Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Motivation: An important object in the analysis of high-throughput genomic data is to find an association beten the expression profile of functional gene sets and the different levels of a group response. Instead of multiple testing procedures which focus on single genes, global tests are usually used to detect a group effect in an entire gene set. In a simulation study,  compare the por and computation times of four different approaches for global testing. The applicability of one of these methods to gene expression data is demonstrated for the first time. In addition,  propose an algorithm for the detection of those genes which might be responsible for a group effect.#R##N##R##N#Results:  could detect that the por of three of the approaches is comparable in many settings but considerable differences re detected in the computation times. Our proposed gene selection algorithm was able to detect potentially effect-causing genes in artificial sets with high por when many genes re altered with a small effect, while classical multiple testing was more porful when few genes re altered with a large effect.#R##N##R##N#Availability: An R-package called ‘RepeatedHighDim’ which implements our new global test procedures is made available from http://cran.r-project.org/.#R##N##R##N#Contact: tim.beissbarth@ams.med.uni-goettingen.de#R##N##R##N#Supplementary information:Supplementary data are available at Bioinformatics online.
['Klaus Jung', 'Benjamin Becker', 'Edgar Brunner', 'Tim Beißbarth']
I am writing a research paper on a idea Comparison of global tests for functional gene sets in two-group designs and selection of potentially effect-causing genes
[{"from": "human", "value": "I am writing a research paper on a idea Comparison of global tests for functional gene sets in two-group designs and selection of potentially effect-causing genes"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Motivation: An important object in the analysis of high-throughput genomic data is to find an association beten the expression profile of functional gene sets and the different levels of a group response. Instead of multiple testing procedures which focus on single genes, global tests are usually used to detect a group effect in an entire gene set. In a simulation study,  compare the por and computation times of four different approaches for global testing. The applicability of one of these methods to gene expression data is demonstrated for the first time. In addition,  propose an algorithm for the detection of those genes which might be responsible for a group effect.#R##N##R##N#Results:  could detect that the por of three of the approaches is comparable in many settings but considerable differences re detected in the computation times. Our proposed gene selection algorithm was able to detect potentially effect-causing genes in artificial sets with high por when many genes re altered with a small effect, while classical multiple testing was more porful when few genes re altered with a large effect.#R##N##R##N#Availability: An R-package called \u2018RepeatedHighDim\u2019 which implements our new global test procedures is made available from http://cran.r-project.org/.#R##N##R##N#Contact: tim.beissbarth@ams.med.uni-goettingen.de#R##N##R##N#Supplementary information:Supplementary data are available at Bioinformatics online."}]