The 'MSiP' is a computational approach to predict protein-protein interactions from large-scale affinity purification mass 'spectrometry' (AP-MS) data. This approach includes both spoke and matrix models for interpreting AP-MS data in a network context. The "spoke" model considers only bait-prey interactions, whereas the "matrix" model assumes that each of the identified proteins (baits and prey) in a given AP-MS experiment interacts with each of the others. The spoke model has a high false-negative rate, whereas the matrix model has a high false-positive rate. Although, both statistical models have merits, a combination of both models has shown to increase the performance of machine learning classifiers in terms of their capabilities in discrimination between true and false positive interactions.
| Version: | 1.3.7 |
| Depends: | R (≥ 3.6.0) |
| Imports: | dplyr (≥ 1.0.6), tibble (≥ 3.1.2), tidyr (≥ 1.1.3), magrittr (≥ 2.0.1), plyr (≥ 1.8.6), PRROC (≥ 1.3.1), caret (≥ 6.0.88), e1071 (≥ 1.7.7), mice (≥ 3.13.0), pROC (≥ 1.17.0.1), ranger (≥ 0.12.1) |
| Suggests: | knitr, markdown |
| Published: | 2021-06-17 |
| Author: | Matineh Rahmatbakhsh [aut, cre] |
| Maintainer: | Matineh Rahmatbakhsh <matinerb.94 at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | MSiP results |
| Reference manual: | MSiP.pdf |
| Vignettes: |
MSiP tutorial |
| Package source: | MSiP_1.3.7.tar.gz |
| Windows binaries: | r-devel: MSiP_1.3.7.zip, r-release: MSiP_1.3.7.zip, r-oldrel: MSiP_1.3.7.zip |
| macOS binaries: | r-release (arm64): MSiP_1.3.7.tgz, r-release (x86_64): MSiP_1.3.7.tgz, r-oldrel: MSiP_1.3.7.tgz |
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