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author | lgueguen |
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date | Fri, 22 Jul 2016 05:39:13 -0400 |
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<tool id="sartools_deseq2" name="SARTools DESeq2" version="1.0.0"> <!-- [REQUIRED] Tool description displayed after the tool name --> <description>Compare two or more biological conditions in a RNA-Seq framework with DESeq2</description> <macros> <import>macros.xml</import> </macros> <expand macro="requirements"/> <expand macro="stdio"/> <!-- [REQUIRED] The command to execute --> <command interpreter="python"><![CDATA[ abims_sartools_deseq2_wrapper.py ## parameters @COMMAND_BASIC_PARAMETERS@ #if str( $advanced_parameters.adv_param ) == "show": @COMMAND_BATCH_PARAM@ --fitType $advanced_parameters.fitType --cooksCutoff $advanced_parameters.cooksCutoff --independentFiltering $advanced_parameters.independentFiltering --alpha $advanced_parameters.alpha --pAdjustMethod $advanced_parameters.pAdjustMethod --typeTrans $advanced_parameters.typeTrans --locfunc $advanced_parameters.locfunc --colors $advanced_parameters.colors #end if ## ouputs @COMMAND_OUTPUTS@ ]]></command> <!-- [REQUIRED] Input files and tool parameters --> <inputs> <expand macro="basic_parameters" /> <conditional name="advanced_parameters" > <param name="adv_param" type="select" label="Advanced Parameters" help="" > <option value="hide" selected="true">Hide</option> <option value="show">Show</option> </param> <when value="hide" /> <when value="show"> <expand macro="batch_param" /> <param name="fitType" type="select" label="Mean-variance relationship" help="(-f, --fitType) Type of model for the mean-dispersion relationship. Parametric by default." > <option value="parametric" selected="true">parametric</option> <option value="local">local</option> </param> <param name="cooksCutoff" type="boolean" checked="true" truevalue="TRUE" falsevalue="FALSE" label="Perform the outliers detection" help="(-o, --cooksCutoff) Checked by default."/> <param name="independentFiltering" type="boolean" checked="true" truevalue="TRUE" falsevalue="FALSE" label="Perform independent filtering" help="(-i, --independentFiltering) Checked by default."/> <expand macro="alpha_param" /> <expand macro="padjustmethod_param" /> <param name="typeTrans" type="select" label="Transformation for PCA/clustering" help="(-T --typeTrans) Method of transformation of the counts for the clustering and the PCA: 'VST' (default) for Variance Stabilizing Transformation, or 'rlog' for Regularized Log Transformation." > <option value="VST" selected="true">VST</option> <option value="rlog">rlog</option> </param> <param name="locfunc" type="select" label="Estimation of the size factors" help="(-l --locfunc) 'median' (default) or 'shorth' from the genefilter package." > <option value="median" selected="true">median</option> <option value="shorth">shorth</option> </param> <expand macro="colors_param" /> </when> </conditional> </inputs> <!-- [REQUIRED] Output files --> <outputs> <expand macro="outputs" /> </outputs> <!-- [OPTIONAL] Tests to be run manually by the Galaxy admin --> <tests> <!-- [HELP] Test files have to be in the ~/test-data directory --> <test> <!-- Test with 2 conditions, 2 replicates, 8217 features --> <param name="targetFile" dbkey="?" value="target.txt" /> <param name="rawDir" value="raw.zip" dbkey="?" ftype="zip"/> <param name="adv_param" value="show"/> <output name="log"> <assert_contents> <has_text text="KO vs WT 0.1 171" /> <has_text text="KO vs WT 2584 2665 5249" /> <has_text text="HTML report created" /> </assert_contents> </output> </test> <!-- <test> --> <!-- NOT WORKING YET: Test with 3 conditions, 3 replicates, 10160 features, with batch effect --> <!