<tool id="shRNAseq" name="shRNAseq Tool" version="1.0.8">
  <description>
    Analyse hairpin differential representation using edgeR
  </description>
    
  <requirements>
    <requirement type="R-module" version="3.5.27">edgeR</requirement>
    <requirement type="R-module" version="3.18.13">limma</requirement>
  </requirements>
  
  <stdio>
    <exit_code range="1:" level="fatal" description="Tool exception" />
  </stdio>
  
  <command interpreter="Rscript">
  hairpinTool.R $inputOpt.inputType
                #if $inputOpt.inputType=="fastq":
                  #for $i, $fas in enumerate($inputOpt.fastq):
                    fastq::$fas.file
                  #end for
    
                  $inputOpt.hairpin
                  $inputOpt.samples
                    
                  #if $inputOpt.positions.posOption=="yes":
                    $inputOpt.positions.barstart
                    $inputOpt.positions.barend
                    $inputOpt.positions.hpstart
                    $inputOpt.positions.hpend
                  #else:
                    1
                    5
                    37
                    57
                  #end if
                #else:
                  $inputOpt.counts
                  $inputOpt.hairpin
                  $inputOpt.samples
                  0 0 0
                #end if
          
                #if $filterCPM.filtOption=="yes":
                  $filterCPM.cpmReq
                  $filterCPM.sampleReq
                #else:
                  -Inf
                  -Inf
                #end if
          
                $fdr
                $lfc
                $workMode.mode
                $outFile
                $outFile.files_path
          
                #if $workMode.mode=="classic":
                  "$workMode.pair1"
                  "$workMode.pair2"
                #elif $workMode.mode=="glm":
                  "$workMode.contrast"
                  $workMode.roast.roastOption
                  #if $workMode.roast.roastOption=="yes":
                    $workMode.roast.hairpinReq
                    $workMode.roast.select.selOption
                    "$workMode.roast.select.selection"
                  #else:
                    0
                    0
                    0
                  #end if
                #end if
  </command>
  
  <inputs>
    <conditional name="inputOpt">
      <param name="inputType" type="select" label="Input File Type">
        <option value="fastq">FastQ File</option>
        <option value="counts">Table of Counts</option>
      </param>
    
      <when value="fastq">
        <param name="hairpin" type="data" format="tabular" 
               label="Hairpin Annotation"/>
          
        
        <param name="samples" type="data" format="tabular" 
               label="Sample Annotation"/>
               
        <repeat name="fastq" title="FastQ Files">       
          <param name="file" type="data" format="fastq"/>
        </repeat>
          
        <conditional name="positions">
          <param name="posOption" type="select" 
                 label="Specify Barcode and Hairpin Locations?"
                 help="Default Positions: Barcode: 1 to 5, Hairpin: 37 to 57.">
            <option value="no" selected="True">No</option>
            <option value="yes">Yes</option>
          </param>
          
          <when value="yes">
            <param name="barstart" type="integer" value="1"
                   label="Barcode Starting Position"/>
            <param name="barend" type="integer" value="5"
                   label="Barcode Ending Position"/>
            
            <param name="hpstart" type="integer" value="37"
                   label="Hairpin Starting Position"/>
               
            <param name="hpend" type="integer" value="57"
                   label="Hairpin Ending Position"/>
          </when>
          
          <when value="no"/>
        </conditional>
      </when>
      
      <when value="counts">
        <param name="counts" type="data" format="tabular" label="Counts Table"/>
        <param name="hairpin" type="data" format="tabular" 
               label="Hairpin Annotation"/>
        <param name="samples" type="data" format="tabular"
               label="Sample Annotation"/> 
      </when>
    </conditional>
    
    <conditional name="filterCPM">
      <param name="filtOption" type="select" label="Filter Low CPM?"
       help="Ignore hairpins with very low representation when performing 
             analysis.">
        <option value="yes">Yes</option>
       	<option value="no">No</option>
      </param>
      
        <when value="yes">
          <param name="cpmReq" type="float" value="0.5" min="0" max="1"
                 label="Minimum CPM"/>
                 
          <param name="sampleReq" type="integer" value="1" min="0"
                 label="Minimum Samples" 
                 help="Filter out all the genes that do not meet the minimum 
                       CPM in at least this many samples."/>
        </when>
        
        <when value="no"/>
        
    </conditional>
    
    <conditional name="workMode">
      <param name="mode" type="select" label="Analysis Type"
       help="Classic Exact Tests are useful for simple comparisons across
             two sampling groups. Generalised linear models allow for more 
             complex contrasts and gene level analysis to be made.">
        <option value="classic">Classic Exact Test</option>
        <option value="glm">Generalised Linear Model</option>
      </param>
      
