Visualization of the data was accomplished using the ReadXplorer double track viewer [ 87] and the Integrated Genomics Viewer (IGV) [ 88], enabling direct comparison of the different alignments of each strain (including SNPs) to the JGI reference.
Pre-processing and normalization of data were accomplished using the R-project statistical environment [ 68] and Bioconductor [ 69] through the GenePix AutoProcessor (GPAP) [ 70].
Analysis of the questionnaire data was accomplished using R statistical package R 2.10.1 (The R Project for Statistical Computing, 2009. http://www.r-project.org/).org/
Technical validation of the array data was accomplished using a series of 38 of the advanced stage cancers that were analyzed using the DASL platform from Illumina.
Behavioral time-tagging of all events and analysis of the spike data was accomplished using a CED 1401 plus system (Cambridge Electronic Design Limited, Cambridge, United Kingdom) and CED Spike 2 software.
Non-specific GUS and luciferase activity was corrected, and normalization of the MUG data was accomplished using luciferase activity as previously described [ 62].
Validation of the gene predictions using the RNA-Seq data was accomplished using Cufflinks [ 54] (-I 3000 --min-intron-length 20 --max-bundle-length 35000).
Manual filter hit-calling and deconvolution of the multi-dimensional pool hybridization data was accomplished using HybDecon, open source software available at http://www.genome.clemson.edu/software/hybdecon.edu/software/hybdecon
The sharing and discovery of scientific data is accomplished using a virtual database focused on metadata and designed specifically to store geospatial information.
De novo assembly of high quality data was accomplished using the CLC Genomics workbench 6.0 (Qiagen, USA) at default parameters (minimum contig length: 200, automatic word size: yes, perform scaffolding: yes, mismatch cost: 2, insertion cost: 3, deletion cost: 3, length fraction: 0.5, similarity fraction: 0.8).