-- <param name="targetFile" dbkey="?" value="targetT048.txt" /> <param name="rawDir" value="rawT048.zip" dbkey="?" ftype="no_unzip.zip"/> <param name="condRef" value="T0"/> <param name="adv_param" value="show"/> <param name="condition" value="true"/> <output name="tables_html" file="SARTools_DESeq2_targetT048_tables.html" lines_diff="14"> <extra_files type="file" name="T4vsT0.complete.txt" value="SARTools_DESeq2_T4vsT0.complete.txt"/> <extra_files type="file" name="T8vsT0.complete.txt" value="SARTools_DESeq2_T8vsT0.complete.txt"/> <extra_files type="file" name="T8vsT4.complete.txt" value="SARTools_DESeq2_T8vsT4.complete.txt"/> </output> </test> --> </tests> <!-- [OPTIONAL] Help displayed in Galaxy --> <help><![CDATA[ @HELP_AUTHORS@ =============== SARTools DESeq2 =============== ----------- Description ----------- @HELP_DESCRIPTION@ ----------- Input files ----------- @HELP_INPUT_FILES@ ---------- Parameters ---------- @HELP_BASIC_PARAMETERS@ * **batch:** adjustment variable to use as a batch effect, must be a column of the target file (NULL if no batch effect needs to be taken into account); * **alpha:** significance threshold applied to the adjusted p-values to select the differentially expressed features (default is 0.05); * **fitType:** type of model for the mean-dispersion relationship ("parametric" by default, or "local"); * **cooksCutoff:** TRUE (default) of FALSE to execute or not the detection of the outliers [4]; * **independentFiltering:** TRUE (default) of FALSE to execute or not the independent filtering [5]; * **pAdjustMethod:** p-value adjustment method for multiple testing [6, 7] ("BH" by default, "BY" or any value of p.adjust.methods); * **typeTrans:** method of transformation of the counts for the clustering and the PCA (default is "VST" for Variance Stabilizing Transformation, or "rlog" for Regularized Log Transformation); * **locfunc:** function used for the estimation of the size factors (default is "median", or "shorth" from the genefilter package); * **colors:** colors used for the figures (one per biological condition), 8 are given by default. ------------ Output files ------------ @HELP_OUTPUT_FILES@ --------------------------------------------------- [1] G.-K. Smyth. Limma: linear models for microarray data. In R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, and W. Huber, editors, Bioinformatics and Computational Biology Solutions Using R and Bioconductor, pages 397–420. Springer, New York, 2005. [2] S. Anders. HTSeq: Analysing high-throughput sequencing data with Python. http://www-huber.embl.de/users/anders/HTSeq/, 2011. [3] S. Anders, P.-T. Pyl, and W. Huber. HTSeq - A Python framework to work with high-throughput sequencing data. bioRxiv preprint, 2014. URL: http://dx.doi.org/10.1101/002824. [4] R.-D. Cook. Detection of Influential Observation in Linear Regression. Technometrics, February 1977. [5] R. Bourgon, R. Gentleman, and W. Huber. Independent filtering increases detection power for high-throughput experiments. PNAS, 107(21):9546–9551, 2010. URL: http://www.pnas.org/content/107/21/9546.long. [6] Y. Benjamini and Y. Hochberg. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society B, 57:289–300, 1995. [7] Y. Benjamini and D. Yekutieli. The control of the false discovery rate in multiple testing under dependency. Ann. Statist., 29(4):1165–1188, 2001. ]]></help> <citations> <expand macro="common_citations" /> <citation type="bibtex">@ARTICLE{Cook77, author = {R.-D. Cook}, title = {Detection of Influential Observation in Linear Regression}, journal = {Technometrics}, year = {1977}, month = {February} }</citation> <citation type="bibtex">@ARTICLE{Bourgon10, author = {R. Bourgon, R. Gentleman, and W. Huber}, title = {Independent filtering increases detection power for high-throughput experiments}, journal = {PNAS}, year = {2010}, volume = {107}, number = {21}, pages = {9546–9551}, note = {URL: http://www.pnas.org/content/107/21/9546.long} }</citation> </citations> </tool>