@Manual{R,
title = {R: A language and environment for statistical computing},
author = {{R Development Core Team}},
organization = {R Foundation for Statistical Computing},
address = {Vienna, Austria},
year = {2005},
note = {{ISBN} 3-900051-07-0},
url = {http://www.R-project.org},
}

@Manual{AFE,
title = {Agilent Feature Extraction Reference Guide},
organization = {Agilent},
year = {2007},
url = {http://www.Agilent.com},
}

@Article{GSEA,
author = {Aravind Subramanian and Pablo Tamayo and Vamsi K Mootha and Sayan
    Mukherjee and Benjamin L Ebert and Michael A Gillette and Amanda
    Paulovich and Scott L Pomeroy and Todd R Golub and Eric S Lander
    and Jill P Mesirov},
title = {Gene set enrichment analysis: a knowledge-based approach for interpreting
    genome-wide expression profiles.},
journal = {Proc Natl Acad Sci U S A},
year = {2005},
volume = {102},
pages = {15545--15550},
number = {43},
month = {Oct},
abstract = {Although genomewide RNA expression analysis has become a routine tool
    in biomedical research, extracting biological insight from such information
    remains a major challenge. Here, we describe a powerful analytical
    method called Gene Set Enrichment Analysis (GSEA) for interpreting
    gene expression data. The method derives its power by focusing on
    gene sets, that is, groups of genes that share common biological
    function, chromosomal location, or regulation. We demonstrate how
    GSEA yields insights into several cancer-related data sets, including
    leukemia and lung cancer. Notably, where single-gene analysis finds
    little similarity between two independent studies of patient survival
    in lung cancer, GSEA reveals many biological pathways in common.
    The GSEA method is embodied in a freely available software package,
    together with an initial database of 1,325 biologically defined gene
    sets.},
doi = {10.1073/pnas.0506580102},
institution = {Broad Institute of Massachusetts Institute of Technology and Harvard,
    320 Charles Street, Cambridge, MA 02141, USA.},
keywords = {Cell Line, Tumor; Female; Gene Expression Profiling; Genes, p53; Genome;
    Humans; Leukemia, Myeloid, Acute; Lung Neoplasms; Male; Oligonucleotide
    Array Sequence Analysis; Precursor Cell Lymphoblastic Leukemia-Lymphoma},
owner = {diez},
pii = {0506580102},
pmid = {16199517},
timestamp = {2008.07.14},
url = {http://dx.doi.org/10.1073/pnas.0506580102}
}

@inbook{Bold3,
title = {Quality Assesement of Affymetrix GeneChip Data},
author = {Bolstad, B. and Collin, F. and Brettschneider, J. and Simpson, K. and Cope, L. and Irizarry, R. and Speed, T.P.},
booktitle = {Bioinformatics and Computational Biology Solutions using R and Bioconductor},
editor = {Robert Gentleman, Vincent J Carey, Wolfgang Huber, Rafael A Irizarry, Sandrine Dudoit},
publisher = {Springer},
address = {New York},
year = {2005},
pages = {397--420},
url = {http://dx.doi.org/10.1007/0-387-29362-0_3},
}

@inbook{limma,
title = {Limma: linear models for microarray data},
author = {Gordon K Smyth},
booktitle = {Bioinformatics and Computational Biology Solutions using R and Bioconductor},
editor = {R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, W. Huber},
publisher = {Springer},
address = {New York},
year = {2005},
pages = {397--420},
}
