Evaluating methods for ranking differentially expressed genes applied to microArray quality control data
نویسندگان
چکیده
منابع مشابه
Nonparametric methods for identifying differentially expressed genes in microarray data
MOTIVATION Gene expression experiments provide a fast and systematic way to identify disease markers relevant to clinical care. In this study, we address the problem of robust identification of differentially expressed genes from microarray data. Differentially expressed genes, or discriminator genes, are genes with significantly different expression in two user-defined groups of microarray exp...
متن کاملStatistical methods for identifying differentially Expressed genes in microarray data
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...
متن کاملAdaptive thresholds to detect differentially expressed genes in microarray data
To detect changes in gene expression data from microarrays, a fixed threshold for fold difference is used widely. However, it is not always guaranteed that a threshold value which is appropriate for highly expressed genes is suitable for lowly expressed genes. In this study, aiming at detecting truly differentially expressed genes from a wide expression range, we proposed an adaptive threshold ...
متن کاملMicroarray data quality control improves the detection of differentially expressed genes.
Microarrays have become a routine tool for biomedical research. Data quality assessment is an essential part of the analysis, but it is still not easy to perform objectively or in an automated manner, and as a result it is often neglected. Here, we compared two strategies of array-level quality control using five publicly available microarray experiments: outlier removal and array weights. We a...
متن کاملTesting for differentially expressed genes with microarray data.
This paper compares the type I error and power of the one- and two-sample t-tests, and the one- and two-sample permutation tests for detecting differences in gene expression between two microarray samples with replicates using Monte Carlo simulations. When data are generated from a normal distribution, type I errors and powers of the one-sample parametric t-test and one-sample permutation test ...
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ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2011
ISSN: 1471-2105
DOI: 10.1186/1471-2105-12-227