2.0.0版本变化o trainSingleR的输出的格式()已经改变了,不再是back-compatible。o在trainSingleR验算= FALSE()没有;所有集成分析现在都完成了再计算= TRUE。为此,combineCommonResults()也弃用。o =“sd”基因及其相关选项trainSingleR()不再支持。o。标签不再报道classifySingleR ()。通过num.threads = o添加另一个并行机制和c++ 11线程。这应该是内存效率比使用BiocParallel得多。o combineRecomputedScores()将自动处理不匹配输入默认引用。 Changes in version 1.6.0 o Relaxed the requirements for consistent row names in combineRecomputedResults(). o Support sparse DelayedArray inputs in classifySingleR(). o Parallelize over labels instead of rows in aggregateReference(), with minor changes in the setting of the seed. Restrict the PCA to the top 1000 most highly variable genes, for speed. Changes in version 1.4.0 o Migrated all of the dataset getter functions to the celldex package. o Streamlined the vignette to point to the book at。o添加了一个限制trainSingleR =参数()和单()轻松地限制功能的一个子集。o弃用单一的方法=参数()。o防止意外data.frames ref =或测试=所有功能。版本变化1.2.0 o添加支持巩固标签从多个引用通过combineResults ()。o映射添加到标准细胞本体术语*数据()函数。改变标签的名称输入阿plotScoreDistribution()标签。使用一致性的功能。o固定标签从脂肪细胞、星形胶质细胞在BlueprintEncodeData ()。o将变音符号从标签(例如,天真)NovershternHematopoieticData Windows()来避免问题。o执行PCA在聚类之前aggregateReference()在速度和记忆效率。 o Modified genes="all" behavior in trainSingleR() to report DE-based markers for fine-tuning only. Changes in version 1.0.0 o New package SingleR for cell type annotation.