Open Access
The Integrative Correlation Coefficient: a Measure of Cross-study
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The article was published on 2007-01-01 and is currently open access. It has received 6 citations till now. The article focuses on the topics: Measure (physics) & Correlation coefficient.read more
Citations
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Journal ArticleDOI
Batch effect removal methods for microarray gene expression data integration: a survey
Cosmin Lazar,Stijn Meganck,Jonatan Taminau,David Steenhoff,Alain Coletta,Colin Molter,David Y. Weiss-Solis,Robin Duque,Hugues Bersini,Ann Nowé +9 more
TL;DR: Methods designed to combine genomic data recorded from microarray gene expression (MAGE) experiments are reviewed in a unified framework together with a wide range of evaluation tools, which are mandatory in assessing the efficiency and the quality of the data integration process.
Journal ArticleDOI
Merging two gene-expression studies via cross-platform normalization
TL;DR: The proposed normalization method is applied to three existing breast cancer datasets, and is compared to several competing normalization methods using the proposed validation measures.
Journal ArticleDOI
Large scale comparison of global gene expression patterns in human and mouse
TL;DR: The results indicate that the global patterns of tissue-specific expression of orthologous genes are conserved in human and mouse.
Detecting, correcting, and preventing the batch effects in multi-site data, with a focus on gene expression Microarrays
TL;DR: This thesis proposes an efficient algorithm to extend the single-study variance-based gene selection method to a multi-study gene selection algorithm and empirical results show this feature selection algorithm outperforms other algorithms in reducing the destructive influence of batch effects.
Detection of Low Rank Signals in Noise and Fast Correlation Mining with Applications to Large Biological Data
TL;DR: A new method is proposed, called FastMap, that exploits the discreteness of SNPs, and uses a permutation approach to account for multiple comparisons in the analysis of biomedical data.
References
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Journal ArticleDOI
Batch effect removal methods for microarray gene expression data integration: a survey
Cosmin Lazar,Stijn Meganck,Jonatan Taminau,David Steenhoff,Alain Coletta,Colin Molter,David Y. Weiss-Solis,Robin Duque,Hugues Bersini,Ann Nowé +9 more
TL;DR: Methods designed to combine genomic data recorded from microarray gene expression (MAGE) experiments are reviewed in a unified framework together with a wide range of evaluation tools, which are mandatory in assessing the efficiency and the quality of the data integration process.
Journal ArticleDOI
Merging two gene-expression studies via cross-platform normalization
TL;DR: The proposed normalization method is applied to three existing breast cancer datasets, and is compared to several competing normalization methods using the proposed validation measures.
Journal ArticleDOI
Large scale comparison of global gene expression patterns in human and mouse
TL;DR: The results indicate that the global patterns of tissue-specific expression of orthologous genes are conserved in human and mouse.
Journal ArticleDOI
Comparing cDNA and oligonucleotide array data: concordance of gene expression across platforms for the NCI-60 cancer cells
Jae K. Lee,Jae K. Lee,Kimberly J. Bussey,Fuad G. Gwadry,William C. Reinhold,Gregory Riddick,Sandra L. Pelletier,Satoshi Nishizuka,Gergely Szakács,Jean Phillipe Annereau,Uma Shankavaram,Samir Lababidi,Lawrence H. Smith,Michael M. Gottesman,John N. Weinstein +14 more
TL;DR: The result described here for the NCI-60 cancer cell lines is a consensus set of genes that give similar profiles on spotted cDNA arrays and Affymetrix oligonucleotide chips.
Journal ArticleDOI
MergeMaid: R tools for merging and cross-study validation of gene expression data.
TL;DR: An R package and associated object definitions are developed to merge and visualize multiple gene expression datasets that use arbitrary character IDs and generate objects that can efficiently support a variety of joint analyses.