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type: software
license: MIT
title: 'scClustEval: Single Cell Clustering Evaluation and Optimization Framework'
version: 1.0.0
doi: 10.32614/CRAN.package.scClustEval
abstract: A comprehensive framework for evaluating and optimizing single-cell RNA-seq
  clustering results using self-projection machine learning approaches. The package
  implements an iterative optimization strategy that merges poorly discriminated clusters
  based on confusion matrix analysis, achieving robust and reliable cell type identification.
  Features include multiple classifier support (logistic regression, random forest,
  SVM, etc.), ROC curve analysis, confusion matrix visualization, and seamless integration
  with Seurat objects. This is an R implementation inspired by the SCCAF Python package.
authors:
- family-names: Liu
  given-names: Zaoqu
  email: liuzaoqu@163.com
repository: https://zaoqu-liu.r-universe.dev
repository-code: https://github.com/Zaoqu-Liu/scClustEval
commit: dabff729e1d04edfedf119d6d2c1617aa99de218
url: https://github.com/Zaoqu-Liu/scClustEval
date-released: '2026-01-26'
contact:
- family-names: Liu
  given-names: Zaoqu
  email: liuzaoqu@163.com