AbstractBreitling et al. (2004) [1] introduced a statistical technique, the rank product method, for detecting differentially regulated genes in replicated microarray experiments. The technique has achieved widespread acceptance and is now used more broadly, in such diverse fields as RNAi analysis, proteomics, and machine learning. In this note, we extend the rank product method to the two sample setting, provide distribution theory attending the rank product method in this setting, and give numerical details for implementing the method
This paper proposes a novel ranking function, called RFHOS by incorporating higher order cumulants i...
The Significance Analysis of Microarrays (SAM) software is a very practical tool for detecting signi...
With the introduction of omics-technologies such as transcriptomics and proteomics, numerous methods...
AbstractBreitling et al. [1] introduced a statistical technique, the rank product method, for detect...
AbstractThe rank product method is a widely accepted technique for detecting differentially regulate...
AbstractOne of the main objectives in the analysis of microarray experiments is the identification o...
The rank product method is a widely accepted technique for detecting differentially regulated genes ...
We have recently introduced a rank-based test statistic, RankProducts (RP), as a new non-parametric ...
The rank product statistic has been widely used to detect differentially expressed genes in replicat...
Contains fulltext : 175881.pdf (publisher's version ) (Open Access)Motivation: The...
Abstract Motivation: The Rank Product (RP) is a statistical technique widely used to detect differen...
Abstract Background The first objective of a DNA microarray experiment is typically to generate a li...
The ability to analyze gene expression data has had a fundamental impact in the biological sciences ...
Motivation: The proliferation of public data repositories creates a need for meta-analysis methods t...
Summary: While meta-analysis provides a powerful tool for analyzing microarray experiments by combin...
This paper proposes a novel ranking function, called RFHOS by incorporating higher order cumulants i...
The Significance Analysis of Microarrays (SAM) software is a very practical tool for detecting signi...
With the introduction of omics-technologies such as transcriptomics and proteomics, numerous methods...
AbstractBreitling et al. [1] introduced a statistical technique, the rank product method, for detect...
AbstractThe rank product method is a widely accepted technique for detecting differentially regulate...
AbstractOne of the main objectives in the analysis of microarray experiments is the identification o...
The rank product method is a widely accepted technique for detecting differentially regulated genes ...
We have recently introduced a rank-based test statistic, RankProducts (RP), as a new non-parametric ...
The rank product statistic has been widely used to detect differentially expressed genes in replicat...
Contains fulltext : 175881.pdf (publisher's version ) (Open Access)Motivation: The...
Abstract Motivation: The Rank Product (RP) is a statistical technique widely used to detect differen...
Abstract Background The first objective of a DNA microarray experiment is typically to generate a li...
The ability to analyze gene expression data has had a fundamental impact in the biological sciences ...
Motivation: The proliferation of public data repositories creates a need for meta-analysis methods t...
Summary: While meta-analysis provides a powerful tool for analyzing microarray experiments by combin...
This paper proposes a novel ranking function, called RFHOS by incorporating higher order cumulants i...
The Significance Analysis of Microarrays (SAM) software is a very practical tool for detecting signi...
With the introduction of omics-technologies such as transcriptomics and proteomics, numerous methods...