputs>
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23 <tests>
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24 <test>
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25 </test>
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26 </tests>
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27 <help>
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28 **What it does**
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29
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30 Not all candidate LoF variants are created equal. For e.g, a nonsense (stop gain) variant impacting the first 5% of a polypeptide is far
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31 more likely to be deleterious than one affecting the last 5%. Assuming you’ve annotated your VCF with snpEff v3.0+, the lof_sieve tool
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32 reports the fractional position (e.g. 0.05 for the first 5%) of the mutation in the amino acid sequence.
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33 In addition, it also reports the predicted function of the transcript so that one can segregate candidate
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34 LoF variants that affect protein_coding transcripts from processed RNA, etc.
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35
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36 @CITATION@
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37 </help>
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38 <expand macro="citations"/>
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39 </tool>
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