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date Thu, 22 Sep 2022 11:35:13 +0000
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<tool id="oncoenrichr_wrapper" name="oncoEnrichR" version="1.3.1">
  <description>Cancer-dedicated gene set interpretation</description>
    <requirements>
        <container type="docker">sigven/oncoenrichr:1.3.1</container>
  </requirements>
  <command detect_errors="aggressive"><![CDATA[
      #if $query_set.query_choice.query_input == "text"
        echo $query_set.query_choice.query_text | sed 's/__cn__/\n/g' > query_text.csv &&
        #set input_file = './query_text.csv'
      #else if $query_set.query_choice.query_input == "file"
        ln -s $query_set.query_choice.query_file "$query_set.query_choice.query_file.element_identifier" &&
        #set input_file = './' + str($query_set.query_choice.query_file.element_identifier)
      #end if

      #set background_file = ''
      #if $fun_enrich.custom_bgset.def_background
	      #if $fun_enrich.custom_bgset.bg_choice.bg_source == "text"
	        echo $fun_enrich.custom_bgset.bg_choice.bg_enrich_text | sed 's/__cn__/\n/g' > custom_bgset.csv &&
	        #set background_file = './custom_bgset.csv'
	      #else if $fun_enrich.custom_bgset.bg_choice.bg_source == "file" and $fun_enrich.custom_bgset.bg_choice.bg_enrich_file
	        ln -s $fun_enrich.custom_bgset.bg_choice.bg_enrich_file background_text.csv &&
	        #set background_file = './custom_bgset.csv'
	      #else
	        #set background_file = ''
	      #end if
	 #end if

      R -e 'suppressPackageStartupMessages(library(oncoEnrichR));
      suppressWarnings(load(system.file("internal_db", "oedb.rda", package = "oncoEnrichR")));
      gene_data <- read.csv("$input_file", stringsAsFactors = F, header = F);
      oe_report <- oncoEnrichR::onco_enrich(
        query = gene_data[[1]],
        oeDB = oedb,
      #if $query_set.query_id_type
        query_id_type = "$query_set.query_id_type",
      #end if
      ignore_id_err = $query_set.ignore_id_err,

      #if $report_metadata.project_title
          project_title = "$report_metadata.project_title",
      #end if
      #if $report_metadata.project_owner
          project_owner = "$report_metadata.project_owner",
      #end if
      #if $report_metadata.project_description
          project_description = "$report_metadata.project_description",
      #end if

      show_enrichment = $modules.show_enrichment,
      show_ppi = $modules.show_ppi,
      show_disease = $modules.show_disease,
      show_cancer_hallmarks = $modules.show_cancer_hallmarks,
      show_drug = $modules.show_drug,
      show_aberration = $modules.show_aberration,
      show_coexpression = $modules.show_coexpression,
      show_subcell_comp = $modules.show_subcell_comp,
      show_complex = $modules.show_complex,
	 show_domain = $modules.show_domain,
      show_fitness = $modules.show_fitness,
	 show_cell_tissue = $modules.show_cell_tissue,
      show_ligand_receptor = $modules.show_ligand_receptor,
      show_regulatory = $modules.show_regulatory,
	 show_prognostic = $modules.show_prognostic,
	 show_unknown_function = $modules.show_unknown_function,
      show_synleth = $modules.show_synleth,

      #if $background_file
          bgset = read.csv("$background_file", stringsAsFactors = F, header = F)[[1]],
		#if $fun_enrich.custom_bgset.bg_enrich_id_type
            bgset_id_type = "$fun_enrich.custom_bgset.bg_enrich_id_type",
          #end if
          #if $fun_enrich.custom_bgset.bg_enrich_description
            bgset_description = "$fun_enrich.custom_bgset.bg_enrich_description",
          #end if
      #else
          bgset = NULL,
      #end if

