Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Motivation: The need for normalization in microarray experiments has been ll documented in the literature. Currently, many analysis methods treat normalization and analysis as a series of steps, with summarized data carried forward to the next step.#R##N##R##N#Results:  present a unified algorithm which incorporates normalization and class comparison in one analysis using probe level perfect match and mismatch data. The algorithm is based on calibration models common to most biological assays, and the resulting chip-specific parameters have a natural interpretation.  show that the algorithm fits into the statistical generalized linear models framework, describe a practical fitting strategy and present results of the algorithm applied to an example dataset as ll as based on metrics used in affycomp. The algorithm ranks amongst the top third of the affycomp competitors, performing best in measures of bias.#R##N##R##N#Availability: R functions are available on request from the authors.#R##N##R##N#Contact: oberg.ann@mayo.edu
['Ann L. Oberg', 'Douglas W. Mahoney', 'Karla V. Ballman', 'Terry M. Therneau']
I am writing a research paper on a idea Joint estimation of calibration and expression for high-density oligonucleotide arrays
[{"from": "human", "value": "I am writing a research paper on a idea Joint estimation of calibration and expression for high-density oligonucleotide arrays"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Motivation: The need for normalization in microarray experiments has been ll documented in the literature. Currently, many analysis methods treat normalization and analysis as a series of steps, with summarized data carried forward to the next step.#R##N##R##N#Results:  present a unified algorithm which incorporates normalization and class comparison in one analysis using probe level perfect match and mismatch data. The algorithm is based on calibration models common to most biological assays, and the resulting chip-specific parameters have a natural interpretation.  show that the algorithm fits into the statistical generalized linear models framework, describe a practical fitting strategy and present results of the algorithm applied to an example dataset as ll as based on metrics used in affycomp. The algorithm ranks amongst the top third of the affycomp competitors, performing best in measures of bias.#R##N##R##N#Availability: R functions are available on request from the authors.#R##N##R##N#Contact: oberg.ann@mayo.edu"}]