Implements the algorithm described in Jun Li and Alicia T. Lamere, "DiPhiSeq: Robust comparison of expression levels on RNA-Seq data with large sample sizes" (Unpublished). Detects not only genes that show different average expressions ("differential expression", DE), but also genes that show different diversities of expressions in different groups ("differentially dispersed", DD). DD genes can be important clinical markers. 'DiPhiSeq' uses a redescending penalty on the quasi-likelihood function, and thus has superior robustness against outliers and other noise. Updates from version 0.1.0: (1) Added the option of using adaptive initial value for phi. (2) Added a function for estimating the proportion of outliers in the data. (3) Modified the input parameter names for clarity, and modified the output format for the main function.
| Version: | 0.2.0 |
| Depends: | R (≥ 3.1.0) |
| Imports: | stats (≥ 3.1.0) |
| Published: | 2018-10-24 |
| Author: | Jun Li [aut, cre], Alicia T. Lamere [aut] |
| Maintainer: | Jun Li <jun.li at nd.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | DiPhiSeq results |
| Reference manual: | DiPhiSeq.pdf |
| Package source: | DiPhiSeq_0.2.0.tar.gz |
| Windows binaries: | r-devel: DiPhiSeq_0.2.0.zip, r-release: DiPhiSeq_0.2.0.zip, r-oldrel: DiPhiSeq_0.2.0.zip |
| macOS binaries: | r-release: DiPhiSeq_0.2.0.tgz, r-oldrel: DiPhiSeq_0.2.0.tgz |
| Old sources: | DiPhiSeq archive |
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