A single-sample microarray normalization method to facilitate personalized-medicine workflows.

[1]  J. Kleinman,et al.  Spatiotemporal transcriptome of the human brain , 2011, Nature.

[2]  Benjamin J. Raphael,et al.  Integrated Genomic Analyses of Ovarian Carcinoma , 2011, Nature.

[3]  Michael R Stratton,et al.  Genomics and the continuum of cancer care. , 2011, The New England journal of medicine.

[4]  Dennis B. Troup,et al.  NCBI GEO: archive for functional genomics data sets—10 years on , 2010, Nucleic Acids Res..

[5]  Björn Usadel,et al.  Algorithm-driven Artifacts in median polish summarization of Microarray data , 2010, BMC Bioinformatics.

[6]  David M. Simcha,et al.  Tackling the widespread and critical impact of batch effects in high-throughput data , 2010, Nature Reviews Genetics.

[7]  Joel Greshock,et al.  Molecular target class is predictive of in vitro response profile. , 2010, Cancer research.

[8]  Rafael A Irizarry,et al.  Frozen robust multiarray analysis (fRMA). , 2010, Biostatistics.

[9]  D. Hayes,et al.  Prospective multicenter study of the impact of the 21-gene recurrence score assay on medical oncologist and patient adjuvant breast cancer treatment selection. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[10]  Kai Wang,et al.  Comparative analysis of microarray normalization procedures: effects on reverse engineering gene networks , 2007, ISMB/ECCB.

[11]  Yi Xing,et al.  Exon arrays provide accurate assessments of gene expression , 2007, Genome Biology.

[12]  Paul A Clemons,et al.  The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease , 2006, Science.

[13]  J. Nevins,et al.  Linking oncogenic pathways with therapeutic opportunities , 2006, Nature Reviews Cancer.

[14]  Clifford A. Meyer,et al.  Model-based analysis of tiling-arrays for ChIP-chip , 2006, Proceedings of the National Academy of Sciences.

[15]  R. Myers,et al.  Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data , 2005, Nucleic acids research.

[16]  M. Cronin,et al.  A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. , 2004, The New England journal of medicine.

[17]  Rafael A. Irizarry,et al.  A Model-Based Background Adjustment for Oligonucleotide Expression Arrays , 2004 .

[18]  Benjamin M. Bolstad,et al.  affy - analysis of Affymetrix GeneChip data at the probe level , 2004, Bioinform..

[19]  T. Speed,et al.  Summaries of Affymetrix GeneChip probe level data. , 2003, Nucleic acids research.

[20]  Wei-Min Liu,et al.  Robust estimators for expression analysis , 2002, Bioinform..

[21]  Yudong D. He,et al.  Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.

[22]  R. Spang,et al.  Predicting the clinical status of human breast cancer by using gene expression profiles , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[23]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[24]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[25]  Jeffrey T. Chang,et al.  A pharmacogenomic method for individualized prediction of drug sensitivity. , 2011, Molecular systems biology.

[26]  F. Monzon A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast Cancer , 2006 .