<tool id="rgEigPCA1" name="Eigensoft:">
    <description>PCA Ancestry using SNP</description>

    <command interpreter="python">
    rgEigPCA.py "$i.extra_files_path/$i.metadata.base_name" "$title" "$out_file1"
    "$out_file1.files_path" "$k" "$m" "$t" "$s" "$pca"
    </command>

    <inputs>

       <param name="i"  type="data" label="Input genotype data file"
          size="120" format="ldindep" />
       <param name="title"  type="text" value="Ancestry PCA" label="Title for outputs from this run"
          size="80"  />
       <param name="k"  type="integer" value="4" label="Number of principal components to output"
          size="3"  />
       <param name="m"  type="integer" value="0" label="Max. outlier removal iterations"
          help="To turn on outlier removal, set m=5 or so. Do this if you plan on adjusting any analyses"
          size="3"  />
       <param name="t"  type="integer" value="5" label="# principal components used for outlier removal"
          size="3"  />
       <param name="s"  type="integer" value="6" label="#SDs for outlier removal"
          help = "Any individual with SD along one of k top principal components > s will be removed as an outlier."
          size="3"  />

   </inputs>

   <outputs>
       <data name="out_file1" format="html" label="${title}_rgEig.html"/>
       <data name="pca" format="txt" label="${title}_rgEig.txt"/>
   </outputs>

<tests>
 <test>
   <param name='i' value='tinywga' ftype='ldindep' >
   <metadata name='base_name' value='tinywga' />
   <composite_data value='tinywga.bim' />
   <composite_data value='tinywga.bed' />
   <composite_data value='tinywga.fam' />
   <edit_attributes type='name' value='tinywga' /> 
   </param>
    <param name='title' value='rgEigPCAtest1' />
    <param name="k" value="4" />
    <param name="m" value="2" />
    <param name="t" value="2" />
    <param name="s" value="2" />
    <output name='out_file1' file='rgtestouts/rgEigPCA/rgEigPCAtest1.html' ftype='html' compare='diff' lines_diff='195'>
    <extra_files type="file" name='rgEigPCAtest1_PCAPlot.pdf' value="rgtestouts/rgEigPCA/rgEigPCAtest1_PCAPlot.pdf" compare="sim_size" delta="3000"/>
    </output>
    <output name='pca' file='rgtestouts/rgEigPCA/rgEigPCAtest1.txt' compare='diff'/>
 </test>
</tests>

<help>


**Syntax**

- **Genotype data** is an input genotype dataset in Plink lped (http://pngu.mgh.harvard.edu/~purcell/plink/data.shtml) format. See below for notes
- **Title** is used to name the output files so you can remember what the outputs are for
- **Tuning parameters** are documented in the Eigensoft (http://genepath.med.harvard.edu/~reich/Software.htm) documentation - see below 


-----

**Summary**

Eigensoft requires ld-reduced genotype data. 
Galaxy has an automatic converter for genotype data in Plink linkage pedigree (lped) format.
For details of this generic genotype format, please see the Plink documentation at 
http://pngu.mgh.harvard.edu/~purcell/plink/data.shtml

Reading that documentation, you'll see that the linkage pedigree format is really two related files with the same 
file base name - a map and ped file - eg 'mygeno.ped' and 'mygeno.map'.
The map file has the chromosome, offset, genetic offset and snp name corresponding to each
genotype stored as separate alleles in the ped file. The ped file has family id, individual id, father id (or 0), mother id
(or 0), gender (1=male, 2=female, 0=unknown) and affection (1=unaffected, 2=affected, 0=unknown), 
then two separate allele columns for each genotype. 

Once you have your data in the right format, you can upload those into your Galaxy history using the "upload" tool.

To upload your lped data in the upload tool, choose 'lped' as the 'file format'. The tool form will change to 
allow you to navigate to and select each member of the pair of  ped and map files stored on your local computer
(or available at a public URL for Galaxy to grab). 
Give the dataset a meaningful name (replace rgeneticsData with something more useful!) and click execute. 

When the upload is done, your new lped format dataset will appear in your history and then, 
when you choose the ancestry tool, that history dataset will be available as input.

**Warning for the Impatient**

When you execute the tool, it will look like it has not started running for a while as the automatic converter 
reduces the amount of LD - otherwise eigenstrat gives biased results.


**Attribution**

This tool runs and relies on the work of many others, including the
maintainers of the Eigensoft program, and the R and
Bioconductor projects. For full attribution, source code and documentation, please see
http://genepath.med.harvard.edu/~reich/Software.htm, http://cran.r-project.org/
and http://www.bioconductor.org/ respectively

This implementation is a Galaxy tool wrapper around these third party applications.
It was originally designed and written for family based data from the CAMP Illumina run of 2007 by
ross lazarus (ross.lazarus@gmail.com) and incorporated into the rgenetics toolkit.

copyright Ross Lazarus 2007
Licensed under the terms of the LGPL as documented http://www.gnu.org/licenses/lgpl.html
but is about as useful as a sponge boat without EIGENSOFT pca code.

**README from eigensoft2 distribution at http://genepath.med.harvard.edu/~reich/Software.htm**

[rerla@beast eigensoft2]$ cat README
EIGENSOFT version 2.0, January 2008 (for Linux only)

This is the same as our EIGENSOFT 2.0 BETA release with a few recent changes
as described at http://genepath.med.harvard.edu/~reich/New_In_EIGENSOFT.htm.

Features of EIGENSOFT version 2.0 include:
-- Keeping track of ref/var alleles in all file formats: see CONVERTF/README
-- Handling data sets up to 8 billion genotypes: see CONVERTF/README
-- Output SNP weightings of each principal component: see POPGEN/README

The EIGENSOFT package implements methods from the following 2 papers:
Patterson N. et al. 2006 PLoS Genetics in press (population structure)
Price A.L. et al. 2006 NG 38:904-9 (EIGENSTRAT stratification correction)

See POPGEN/README for documentation of population structure programs.

See EIGENSTRAT/README for documentation of EIGENSTRAT programs.

See CONVERTF/README for documentation of programs for converting file formats.


Executables and source code:
----------------------------
All C executables are in the bin/ directory.

We have placed source code for all C executables in the src/ directory,
for users who wish to modify and recompile our programs.  For example, to
recompile the eigenstrat program, type
"cd src"
"make eigenstrat"
"mv eigenstrat ../bin"

Note that some of our software will only compile if your system has the
lapack package installed.  (This package is used to compute eigenvectors.)
Some users may need to change "blas-3" to "blas" in the Makefile,
depending on how blas and lapack are installed.

If cc is not available on your system, try "cp Makefile.alt Makefile"
and then recompile.

If you have trouble compiling and running our code, try compiling and
running the pcatoy program in the src directory:
"cd src"
"make pcatoy"
"./pcatoy"
If you are unable to run the pcatoy program successfully, please contact
your system administrator for help, as this is a systems issue which is
beyond our scope.  Your system administrator will be able to troubleshoot
your systems issue using this trivial program.  [You can also try running
the pcatoy program in the bin directory, which we have already compiled.]
</help>
</tool>