      #if $fun_enrich.p_value_cutoff_enrichment
          p_value_cutoff_enrichment = $fun_enrich.p_value_cutoff_enrichment,
      #end if
      #if $fun_enrich.p_value_adjustment_method
          p_value_adjustment_method = "$fun_enrich.p_value_adjustment_method",
      #end if
      #if $fun_enrich.q_value_cutoff_enrichment
          q_value_cutoff_enrichment = $fun_enrich.q_value_cutoff_enrichment,
      #end if
      #if $fun_enrich.min_geneset_size
          min_geneset_size = $fun_enrich.min_geneset_size,
      #end if
      #if $fun_enrich.max_geneset_size
          max_geneset_size = $fun_enrich.max_geneset_size,
      #end if

      #if $protein_interactions.ppi_add_nodes
          ppi_add_nodes = $protein_interactions.ppi_add_nodes,
      #end if
      #if $protein_interactions.ppi_score_threshold
          ppi_score_threshold = $protein_interactions.ppi_score_threshold,
      #end if
      show_drugs_in_ppi = $protein_interactions.show_drugs_in_ppi,
	 ppi_node_shadow = $protein_interactions.ppi_node_shadow,

	 #if $subcellular_compartments.min_subcellcomp_confidence
          min_subcellcomp_confidence = $subcellular_compartments.min_subcellcomp_confidence,
      #end if
      #if $fitness.max_fitness_score
          max_fitness_score = $fitness.max_fitness_score,
      #end if
      subcellcomp_show_cytosol = $subcellular_compartments.show_cytosol,
      #if $disease.show_top_diseases_only
          show_top_diseases_only = $disease.show_top_diseases_only,
      #end if

      min_confidence_reg_interaction = "$regulatory.min_confidence_reg_interaction",
      num_terms_enrichment_plot = $fun_enrich.num_terms_enrichment_plot,
      simplify_go = $fun_enrich.simplify_go,
      html_floating_toc = $report_metadata.html_floating_toc,
      html_report_theme = "$report_metadata.html_report_theme",
      galaxy = TRUE
      );

      oncoEnrichR::write(report = oe_report, oeDB = oedb, file = "$report1", format = "html", selfcontained_html = F, extra_files_path = "$report1.extra_files_path", overwrite = T, ignore_file_extension = T);
	 oncoEnrichR::write(report = oe_report, oeDB = oedb, file = "$report2", format = "excel", overwrite = T, ignore_file_extension = T)' 2>&1

  ]]></command>
  <inputs>
      <section title="" name=""/>
      <section name="query_set" title="Query gene set" expanded="true">
          <conditional name="query_choice">
                <param name="query_input" type="select" multiple="false" display="radio"
                       label="Query gene set: do you want to upload a file OR paste into a text box?">
                    <option value="text">Text field</option>
				<option value="file">From file</option>
                </param>
                <when value="text">
                    <param type="text" name="query_text" label="Query gene set identifiers (one per line)" area="true"/>
                </when>
			 <when value="file">
                   <param name="query_file" type="data" format="txt" label="Query gene set identifiers" multiple="false"/>
                </when>
          </conditional>
          <param name="query_id_type" type="select" label="Query identifier type" display="radio" multiple="false">
              <option value="symbol">Primary gene symbol (HGNC) - e.g. KRAS</option>
              <option value="uniprot_acc">UniProt accession - e.g. P01116</option>
              <option value="entrezgene">NCBI Entrez gene identifier - e.g. 3845</option>
              <option value="ensembl_gene">Ensembl gene identifier - e.g. ENSG00000133703</option>
              <option value="ensembl_mrna">Ensembl transcript identifier - e.g. ENST00000311936</option>
              <option value="ensembl_protein">Ensembl protein identifier - e.g. ENSP00000308495</option>
              <option value="refseq_mrna">RefSeq mRNA identifier - e.g. NM_004985</option>
              <option value="refseq_protein">RefSeq protein identifier - e.g. NP_004976</option>
          </param>
		<param name="ignore_id_err" type="boolean" label="Ignore erroneous idenfiers" truevalue="T" falsevalue="F" checked="true"/>
      </section>

