Added a new model to all.models for predicting T2E.fusion. Thus estimate.features() will now predict T2E.fusion.
For devs: previously the new T2E model and old model results were created/saved in 2 different files, making maintenance more difficult. Thus scripts were consolidated so that all models are now created/saved in a single file. This will improve maintenance of the package.
PrCaMethy 1.0.0 (2025-05-22)
New Features
Added a random forest model for assigning the 4 methylation subtypes (subtype.model.rf). Unlike subtype.model.pamr which requires all 5,486 subtype-defining CpGs to be measured, subtype.model.rf can handle missing CpGs through imputation (although ideally you should have as many of the CpGs as possible).
Changed
Renamed subtype.model to subtype.model.pamr since now the package has 2 models for assigning the methylation subtypes (subtype.model.pamr and subtype.model.rf). This will not cause any breaking changes to the user.
Breaking changes
estimate.subtypes() now returns a list with 2 elements: subtypes and validation where the latter checks the validity of the input methylation data. Previously it only returned the subtypes data.frame. This is a minor breaking change.
PrCaMethy 0.2.0 (2025-05-15)
New Features
Support CpGs from Illumina 850K array when using gene.methylation to calculate gene-level methylation. Previously only 450K array was supported.
Enhancements
Documentation updated to explain both Illumina 450K and 850K arrays are supported (previously only 450K was supported)