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1 <tool id="condel_web" name="condel">
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2 <description>Condel web service</description>
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3 <command interpreter="python">
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4 condel_web.py --input $input --output $output
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5 </command>
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6 <inputs>
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7 <param name="input" format="text" type="data" label="Input Variants" />
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8 </inputs>
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9 <outputs>
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10 <data name="output" format="tabular"/>
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11 </outputs>
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12 <help>
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13 **What it does**
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14 Condel stands for CONsensus DELeteriousness score of non-synonymous single nucleotide variants (SNVs).
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15 The idea behind it is to integrate the output of computational tools aimed at assessing the impact of non synonymous
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16 SNVs on protein function. To do this, it computes a weighted average of the scores (WAS) of these tools.
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17 Condel was developed to integrate the outputs of five tools: SIFT, Polyphen2, MAPP, LogR Pfam E-value
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18 (implemented ad hoc following the instructions at Clifford RJ, Edmonson MN, Nguyen C, and Buetow KH (2004)
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19 Large-scale analysis of non-synonymous coding region single nucleotide polymorphisms. Bioinformatics 20, 1006-1014) and MutationAssessor
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20
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21
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22 The scores of different methods are weighted using the complementary cumulative distributions produced by the five
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23 methods on a dataset of approximately 20000 missense SNPs, both deleterious and neutral.
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24 The probability that a predicted deleterious mutation is not a false positive of the method and the probability that a
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25 predicted neutral mutation is not a false negative are employed as weights
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26
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27 **Citation**
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28
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29 If you use this Galaxy tool in work leading to a scientific publication please cite:
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30
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31 Improving the Assessment of the Outcome of Nonsynonymous SNVs with a Consensus Deleteriousness Score,
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32 Condel (2011) Abel González-Pérez and Nuria López-Bigas, American Journal of Human Genetics 10.1016/j.ajhg.2011.03.004
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33 </help>
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34 </tool>
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