<?xml version="1.0"?>

<tool name="Conduct GO" id="goId" force_history_refresh="True">
  <description>
     Given a list of genes, using Bioconductor (GO, GOstats) and  DAVID at NIH
  </description>
  <code file="go_analysis_code.py"/>
  <command interpreter="python">
  go_analysis.py  '$title' '$diff_expr_file' '$logmeta' '$diff_expr_file.dbkey', '$annotation'
  </command>

  <inputs>
    <param name="title" label="Title to label the new output file" type="text" size="80" value="Conduct GO" />
    <param name="diff_expr_file" type="data" format="txt" label="Target Gene List"
	   optional="false" size="120" help="Choose a target gene list from your history (make sure in this file there is a column called 'Gene' for gene Entrez IDs or the file only contains a single column for Entrez IDs) "/>
    <param name="annotation" type="select" label="Gene Universe">
      <option value="hgu133a" selected="True">Homo sapiens hgu133a</option>
      <option value="hgu133b">Homo sapiens hgu133b</option>
      <option value="hgu133plus2">Homo sapiens hgu133plus</option>
      <option value="hgu95av2">Homo sapiens hgu95av2</option>
      <option value="mouse430a2">Mouse 430a2</option>
      <option value="celegans">C. elengans</option>
      <!--<option value="fly.db0">Fly</option>-->
      <option value="drosophila2">Drosophila</option>
      <option value="org.Hs.eg">org.Hs.eg</option>
      <option value="org.Mm.eg">org.Mm.eg</option>
      <option value="org.Ce.eg">org.Ce.eg</option>
      <option value="org.Dm.eg">org.Dm.eg</option>
    </param>         
  </inputs>

  <outputs>     
    <data format='txt' name="logmeta"/>
  </outputs>
  <help>
  

**Syntax**

- **Title:** is used to name the output files - so make it meaningful
- **Target Gene List:** Choose a target gene list from your history
- **Gene Universe:** Select a gene universe

-----

**Summary**

For a list of input genes, this tool uses R/BioC packages (GO, GOstats)  to
identify over represented GO terms.  The number of input genes that can be associated
with the GO term are compared to the number of genes from the gene universe that can
be associated with the specific GO term. The gene universe should be defined as the
list of genes that were used to identify differentially expressed genes (the input genes).
This gene universe can be either the collection of all genes that can be detected with
the microarray used in the analysis, or the list of genes that passed a non-specific
pre-filtering in an analysis for the identification of differentially expressed genes.
This tool also allows to perform  GO analysis using DAVID (http://david.abcc.ncifcrf.gov).

The input list of target genes, (Entrez Gene ID) is typically obtained as result of the use of the
"Calculate differential expression" tool and the format is as follow:

::

    Probe       Symbol  Description     Gene    Cytoband    Log2Ratio   PValue
    20042_at    SOD1    superoxide..    6647    21q22.1     0.838191    0.008021
    200818_at   ATP50   ATP synthase..  539     21q22.1-q   0.711812    0.006348
    201123_s_at EIF5A   eukayotic..     1984    17p13-p12   -1.80077    0.008021

Any gene list with  Entrez ID can be used as input for this tool, you can load the list into your history using the
"Upload File from your computer" tool, the tool will look for a column called "Gene". The following is a valid example:

::

	Gene
	351
	6647
	3337
	754
	6612
	539
	1984
	1471
	5445
	8209
	522
	

The output will be 3 different text files:

- Cellular Component ontology: GO_CC_Result.txt
- Biological Process ontology: GO_BP_Result.txt
- Molecular Function ontology: GO_MF_Result.txt

The column "Gene"  (EntrezIDs) will be used to map the significantly over represented GO
terms for the particular GO analysis, GO-terms reported will be sorted according to their
significance (p-value).

After the GO analysis is conducted using uses R/BioC packages (GO, GOstats), the original
target gene list  is also send to DAVID (http://david.abcc.ncifcrf.gov) for comparative
analysis.

  </help>
</tool>