Methods for Identifying Differentially Expressed Genes: An Empirical Comparison
نویسندگان
چکیده
منابع مشابه
Multivariate methods for identifying differentially expressed genes
Motivation: Univariate testing procedures remain the most common way to identify differentially expressed genes (DEGs). Univariate techniques suffer from the multiple comparison problem and reduced power, because they fail to account for gene interaction. Motivated by these issues, we adopt a multivariate procedure. Namely, we utilize the sup-norm test, which was specifically developed for high...
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Microarray is a recently developed functional genomic technology that has powerful applications in a wide array of biological research areas, including the medical sciences, agriculture, biotechnology and environmental studies. One of the important problems in the analysis of microarray data is the identification of differentially expressed genes. Commonly used approaches for identifying differ...
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Identification of genes differentially expressed across multiple conditions has become an important statistical problem in analyzing large-scale microarray data. Many statistical methods have been developed to address the challenging problem. Therefore, an extensive comparison among these statistical methods is extremely important for experimental scientists to choose a valid method for their d...
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In this vignette, we show how the functions contained in the R package siggenes can be used to perform both the Significance Analysis of Microarrays (SAM) proposed by Tusher et al. (2001) and the Empirical Bayes Analysis of Microarrays (EBAM) suggested by Efron et al. (2001).
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ژورنال
عنوان ژورنال: Journal of Biometrics & Biostatistics
سال: 2015
ISSN: 2155-6180
DOI: 10.4172/2155-6180.1000265