ccAFv2分析cell cycle status

Tips:

Tip1. 当前ccAFv2已经有Python和R版本，本文是R版本的安装和使用；

Tip2.ccAFv2依赖tensorflow 2.12.0，而tensorflow 2.12.0依赖python 3.9（可能3.8也可以，但3.11不行）。python 3.11会默认安装2.19版本，ccAFv2使用时会报错；

Tip3. ThresholdPlot() 函数得出的结果，值越大，可信度一般越高。后续如果没指定，默认为0.5。

1. tensorflow安装

python3.9 -m pip install tensorflow==2.12.0
install_tensorflow(
method = "auto",
version = "2.12.1",
conda_python_version = "3.9",
extra_packages = c("matplotlib", "numpy", "pandas", "scikit-learn")
)

2. ccAFv2安装

remotes::install_github('plaisier-lab/ccafv2_R/ccAFv2')

3. ccAFv2 running

3.1 Without Neural G0

Predict cell cycle states

seurat_obj = PredictCellCycle(seurat_obj,gene_id = "symbol",assay='RNA')  ##注意参数的设置

Plot DimPlot colorized by cell cycle states

pdf('ccAFv2_DimPlot.pdf')
DimPlot.ccAFv2(seurat_obj)
dev.off()

Plot DimPlot colorized by cell cycle states

pdf('ccAFv2_ThresholdPlot.pdf')
ThresholdPlot(seurat_obj)
dev.off()

Adjust ccAFv2 threshold to 0.9

seurat_obj = AdjustCellCycleThreshold(seurat_obj, threshold=0.9)

Plot DimPlot colorized by cell cycle states

pdf('ccAFv2_DimPlot_T_0.9.pdf')
DimPlot.ccAFv2(seurat_obj)
dev.off()

Adjust ccAFv2 threshold back to 0.5

seurat_obj = AdjustCellCycleThreshold(seurat_obj, threshold=0.5)

Plot DimPlot colorized by cell cycle states

pdf('ccAFv2_DimPlot_T_0.5.pdf')
DimPlot.ccAFv2(seurat_obj)
dev.off()

3.2 With Neural G0

Predict cell cycle states

seurat_obj = PredictCellCycle(seurat_obj, include_g0=TRUE)

Plot DimPlot colorized by cell cycle states

pdf('ccAFv2_DimPlot_wNeuralG0.pdf')
DimPlot.ccAFv2(seurat_obj)
dev.off()

Plot DimPlot colorized by cell cycle states

pdf('ccAFv2_ThresholdPlot_wNeuralG0.pdf')
ThresholdPlot(seurat_obj)
dev.off()

Adjust ccAFv2 threshold to 0.9

seurat_obj = AdjustCellCycleThreshold(seurat_obj, threshold=0.9, include_g0=TRUE)

Plot DimPlot colorized by cell cycle states

pdf('ccAFv2_DimPlot_T_0.9_wNeuralG0.pdf')
DimPlot.ccAFv2(seurat_obj)
dev.off()

Adjust ccAFv2 threshold back to 0.5

seurat_obj = AdjustCellCycleThreshold(seurat_obj, threshold=0.5, include_g0=TRUE)

Plot DimPlot colorized by cell cycle states

pdf('ccAFv2_DimPlot_T_0.5_wNeuralG0.pdf')
DimPlot.ccAFv2(seurat_obj)
dev.off()

3.3 Cell cycle regression

Regress out cell cycle

seurat_obj = PrepareForCellCycleRegression(seurat_obj)
seurat_obj = SCTransform(seurat_obj, vars.to.regress = c("Late.G1_exprs1", "S_exprs2", "S.G2_exprs3", "G2.M_exprs4", "M.Early.G1_exprs5"))

Plot cell cycle regressed UMAP

seurat_obj = RunPCA(seurat_obj)
seurat_obj = RunUMAP(seurat_obj, dims=1:10)
pdf('ccAFv2_DimPlot_regressed.pdf')
DimPlot.ccAFv2(seurat_obj)
dev.off()
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