Changelog

Source: NEWS.md

RankMap 0.99.0

Initial submission to Bioconductor

New Features

• Fast, robust, and scalable reference-based cell type annotation using multinomial regression on sparse ranked expression matrices.
• Supports both single-cell and spatial transcriptomics data.
• Compatible with Seurat, SingleCellExperiment, and SpatialExperiment objects.
• Core function RankMap() provides a streamlined pipeline for preprocessing, model training, and prediction.
• Customizable preprocessing: top-K gene masking, optional binning, expression weighting, and scaling.
• Additional functions:
  • ComputeRankedMatrix() – generate ranked matrices
  • TrainRankModel() – train multinomial GLM
  • PredictRankModel() – apply trained model to query data
  • EvaluatePredictionPerformance() – assess accuracy
• Optimized for large datasets with significantly faster runtime than SingleR, Azimuth, and RCTD.