1. NormalizeData()
method = LogNormalize
:
- Feature counts for each cell are divided by the total counts for that cell
- Multiplied by the scale.factor (10000)
- Log1p()
结果存放在
@assays$RNA@data
中
2. NormalizeData(Seurat_object, assay = "HTO", normalization.method = "CLR")
对
HTO
数据进行CLR
归一化处理
对
Seurat_object@assays$HTO@counts
中的每一行进行CLR
处理,即对同一hashtag
的UMI
值在细胞之间进行归一化归一化后的值放在
Seurat_object@assays$HTO@data
中
处理步骤:
kk <- as.numeric(kk@assays$HTO@counts[1,])
data_0 <- log1p(kk[kk > 0])
data_1 <- sum(data_0, na.rm=TRUE)
data_2 <- length(kk)
data_3 <- exp(data_1/data_2)
data_4 <- kk/data_3
log1p(data_4)
:CLR
归一化后的值
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