使用Seurat和Velocyto估算RNA速率

分享是一种态度

此教程演示分析存储在Seurat对象中的RNA速率定量。参数基于RNA速率教程[1]。如果您在工作中使用Seurat，请引用：

RNA velocity of single cells
Gioele La Manno, Ruslan Soldatov, Amit Zeisel, Emelie Braun, Hannah Hochgerner, Viktor Petukhov, Katja Lidschreiber, Maria E. Kastriti, Peter Lönnerberg, Alessandro Furlan, Jean Fan, Lars E. Borm, Zehua Liu, David van Bruggen, Jimin Guo, Xiaoling He, Roger Barker, Erik Sundström, Gonçalo Castelo-Branco, Patrick Cramer, Igor Adameyko, Sten Linnarsson & Peter V. Kharchenko
doi: 10.1038/s41586-018-0414-6
Website: https://velocyto.org

准备工作

提前安装好如下3个R包。

Seurat
velocyto.R
SeuratWrappers

加载所需R包

代码语言：javascript复制

library(Seurat)
library(velocyto.R)
library(SeuratWrappers)

下载所需示例数据

代码语言：javascript复制

# If you don't have velocyto's example mouse bone marrow dataset, download with the CURL command
# curl::curl_download(url = 'http://pklab.med.harvard.edu/velocyto/mouseBM/SCG71.loom', destfile
# = '~/Downloads/SCG71.loom')

转换为seurat对象

代码语言：javascript复制

ldat <- ReadVelocity(file = "~/Downloads/SCG71.loom")
bm <- as.Seurat(x = ldat)

整合降维聚类

代码语言：javascript复制

bm <- SCTransform(object = bm, assay = "spliced")
bm <- RunPCA(object = bm, verbose = FALSE)
bm <- FindNeighbors(object = bm, dims = 1:20)
bm <- FindClusters(object = bm)
bm <- RunUMAP(object = bm, dims = 1:20)

速率分析及可视化

代码语言：javascript复制

bm <- RunVelocity(object = bm, deltaT = 1, kCells = 25, fit.quantile = 0.02)
ident.colors <- (scales::hue_pal())(n = length(x = levels(x = bm)))
names(x = ident.colors) <- levels(x = bm)
cell.colors <- ident.colors[Idents(object = bm)]
names(x = cell.colors) <- colnames(x = bm)
show.velocity.on.embedding.cor(emb = Embeddings(object = bm, reduction = "umap"), vel = Tool(object = bm, 
    slot = "RunVelocity"), n = 200, scale = "sqrt", cell.colors = ac(x = cell.colors, alpha = 0.5), 
    cex = 0.8, arrow.scale = 3, show.grid.flow = TRUE, min.grid.cell.mass = 0.5, grid.n = 40, arrow.lwd = 1, 
    do.par = FALSE, cell.border.alpha = 0.1)

参考资料

[1]

RNA速率教程: http://pklab.med.harvard.edu/velocyto/notebooks/R/SCG71.nb.html

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