hello,周四了,一周又即將過(guò)去,不知道大家有沒(méi)有感覺(jué)到時(shí)光飛逝,時(shí)間啊,慢些吧,給自己點(diǎn)時(shí)間可以思考。
這一篇教給大家一個(gè)簡(jiǎn)單的內(nèi)容,畫(huà)圖,一張是細(xì)胞類型占比餅圖,一張是細(xì)胞密度空間分布圖,如下圖:

圖片.png

圖片.png
我們首先來(lái)餅圖
library(Seurat)
library(ggplot2)
###讀取數(shù)據(jù),讀入自己的數(shù)據(jù)
Spatial = readRDS(Seurat_spatial_rds)
anno = read.csv(sp_sc_joint,header = T,row.names = 1,check.names = F)###單細(xì)胞空間聯(lián)合分布矩陣
coor = Spatial@images$image@coordinates[,c(5,4)]
meta = rbind(coor,anno)
head(meta)

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colnames(meta)[1:2] = c('x','y')
st_meta$x <- (st_meta$x - min(st_meta$x))/(max(st_meta$x) -
min(st_meta$x))
st_meta$y <- (st_meta$y - min(st_meta$y))/(max(st_meta$y) -
min(st_meta$y))
cellname <- colnames(meta)[-c(1:2)]
col_manual <- ggpubr::get_palette(palette = "lancet",
k = length(cellname))####顏色
ggplot2::ggplot() + scatterpie::geom_scatterpie(data = st_meta,
ggplot2::aes(x = x, y = y), col = cellname, color = NA,
pie_scale = pie_scale) + ggplot2::coord_fixed(ratio = 1) +
ggplot2::scale_fill_manual(values = col_manual) + ggplot2::theme_bw() +
ggplot2::theme(panel.grid = ggplot2::element_blank()) +
ggplot2::labs(x = "scaled_x", y = "scaled_y")
就可以得到細(xì)胞類型分布的餅圖了

圖片.png
然后下一張圖,看某種細(xì)胞類型的空間分布
col_manual <- ggpubr::get_palette(palette = "lancet",
k = length(cellname))
point_color <- col_manual[which(cellname == celltype)]
st_meta <- st_meta[st_meta$celltype == celltype, ]
p <- ggplot2::ggplot(data = st_meta, ggplot2::aes(x, y)) +
ggplot2::theme_bw() + ggplot2::theme(panel.grid = ggplot2::element_blank())
p <- p + ggplot2::geom_point(size = point_size, color = point_color)
p <- p + ggplot2::stat_density2d(ggplot2::aes(color = ..level..),
size = size)
p + scale_color_gradient(low = color_low, high = color_high)
color_midpoint <- stats::median(st_meta$gene)
p + scale_color_gradient2(low = color_low, mid = color_mid,
high = color_high, midpoint = color_midpoint)
print(p)
就拿到了下面的結(jié)果

圖片.png
其中剛開(kāi)始用
p <- p + ggplot2::stat_density2d(ggplot2::aes(fill = ..density..),
geom = "raster", contour = F)
就會(huì)得到下面的圖

圖片
你學(xué)會(huì)了么,生活很好,有你更好