单细胞中的GSVA基因集评分怎么实现？

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## 使用GSVA:score的大小来定量评价基因集在样本中的相对大小
library(GSVA)
#读取gmt文件
geneset <- read.gmt(file.path("./PreB_pathways_GSVA_score.gmt"))  #read.gmt
geneset <- split(geneset$gene,geneset$term)
geneset

Idents(fasting_memory) <- fasting_memory$Sample
fasting_memory_preB <- subset(fasting_memory,Celltype %in% c("Pre-B")) %>% subset(Sample %in% c("memory_10d","memory_35d","memory_66d"))

fasting_memory_preB <- FindVariableFeatures(fasting_memory_preB,selection.method="vst",nfeatures=2000)
genes <- VariableFeatures(fasting_memory_preB)
GSVA_exp <- AverageExpression(fasting_memory_preB,
                              #features = genes,
                              group.by = 'Sample', assays = 'RNA', slot = "data") 
GSVA_exp <- as.data.frame(GSVA_exp$RNA)
dim(GSVA