      <when value="classic">
        <param name="pair1" type="text" label="Compare" size="40"/>
        <param name="pair2" type="text" label="To" size="40"
               help="The analysis will subtract values of this group from those
                     in the group above to establish the difference."/>
      </when>
      
      <when value="glm">
        <param name="contrast" type="text" size="60"
               label="Contrasts of interest"
               help="Specify equations defining contrasts to be made. Eg. 
                     KD-Control will result in positive fold change if KD has
                     greater expression and negative if Control has greater
                     expression."/>
               
        <conditional name="roast">
          <param name="roastOption" type="select" 
                 label="Perform Gene Level Analysis?"
                 help="Analyse LogFC tendencies for hairpins belonging
                       to the same gene.">
            <option value="no">No</option>
            <option value="yes">Yes</option>
          </param>
          
          <when value="yes">
            <param name="hairpinReq" type="integer" value="2" min="2"
                   label="Minimum Hairpins"
                   help="Only genes with at least this many hairpins will
                         be analysed."/>
                         
            <conditional name="select">
              <param name="selOption" type="select"
                     label="Gene Selection Method">
                <option value="rank">By p-value Rank</option>
                <option value="geneID">By Gene Identifier</option>
              </param>
              <when value="rank">
                <param name="selection" type="text" size="40" value="1:5"
                       label="Ranks of Top Genes to Plot"
                       help="Genes are ranked in ascending p-value for
                             differential representation, individual ranks can
                             be entered seperated by comma or a range seperated
                             by colon."/>
              </when>
              <when value="geneID">
                <param name="selection" type="text" size="80" value=""
                       label="Symbols of Genes to Plot"
                       help="Select genes based on their identifier in the
                             'Gene' column of the sample information file.
                             Please ensure exact match with the values in input
                             file and separate selections with commas."/>
              </when>
            </conditional>

            
          </when>
          
          <when value="no"/>
        </conditional>
      </when>
    </conditional>
    
    <param name="fdr" type="float" value="0.05" min="0" max="1"
           label="FDR Threshold"
           help="All observations below this threshold will be highlighted
                 in the smear plot."/>
    <param name="lfc" type="float" value="0" min="0" 
           label="Absolute LogFC Threshold"
           help="In additional to meeting the FDR requirement, the absolute 
                 value of the log-fold-change of the observation must be above
                 this threshold to be highlighted."/>
  </inputs>

  <outputs>
    <data format="html" name="outFile" label="shRNAseq Analysis"/>
  </outputs>
  <help>
.. class:: infomark

**What it does**

Given tables containing information about the hairpins and their associated
barcodes, information about the samples and fastq file containing the hairpin
reads. This tool will generate plots and tables for the analysis of differential
representation.

.. class:: infomark

A tutorial of how to use this tool is available at:
http://bioinf.wehi.edu.au/shRNAseq/galaxy.html

-----

.. class:: infomark

**INPUTS**

**Input File Type:**

This tool is able to either generate counts from a raw FastQ file given the
information regarding the samples and hairpins. Alternatively if a table of
counts has already been generated it can also be used.

**Counts Table (Counts Input):**

A tab delimited text table of information regarding the counts of hairpins.
Should have a column 'ID' to denote the hairpins that counts correspond to. Each
additional column should have titles corresponding to the label for the sample.

Example::

  ID  Sample1 Sample2 Sample3
  Control1 49802 48014 40148
  Control2 12441 16352 14232
  Control3 9842  9148  9111
  Hairpin1 3300  3418  2914
  Hairpin2 91418 95812 93174
  Hairpin3 32985 31975 35104
  Hairpin4 12082 14081 14981
  Hairpin5 2491  2769  2691
  Hairpin6 1294  1486  1642
  Hairpin7 49501 49076 47611
  ...
  
**Hairpin Annotation:**

A tab delimited text table of information regarding the hairpins. Should have
columns 'ID', 'Sequences' and 'Gene' to uniquely identify the hairpin, align it
with the reads to produce counts and identify which gene the hairpin acts on.

NOTE: the column names are case sensitive and should be input exactly as they
are shown here.