      <section title="" name=""/>
      <section name="report_metadata" title="Project metadata and output settings" expanded="true">
          <param type="text" name="report_name" label="Output filename (prefix)" value="Report"/>
          <param type="text" name="project_title" label="Project title" />
          <param type="text" name="project_owner" label="Project owner" />
          <param type="text" name="project_description" label="Project description" area="true"/>
          <param name="html_floating_toc" type="boolean" label="HTML report - float the table of contents to the left of the main document content (always visible during scrolling)" truevalue="T" falsevalue="F" checked="true"/>
          <param name="html_report_theme" type="select" label="HTML report - bootswatch theme" expanded="true">
              <option value="default">default</option>
              <option value="cerulean">cerulean</option>
              <option value="cosmo">cosmo</option>
              <option value="journal">journal</option>
              <option value="lumen">lumen</option>
              <option value="paper">paper</option>
              <option value="sandstone">sandstone</option>
              <option value="simplex">simplex</option>
              <option value="spacelab">spacelab</option>
              <option value="united">united</option>
              <option value="yeti">yeti</option>
          </param>
      </section>

      <section title="" name=""/>
      <section name="modules" title="Analysis modules included in the report" expanded="true">
		<param name="show_disease" type="boolean" label="Gene-cancer associations" truevalue="T" falsevalue="F" checked="true"/>
          <param name="show_enrichment" type="boolean" label="Gene functional enrichment" truevalue="T" falsevalue="F" checked="true"/>
		<param name="show_cell_tissue" type="boolean" label="Tissue/cell-type enrichment" truevalue="T" falsevalue="F" checked="false"/>
          <param name="show_ppi" type="boolean" label="Protein-protein interaction network" truevalue="T" falsevalue="F" checked="true"/>
          <param name="show_regulatory" type="boolean" label="Regulatory (TF-target) interactions" truevalue="T" falsevalue="F" checked="true"/>
          <param name="show_ligand_receptor" type="boolean" label="Ligand-receptor interactions" truevalue="T" falsevalue="F" checked="true"/>
          <param name="show_cancer_hallmarks" type="boolean" label="Cancer hallmark associations" truevalue="T" falsevalue="F" checked="true"/>
          <param name="show_drug" type="boolean" label="Drug-target associations" truevalue="T" falsevalue="F" checked="true"/>
          <param name="show_aberration" type="boolean" label="Tumor aberration frequencies" truevalue="T" falsevalue="F" checked="true"/>
          <param name="show_coexpression" type="boolean" label="Tumor co-expression patterns" truevalue="T" falsevalue="F" checked="true"/>
          <param name="show_subcell_comp" type="boolean" label="Subcellular localizations" truevalue="T" falsevalue="F" checked="true"/>
          <param name="show_complex" type="boolean" label="Protein complex memberships" truevalue="T" falsevalue="F" checked="true"/>
		<param name="show_domain" type="boolean" label="Protein domain frequencies" truevalue="T" falsevalue="F" checked="false"/>
          <param name="show_fitness" type="boolean" label="Gene fitness effects" truevalue="T" falsevalue="F" checked="true"/>
          <param name="show_synleth" type="boolean" label="Predicted synthetic lethality interactions" truevalue="T" falsevalue="F" checked="true"/>
		<param name="show_unknown_function" type="boolean" label="Genes of poorly defined function" truevalue="T" falsevalue="F" checked="true"/>
		<param name="show_prognostic" type="boolean" label="Prognostic cancer associations" truevalue="T" falsevalue="F" checked="true"/>
      </section>

      <section title="" name=""/>
      <section name="fun_enrich" title="Options - gene functional enrichment" expanded="true">
		 <conditional name="custom_bgset">
			 <param name="def_background" type="boolean" label="Define custom background set (all annotated protein-coding genes by default)" truevalue="T" falsevalue="F" checked="false"/>
			 <when value="T">
		            <conditional name="bg_choice">
		                <param name="bg_source" type="select" display="radio"
		                       label="Custom background gene set: do you want to upload a file OR paste into a text box?">
						<option value="text">Text field</option>
		                    <option value="file">From file</option>

