Differential gene expression analysis tools return a vector of p-values assigned to genes under study. P-values represent a probability of differential gene expression by chance. Genes with lower p-values are considered differentially expressed. Conventionally, p-value less than or equal to 0.05 are considered significant at 95 percent confidence level. However, this p-value cutoff does not work always and also affected by the sample size of the compared groups. This package provides sophesticated simulation-based p-value cutoff selection using permutation resampling technique. The estimated p-value cutoff expected to select differentially expressed genes with false positive rate less than five percent. This technique is data-driven and therefore avoid the biased selection of p-value. Though it is developed for selecting differentially expressed genes but in principle can be used for any data as long as results are in the form of p-value vector and need cutoff to reject null hypothesis.
Package details |
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Author | Vijaykumar Yogesh Muley |
Maintainer | Vijaykumar Yogesh Muley <vijay.muley@gmail.com> |
License | Artistic-2.0 |
Version | 0.1.0 |
Package repository | View on GitHub |
Installation |
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