| Title: | Attribute-Weighted Aggregation Data |
|---|---|
| Description: | The AWAggregatorData package contains the data associated with the AWAggregator R package. It includes two pre-trained random forest models, one incorporating the average coefficient of variation as a feature, and the other one not including it. It also contains the PSMs in Benchmark Set 1~3 derived from the psm.tsv output files generated by FragPipe, which are used to train the random forest models. |
| Authors: | Jiahua Tan [aut, cre] (ORCID: <https://orcid.org/0000-0001-5839-1049>), Gian L. Negri [aut] (ORCID: <https://orcid.org/0000-0001-7722-8888>), Gregg B. Morin [aut] (ORCID: <https://orcid.org/0000-0001-8949-4374>), David D. Y. Chen [aut] (ORCID: <https://orcid.org/0000-0002-3669-6041>) |
| Maintainer: | Jiahua Tan <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 1.2.0 |
| Built: | 2026-10-10 11:51:31 UTC |
| Source: | https://github.com/bioc/AWAggregatorData |
Loads a pre-trained random forest model for predicting the level of quantitative inaccuracy of PSMs.
loadQuantInaccuracyModel(useAvgCV = TRUE)loadQuantInaccuracyModel(useAvgCV = TRUE)
useAvgCV |
A logical value indicating whether the average CV attribute was used in the training. |
The pre-trained random forest model.
regr <- loadQuantInaccuracyModel(useAvgCV=TRUE)regr <- loadQuantInaccuracyModel(useAvgCV=TRUE)