		                </param>
		                <when value="file">
		                   <param type="data" format="txt" name="bg_enrich_file" label="Custom background gene set" optional="true" multiple="false"/>
		                </when>
		                <when value="text">
		                    <param type="text" name="bg_enrich_text" label="Custom background gene set identifiers (one per line):" area="true"/>
		                </when>
		          </conditional>

		          <param type="select" name="bg_enrich_id_type" label="Custom background identifier type" display="radio" multiple="false">
		              <option value="symbol">Primary gene symbol (HGNC) - e.g. KRAS</option>
                      <option value="uniprot_acc">UniProt accession - e.g. P01116</option>
                      <option value="entrezgene">NCBI Entrez gene identifier - e.g. 3845</option>
                      <option value="ensembl_gene">Ensembl gene identifier - e.g. ENSG00000133703</option>
                      <option value="ensembl_mrna">Ensembl transcript identifier - e.g. ENST00000311936</option>
                      <option value="ensembl_protein">Ensembl protein identifier - e.g. ENSP00000308495</option>
                      <option value="refseq_mrna">RefSeq mRNA identifier - e.g. NM_004985</option>
                      <option value="refseq_protein">RefSeq protein identifier - e.g. NP_004976</option>
		          </param>
		          <param type="text" name="bg_enrich_description" label="Custom background gene set description" value="Custom background description"/>
			</when>
		</conditional>

          <param type="float" name="p_value_cutoff_enrichment" label="P-value cutoff for enrichment tests (clusterProfiler)" value="0.05"/>
          <param type="select" name="p_value_adjustment_method" label="P-value adjustment method (clusterProfiler)">
              <option value="holm">holm</option>
              <option value="hochberg">hochberg</option>
              <option value="hommel">hommel</option>
              <option value="bonferroni">bonferroni</option>
              <option value="BH">BH</option>
              <option value="BY">BY</option>
              <option value="fdr">fdr</option>
              <option value="none">none</option>
          </param>
          <param type="float" name="q_value_cutoff_enrichment" label="Q-value cutoff for enrichment tests to report as significant (clusterProfiler)" value="0.2"/>
          <param type="integer" name="min_geneset_size" label="Minimum number of genes annotated by ontology term for testing (clusterProfiler)" value="10"/>
          <param type="integer" name="max_geneset_size" label="Maximum number of genes annotated by ontology term for testing (clusterProfiler)" value="500"/>
          <param name="simplify_go" type="boolean" label="Simplify GO enrichment results by removal of redundant terms (recommended)" truevalue="T" falsevalue="F" checked="true"/>
          <param type="integer" name="num_terms_enrichment_plot" label="Number of top enriched Gene Ontology terms (max) to show in enrichment barplot" min="10" max="30" value="20"/>
      </section>

      <section title="" name=""/>
      <section name="fitness" title="Options - gene fitness scores" expanded="true">
          <param type="float" name="max_fitness_score" label="Maximum loss-of-fitness score (Bayes Factor from BAGEL) for genes retrieved from Project Score" value="-2" min="-5" max="0"/>
      </section>
      <section title="" name=""/>
      <section name="protein_interactions" title="Options - protein-protein interaction network" expanded="true">
          <param type="integer" name="ppi_add_nodes" label="Addition of interacting non-queryset proteins to the protein-protein interaction network (maximum number)" value="50" min="0" max="50"/>
          <param type="integer" name="ppi_score_threshold" label="Minimum confidence score for interactions to be included in the network (STRING confidence: 0-1000)" value="900" min="400" max="1000"/>
          <param name="show_drugs_in_ppi" type="boolean" label="Show anti-cancer drugs in protein-protein interaction network" truevalue="T" falsevalue="F" checked="true"/>
		<param name="ppi_node_shadow" type="boolean" label="Add shadow to nodes in protein-protein interaction network" truevalue="T" falsevalue="F" checked="true"/>
      </section>
      <section title="" name=""/>
      <section name="regulatory" title="Options - regulatory interactions" expanded="true">
         <param type="select" name="min_confidence_reg_interaction" label = "Minimum confidence level of regulatory interactions included (DoRothEA - A:highest, D:lowest)">
            <option value="D">D</option>
            <option value="C">C</option>
            <option value="B">B</option>
            <option value="A">A</option>
        </param>
      </section>
     <section title="" name=""/>

