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| author | iuc |
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| date | Wed, 12 Jan 2022 19:07:45 +0000 |
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<tool id="genomic_super_signature" name="GenomicSuperSignature" version="@TOOL_VERSION@+galaxy@GALAXY_VERSION@" profile="20.01"> <description>interpretation of RNAseq experiments</description> <macros> <token name="@TOOL_VERSION@">1.2.0</token> <token name="@GALAXY_VERSION@">0</token> </macros> <requirements> <requirement type="package" version="@TOOL_VERSION@">bioconductor-genomicsupersignature</requirement> <requirement type="package" version="1.7.1">r-optparse</requirement> <requirement type="package" version="2.6">r-wordcloud</requirement> <requirement type="package" version="2.22.0">bioconductor-biocstyle</requirement> <requirement type="package" version="2.7.3">r-magick</requirement> <requirement type="package" version="2021d">tzdata</requirement> </requirements> <command detect_errors="exit_code"><![CDATA[ #set $model = $model.fields.path mkdir out && Rscript '$__tool_directory__/gss.R' --input '$input' --model '$model' --method '$method' --maxFrom '$maxFrom' --level '$level' --scale '$scale' --numOut $numOut --outDir out --toolDir '$__tool_directory__' --validate '$validate' --html '$html' ]]></command> <inputs> <param argument="--input" type="data" format="tabular,tsv" label="Tabular count matrix"/> <param argument="--model" type="select" label="Using RAVmodel" help="Select model from the list"> <options from_data_table="genomic_super_signature_ravmodels"> <filter type="data_meta" ref="input" key="dbkey" column="dbkey" /> </options> <validator type="no_options" message="A built-in RAVmodel is not available for the build associated with the selected input file"/> </param> <param argument="--method" type="select" label="Select a correlation coefficient"> <option value="pearson">Pearson</option> <option value="kendall">Kendall</option> <option value="spearman">Spearman</option> </param> <param argument="--maxFrom" type="select" label="Select whether to display the maximum value from dataset's PCs or avgLoadings" help="With Principal Component (PC), the maximum correlation coefficient from top 8 PCs for each avgLoading will be selected as an output. If you choose Average Loading, the Average Loading with the maximum correlation coefficient with each Principal Component will be in the output."> <option value="pc">Principal Components</option> <option value="avgLoading">Average Loading</option> </param> <param argument="--level" type="select" label="Output format of validated result" help="max will output the matrix containing only the maximum coefficient. To get the coefficient of all 8 PCs, set this argument to all."> <option value="max">Max</option> <option value="all">All</option> </param> <param argument="--scale" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="false" label="Normalize rows of datasets?"/> <param argument="--numOut" type="integer" min="1" value="3" label="The number of top validated RAVs to check"/> </inputs> <outputs> <collection name="genesets" type="list" label="GenomicSuperSignature Genesets"> <discover_datasets pattern=".*_genesets_(?P<name>.+)\.csv" format="csv" directory="out" /> </collection> <collection name="literatures" type="list" label="GenomicSuperSignature Literatures"> <discover_datasets pattern=".*_literatures_(?P<name>.+)\.csv" format="csv" directory="out" /> </collection> <data name="validate" format="csv" label="GenomicSuperSignature validate.csv"> </data> <data name="html" format="html" label="GenomicSuperSignature report.html"> </data> </outputs> <tests> <test> <param name="input" value="bcellViperExpr_10C.tsv.gz" dbkey="hg38" ftype="tabular"/> <param name="model" value="microRAVmodel" dbkey="hg38"/> <param name="method" value="Pearson"/> <param name="maxFrom" value="Principal Components"/> <param name="level" value="Max"/> <param name="numOut" value="1"/> <output name="html" ftype="html"> <assert_contents> <has_n_lines n="2843"/> </assert_contents> </output> <output name="validate" ftype="csv"> <assert_contents> <has_line line='"","score","PC","sw","cl_size","cl_num"'/> <has_text text='"RAV1076"'/> <has_text text='"RAV725"'/> <has_text text='"RAV884"'/> <has_text text='"RAV1994"'/> <has_n_lines n="5"/> </assert_contents> </output> </test> </tests> <help><![CDATA[ GenomicSuperSignature ===================== What it does ------------ Connect new gene expression profile with the relevant information from the existing databases, such as previous publications, MeSH terms, and gene sets. Inputs ------ Count Files ~~~~~~~~~~~ GenomicSuperSignature takes a count matrix as an input. Input file should have row names in gene symbols and column names in sample ID. For the best result, we recommend a data transformation (e.g. log2) for the input to follow a normal distribution, while scaling is NOT recommended. Currently for validation, inputs need at least eight samples. Example of input format: ===== ======== ========= ======== ========= \ GSM44075 GSM44078 GSM44080 GSM44081 ===== ======== ========= ======== ========= ADA 9.571369 10.599436 8.740659 10.104469 CDH2 6.175890 5.312704 5.651928 4.462205 MED6 9.671113 8.773383 9.190276 9.526235 NR2E3 9.847733 9.582061 9.628792 8.820422 ===== ======== ========= ======== ========= RAVmodel ~~~~~~~~ *R*\ eplicable *A*\ xes of *V*\ ariation (RAV) consists of principal components repeatedly observed in an independent analysis of multiple published datasets. RAVs connect different databases that are both linked to the originated study or associated with the RAV itself through the gene rankings of it. RAVmodel contains the collection of RAVs (RAVindex), metadata from model building process and the additional annotations. Currently, two RAVmodels are available based on the gene sets used for annotation. 1) C2 : RAVmodel annotated with Molecular Signatures Database (MSigDB) curated gene sets (version 7.1) 2) PLIERpriors : RAVmodel annotated with the three gene sets provided in the `PLIER package <https://github.com/wgmao/PLIER>`__ - bloodCellMarkersIRISDMAP, svmMarkers, and canonicalPathways Outputs ------- There are four categories of outputs from this tool, which is one html file and three csv tabular files. The actual number of csv files will vary depending on the parameter, *–numOut*, and the validated RAVs. validate.csv ~~~~~~~~~~~~ +--------------------------+--------------------------------------------+ | Column | Description | +==========================+============================================+ | score | the maximum pearson correlation | | | coefficient between the top 8 PCs of the | | | input and RAVs | +--------------------------+--------------------------------------------+ | PC | one of the top 8 PCs of the input, which | | | gives the highest *score* | +--------------------------+--------------------------------------------+ | sw | the average silhouette width of the RAV | +--------------------------+--------------------------------------------+ | cl_size | the size of each RAV | +--------------------------+--------------------------------------------+ | cl_num | the RAV number | +--------------------------+--------------------------------------------+ Genesets ~~~~~~~~ This is the enriched gene sets for the target RAV, calculated from the ranked gene list. Gene sets with the adjusted p-value < 0.05 are included. =========== ================================ Column Description =========== ================================ Description name of the gene sets NES normalized enrichment score (ES) pvalue statistical significance qvalues p-value adjusted for the FDR =========== ================================ Literatures ~~~~~~~~~~~ ========= ====================== Column Description ========= ====================== studyName study accession title the title of the study ========= ====================== report.html ~~~~~~~~~~~ A html file with the summary of the main analyses by GenomicSuperSignature. It includes MeSH terms in word cloud and an interactive plot overviewing the validated RAVs, in addition to the previews of the tabular output files. Citations --------- Oh, S., Geistlinger, L., Ramos, M., Taroni, J.N., Carey, V.J., Greene, C.S., Waldron, L., & Davis, S.R. (2021). GenomicSuperSignature: interpretation of RNA-seq experiments through robust, efficient comparison to public databases. bioRxiv. References ---------- | GenomicSuperSignature package: `webpage <https://shbrief.github.io/GenomicSuperSignature/>`__ | GenomicSuperSignature usecases: `webpage <https://shbrief.github.io/GenomicSuperSignaturePaper/>`__ ]]></help> <citations> <citation type="doi">10.1101/2021.05.26.445900</citation> </citations> </tool>