Example::

  ID	Sequences	Gene
  Control1	TCTCGCTTGGGCGAGAGTAAG	2
  Control2	CCGCCTGAAGTCTCTGATTAA	2
  Control3	AGGAATTATAATGCTTATCTA	2
  Hairpin1	AAGGCAGAGACTGACCACCTA	4
  Hairpin2	GAGCGACCTGGTGTTACTCTA	4
  Hairpin3	ATGGTGTAAATAGAGCTGTTA	4
  Hairpin4	CAGCTCATCTTCTGTGAAGAA	4
  Hairpin5	CAGCTCTGTGGGTCAGAAGAA	4
  Hairpin6	CCAGGCACAGATCTCAAGATA	4
  Hairpin7	ATGACAAGAAAGACATCTCAA	7
  ...
  
**Sample Annotation (FastQ Input):**

A tab delimited text table of information regarding the samples. Should have
columns 'ID', 'Sequences' and 'group' to uniquely identify each sample, identify
the sample in the reads by its barcode sequence and correctly group replicates
for analysis. Additional columns may inserted for annotation purposes and will
not interfere with analysis as long as the necessary columns are present.

NOTE: the column names are case sensitive and should be input exactly as they
are shown here.

Example::

  ID	Sequences	group	Replicate
  3	GAAAG	Day 2	1
  6	GAACC	Day 10	1
  9	GAAGA	Day 5 GFP neg	1
  16	GAATT	Day 5 GFP pos	1
  18	GACAC	Day 2	2
  21	GACCA	Day 10	2
  28	GACGT	Day 5 GFP neg	2
  31	GACTG	Day 5 GFP pos	2
  33	GAGAA	Day 2	3
  40	GAGCT	Day 10	3
  ...
  
**Specify Barcode and Hairpin Locations (FastQ Input):**

It is assumed that in the sequencing reads that the first 5 bases are the
barcodes and that bases 37-57 are the hairpins. If this is not the case then the
values of the positions can be changed, however it still requires the barcodes
and hairpins to be in a consistent location an in a continuous sequence.

**Filter Low CPM?:**

Often in a large screen there may members with very low counts which are of no
interest in the experiment, these may be filtered out to speed up computations.
Filtering will be based on counts per million in a required number of samples.

**Analysis Type:**

 * **Classic Exact Test:** This allows two experimental groups to be compared and
   p-values for differential representation derivec for each hairpin. Simple and
   fast for straightforward comparisons. In this option you will have the option of
   "*Compare* x *To* y" which implicitly subtracts the data from y from that of x
   to produce the comparison.

 * **Generalised Linear Model:** This allow for complex contrasts to be specified
   and also gene level analysis to be performed. If this option is chosen then
   contrasts must be explicitly stated in equations and multiple contrasts can be
   made. In addition there will be the option to analyse hairpins on a per-gene
   basis to see if hairpins belonging to a particular gene have any overall
   tendencies for the direction of their log-fold-change.

**FDR Threshold:**
The smear plot in the output will have hairpins highlighted to signify
significant differential representation. The significance is determined by
contorlling the false discovery rate, only those with a FDR lower than the
threshold will be highlighted in the plot.

-----

**Citations:**

.. class:: infomark

limma

Please cite the paper below for the limma software itself.  Please also try
to cite the appropriate methodology articles that describe the statistical
methods implemented in limma, depending on which limma functions you are
using.  The methodology articles are listed in Section 2.1 of the limma 
User's Guide.

	* Smyth, GK (2005). Limma: linear models for microarray data. In: 
	  'Bioinformatics and Computational Biology Solutions using R and 
	  Bioconductor'. R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, 
	  W. Huber (eds), Springer, New York, pages 397-420.

.. class:: infomark

edgeR

Please cite the first paper for the software itself and the other papers for
the various original statistical methods implemented in edgeR.  See 
Section 1.2 in the User's Guide for more detail.

	* Robinson MD, McCarthy DJ and Smyth GK (2010). edgeR: a Bioconductor 
	  package for differential expression analysis of digital gene expression 
	  data. Bioinformatics 26, 139-140
	  
	* Robinson MD and Smyth GK (2007). Moderated statistical tests for assessing 
	  differences in tag abundance. Bioinformatics 23, 2881-2887
	  
	* Robinson MD and Smyth GK (2008). Small-sample estimation of negative 
	  binomial dispersion, with applications to SAGE data.
	  Biostatistics, 9, 321-332
	  
	* McCarthy DJ, Chen Y and Smyth GK (2012). Differential expression analysis 
	  of multifactor RNA-Seq experiments with respect to biological variation. 
	  Nucleic Acids Research 40, 4288-4297

.. _edgeR: http://www.bioconductor.org/packages/release/bioc/html/edgeR.html
.. _limma: http://www.bioconductor.org/packages/release/bioc/html/limma.html
  </help>
</tool>