	 <section name="subcellular_compartments" title="Options - Subcellular localizations" expanded="true">
           <param type="integer" name="min_subcellcomp_confidence" label="Minimum confidence level for subcellular localization annotations" value="1" min="1" max="6"/>
          <param name="show_cytosol" type="boolean" label="Show cytosol annotations (very common localization) in subcellular heatmap " truevalue="T" falsevalue="F" checked="false"/>
      </section>
      <section title="" name=""/>

      <section name="disease" title="Options - Disease associations" expanded="true">
          <param type="boolean" name="show_top_diseases_only" label="Show top disease assocations only" truevalue="T" falsevalue="F" checked="true"/>
      </section>

  </inputs>
    <outputs>
        <data format="xlsx" name="report2" label="$report_metadata.report_name - xlsx"/>
        <data format="html" name="report1" label="$report_metadata.report_name - html"/>
    </outputs>


  <help><![CDATA[
.. class:: infomark

The query gene set is limited to n = 500 identifiers. A limited query gene set (e.g. n < 5) will in general reduce the relevance and significance of many oncoEnrichR report modules.

-----

**Dataset formats**

The input dataset is in tabular_ format. The two output datasets are html_ and xlsx.

.. _tabular: ${static_path}/formatHelp.html#tab
.. _html: ${static_path}/formatHelp.html#html

-----

**What it does**

*OncoEnrichR* is intended for exploratory analysis and prioritization of a candidate hits (referred to as *query set* below) from high-throughput cancer biology experiments. The tool queries a number of high-quality data resources in order to interpret the query gene set along various dimensions, examples being cancer aberration frequencies, protein-protein interactions, pathway enrichment, subcellular compartment localization, target druggability, gene fitness scores, and tissue/cell-type specificity.

The results from the various analysis modules are provided in an interactive HTML report where the user can interrogate the results further. A multisheet Excel workbook is also provided for convience. The following resources are currently utilized for annotation and analysis:

-  `Open Targets Platform <https://targetvalidation.org/>`_ - disease associations, drug-target associations, cancer hallmarks, and druggability/tractability rankings

-  `The Cancer Genome Atlas <https://portal.gdc.cancer.gov/>`_ - gene aberration frequencies and co-expression patterns in approximately 10,000 primary tumor samples

-  `The Human Protein Atlas <https://www.proteinatlas.org/>`_ - expression data for healthy human tissues (`GTex <https://gtexportal.org/home/>`_)/cell types, and prognostic gene expression associations in cancer (`The Pathology Atlas <https://www.proteinatlas.org/humanproteome/pathology/>`_)

-  `Molecular Signatures Database (MSigDB) <http://software.broadinstitute.org/gsea/msigdb/index.jsp/>`_ - collection of annotated (e.g. towards pathways) gene sets for enrichment/overrepresentation analysis. This includes gene sets from `Gene Ontology <http://geneontology.org/>`_, `Reactome <https://reactome.org/>`_, `KEGG <https://www.genome.jp/kegg/pathway.html/>`_, `WikiPathways <https://www.wikipathways.org/index.php/WikiPathways/>`_, `BIOCARTA <https://maayanlab.cloud/Harmonizome/dataset/Biocarta+Pathways/>`_, as well as curated `immunologic <https://www.gsea-msigdb.org/gsea/msigdb/collections.jsp#C7/>`_ and `cancer-specific <https://www.gsea-msigdb.org/gsea/msigdb/collections.jsp#C6/>`_ signatures.

