Strategies for aggregating gene expression data: The collapseRows R function
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Daniel R. Salomon | Peter Langfelder | Steve Horvath | Daniel H. Geschwind | Jeremy A. Miller | Chaochao Cai | Sunil M. Kurian | S. Horvath | D. Geschwind | Jeremy A. Miller | Chaochao Cai | P. Langfelder | D. Salomon | S. Kurian
[1] Peter A C 't Hoen,et al. Coexpression network analysis identifies transcriptional modules related to proastrocytic differentiation and sprouty signaling in glioma. , 2010, Cancer research.
[2] S. Horvath,et al. Functional organization of the transcriptome in human brain , 2008, Nature Neuroscience.
[3] Bin Zhang,et al. Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R , 2008, Bioinform..
[4] A. Butte,et al. AILUN: reannotating gene expression data automatically , 2007, Nature Methods.
[5] Steve Horvath,et al. WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.
[6] G. Pertea,et al. RESOURCERER: a database for annotating and linking microarray resources within and across species , 2001, Genome Biology.
[7] Jun Dong,et al. Geometric Interpretation of Gene Coexpression Network Analysis , 2008, PLoS Comput. Biol..
[8] Aleksey A. Nakorchevskiy,et al. Expression deconvolution: A reinterpretation of DNA microarray data reveals dynamic changes in cell populations , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[9] Peter Langfelder,et al. Weighted gene co-expression network analysis of the peripheral blood from Amyotrophic Lateral Sclerosis patients , 2009, BMC Genomics.
[10] P. Flicek,et al. Consistent annotation of gene expression arrays , 2010, BMC Genomics.
[11] Damien Chaussabel,et al. Genomic transcriptional profiling identifies a candidate blood biomarker signature for the diagnosis of septicemic melioidosis , 2009, Genome Biology.
[12] Alistair Rogers,et al. Connecting genes, coexpression modules, and molecular signatures to environmental stress phenotypes in plants , 2008, BMC Systems Biology.
[13] Z. Modrušan,et al. Deconvolution of Blood Microarray Data Identifies Cellular Activation Patterns in Systemic Lupus Erythematosus , 2009, PloS one.
[14] Jennifer Clarke,et al. Statistical expression deconvolution from mixed tissue samples , 2010, Bioinform..
[15] L. Almasy,et al. Discovery of expression QTLs using large-scale transcriptional profiling in human lymphocytes , 2007, Nature Genetics.
[16] Peter Langfelder,et al. Eigengene networks for studying the relationships between co-expression modules , 2007, BMC Systems Biology.
[17] Jill P. Mesirov,et al. GeneCruiser: a web service for the annotation of microarray data , 2005, Bioinform..
[18] S. Horvath,et al. Statistical Applications in Genetics and Molecular Biology , 2011 .
[19] D. Geschwind,et al. Genome-wide analyses of human perisylvian cerebral cortical patterning , 2007, Proceedings of the National Academy of Sciences.
[20] S. Horvath,et al. Conservation and evolution of gene coexpression networks in human and chimpanzee brains , 2006, Proceedings of the National Academy of Sciences.
[21] J. Cerhan,et al. Gene networks and microRNAs implicated in aggressive prostate cancer. , 2009, Cancer research.
[22] J. Wang-Rodriguez,et al. In silico dissection of cell-type-associated patterns of gene expression in prostate cancer. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[23] Gregory Nuel,et al. Deciphering Normal Blood Gene Expression Variation—The NOWAC Postgenome Study , 2010, PLoS genetics.
[24] Jian Huang,et al. Incorporating higher-order representative features improves prediction in network-based cancer prognosis analysis , 2011, BMC Medical Genomics.
[25] G. Church,et al. Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae , 2001, Nature Genetics.
[26] Haiyan Hu,et al. Integrative Array Analyzer: a software package for analysis of cross-platform and cross-species microarray data , 2006, Bioinform..
[27] T. Nikolcheva,et al. Deconvoluting Post-Transplant Immunity: Cell Subset-Specific Mapping Reveals Pathways for Activation and Expansion of Memory T, Monocytes and B Cells , 2010, PloS one.
[28] S. Horvath,et al. Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathways , 2010, Proceedings of the National Academy of Sciences.
[29] R. Myers,et al. Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data , 2005, Nucleic acids research.
[30] BMC Bioinformatics , 2005 .