= Illumina SNP Normalization =

tQN is a strategy using quantile normalization to improve the quality of data from Illumina Infinium Whole-Genome Genotyping SNP Beadchips described in

''Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios'' [[BR]] 
J. Staaf, J. Vallon-Christersson, D. Lindgren, G. Juliusson, R. Rosenquist, M. Höglund, Å. Borg, M. Ringnér [[BR]] 
''submitted'' [[BR]]

=== License ===
The tQN software is available as a stand-alone software package, and will become available as
as a plug-in to BASE as the handling of SNP arrays in BASE is developed. Both versions are available under the [http://www.gnu.org/copyleft/gpl.html GNU General Public License].

=== Download tQN ===

The software will be made available when the manuscript describing the method is accepted for publication.

=== How to use tQN ===

''Requirements''
  tQN is written in R with a Perl wrapper, so both R and Perl are required. Required Perl modules are: File::Spec, Getopt::Long, IO::File and Pod::Usage (http://www.cpan.org). Required R package is limma (http://www.bioconductor.org).

''Installation''
  Download and unzip the file available under the section ''Download tQN'' on this page.

  OS X or Linux:
  The programs should run as they are. You need R and perl in your path.

  Windows:
  Depending on how you have installed R and Perl on your system you may have to edit the variables ''$R_command'' and ''$R_windows'' at the beginning of the file ''tQN_normalize_samples.pl''. ''$R_windows'' should likely contain the full path to the R interpreter on your system. Also comment out (with an initial #) the ''$R_command'' used on OS X and Linux systems. For example, we have successfully used tQN using !ActivePerl on a Windows system with the following ''$R_windows'':
  {{{
  # Mac OS X and Linux
  # my $R_command="R --vanilla --no-save --slave < tQN.R";
  # Windows
  my $R_windows=File::Spec->canonpath('C:/"Program Files"/R/R-2.7.0/bin/Rscript');
  my $R_command="$R_windows --vanilla tQN.R";
  }}}
  

''Input data format''
  tQN is applied to data exported from !BeadStudio. For a set of samples, the file exported from !BeadStudio should be tab-delimited in the following format:
  ||Name||Chr||Position||sample1.X||sample1.Y||sample2.X||sample2.Y||sample3.X||sample3.Y||...|| 
  ||rs12354060||1||10004||0.04424883||1.818238||0.03157751||1.632767||0.04973672||1.770216||...||
  ||rs2691310||1||46844||0.7046126||1.305445||0.8322142||1.271329||0.8042333||1.151523||...||
  ||...||...||...||...||...||...||...||...||...||...|

  The data extracted from !BeadStudio needs to be split into a separate file for each sample using the script ''split_beadstudio_samples.pl''.

  {{{  
    perl split_beadstudio_samples.pl --beadstudio_file=example/example_beadstudio_data.txt
  }}}
  where ''example_beadstudio_data.txt'' is a file exported from !BeadStudio in the format described above.

  This script will generate one file per sample together with a file ''sample_names.txt'' in the tQN subdirectory ''extracted''. These files are used when tQN is run and can be deleted once the samples are normalized.

''Performing tQN''

  In the tQN directory, run tQN with the following command:

  {{{  
     perl tQN_normalize_samples.pl --beadchip=humancnv370-duo
  }}}

  This command will perform tQN on the samples in the tQN subdirectory ''extracted'' that are specified in the file ''sample_names.txt''. If you want to perform tQN on a subset of samples you can edit ''sample_names.txt'' accordingly. The normalized data is stored in the tQN subdirectory ''normalized''. For each sample, there is a file with tQN normalized data. A file ''tQN_beadstudio.txt'' is also generated with tQN BAF and Log R Ratios for all samples in a format suitable for import into !BeadStudio using its import column process. tQN also supports generating tQN data for further analysis with PennCNV and QuantiSNP. Running tQN with the following command:

  {{{  
     perl tQN_normalize_samples.pl --beadchip=humancnv370-duo --output_format=PennCNV
  }}}

  generates one data file per sample in the tQN subdirectory ''normalized'' for further analysis using PennCNV. Alternatives for ''--output_format'' are ''QuantiSNP'', which generates one data file per sample for further analysis with QuantiSNP and ''!BeadStudio'', which is the default argument generating the default ''tQN_beadstudio.txt'' file with data for all samples. Beadchip types for which there is a cluster file in the tQN subdirectory ''lib'' are supported by tQN and can be used as alternatives for ''--beadchip''. For PennCNV and QuantiSNP, SNPs having missing values in either B allele frequencies or log R ratios after normalization are excluded from the respective output files. 
   

''Other information''

  CNV probes are not normalized by tQN; for these probes the original X and Y intensities from !BeadStudio are kept. tQN may result in a slightly smaller number of SNPs having data. The reason for this reduction is that some SNPs have not been genotyped in the !HapMap samples used to generate the cluster files. tQN cluster files for additional beadchip types can be generated upon request.

=== Contact ===

If you have suggestions, comments or bug reports, please send an email to johan.staaf@med.lu.se