-  `NetPath <http://www.netpath.org/>`_ - manually curated resource of signal transduction pathways in humans

-  `STRING <https://string-db.org/>`_ - protein-protein interaction database

-  `CellChatDB <http://www.cellchat.org/>`_ - database on ligand-receptor interactions

-  `DoRothEA <https://saezlab.github.io/dorothea/>`_ - gene set resource containing signed transcription factor (TF) - target interactions

-  `CORUM <https://mips.helmholtz-muenchen.de/corum/>`_ - protein complex database

-  `Compleat <https://fgr.hms.harvard.edu/compleat>`_ - protein complex resource

-  `ComplexPortal <https://www.ebi.ac.uk/complexportal/home/>`_ - manually curated, encyclopaedic resource of macromolecular complexes

-  `hu.MAP2 <http://humap2.proteincomplexes.org/>`_ - human protein complex map

-  `ComPPI <http://comppi.linkgroup.hu/>`_ - subcellular compartment database

-  `CancerMine <http://bionlp.bcgsc.ca/cancermine/>`_ - literature-mined resource on cancer drivers, oncogenes and tumor suppressor genes

-  `Network of Cancer Genes <http://ncg.kcl.ac.uk/>`_ - manually curated collection of cancer genes, healthy drivers and their properties

-  `Project Score <https://score.depmap.sanger.ac.uk/>`_ - database on the effects on cancer cell line viability elicited by CRISPR-Cas9 mediated gene activation

-  `Genetic determinants of survival in cancer <http://survival.cshl.edu/>`_ - resource on the prognostic impact of genetic aberrations (methylation, CNA, mutation, expression) in human cancers (TCGA)

-  `Predicted synthetic lethality interactions <https://pubmed.ncbi.nlm.nih.gov/34529928/>`_ - comprehensive prediction of synthetic lethality interactions in human cancer cell lines

The contents of the gene set analysis report attempt to answer the following questions related to the query set:

-  Which diseases/tumor types are known to be associated with genes in the query set, and to what extent? Which genes are a classified as proto-oncogenes, tumor suppressors or cancer driver genes?

-  Which query genes have been linked (through literature) to the various hallmarks of cancer?

-  Which genes in the query set are poorly characterized or have an unknown function?

-  Which proteins in the query set can be targeted by inhibitors for diffferent cancer conditions (early and late clinical development phases)? What is the tractability/druggability status for other targets in the query set?

-  Which cancer-relevant protein complexes are involved for proteins in the query set?

-  Are there known cancer-relevant regulatory interactions (transcription factor (TF) - target) found in the query set?

-  Are there known ligand-receptor interactions in the query set?

-  Which subcellular compartments (nucleus, cytosol, plasma membrane etc.) are dominant localizations for members of the query set?

-  Are specific tissues or cell types enriched in the query set, considering healthy tissue/cell-type specific expression patterns (GTex/Human Protein Atlas) of query genes?

-  Which protein-protein interactions are known within the query set? Are there interactions between members of the query set and other cancer-relevant proteins (e.g. proto-oncogenes, tumor-suppressors or predicted cancer drivers)? Which proteins constitute hubs in the protein-protein interaction network?

-  Are there specific pathways, biological processes or molecular functions that are enriched within the query set, as compared to a reference/background set?

-  Which members of the query set are frequently mutated in tumor sample cohorts (TCGA - SNVs/InDels / homozygous deletions / copy number amplifications)? What are the most frequent recurrent somatic variants (SNVs/InDels) in the query set genes?

-  Which members of the query set are co-expressed (strong negative or positive correlations) with cancer-relevant genes (i.e. proto-oncogenes or tumor suppressors) in tumor sample cohorts (TCGA)?

-  Which members of the query set are associated with better/worse survival in different cancers, considering mutation, expression, methylation or copy number levels in tumors?

-  Which members of the query set are predicted as partners of synthetic lethality interactions?

-  Which members of the query set are associated with cellular loss-of-fitness in CRISPR/Cas9 whole-genome drop out screens of cancer cell lines (i.e. reduction of cell viability elicited by a gene inactivation)? Which genes should be prioritized considering genomic biomarkers and fitness scores in combination?


]]>
  </help>

 <citations>
     <!-- Example of annotating a citation using a DOI. -->
     <citation type="doi">10.48550/arXiv.2107.13247</citation>
     <!-- Example of annotating a citation using a BibTex entry. -->     
  </citations>
</tool>