Implements Surprisal analysis for gene expression data such as RNA-seq or microarray experiments. Surprisal analysis is an information-theoretic method that decomposes gene expression data into a baseline state and constraint-associated deviations, capturing coordinated gene expression patterns under different biological conditions. References: Kravchenko-Balasha N. et al. (2014) <doi:10.1371/journal.pone.0108549>. Zadran S. et al. (2014) <doi:10.1073/pnas.1414714111>. Su Y. et al. (2019) <doi:10.1371/journal.pcbi.1007034>. Bogaert K. A. et al. (2018) <doi:10.1371/journal.pone.0195142>.
Package details |
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Author | Annice Najafi [aut, cre] (ORCID: <https://orcid.org/0000-0003-0679-9397>) |
Maintainer | Annice Najafi <annicenajafi27@gmail.com> |
License | MIT + file LICENSE |
Version | 0.2 |
Package repository | View on CRAN |
Installation |
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