Bmk Space mapping.R軟件圖文教程

1、打開腳本文件

source(‘xxx’) #’xxx’腳本路徑， 例如’C:/Users/R/Desktop/qq.R’

2、創(chuàng)建Seurat對象并繪制空間聚類圖

FilePath : 存放“barcode.tsv.gz、barcode_pos.tsv.gz、feature.tsv.gz、matrix.mtx.gz”的文件夾路徑
barcode_pos_file : “barcode_pos.tsv.gz”的文件路徑
out_path : 輸出文件目錄
png_path : he染色（.png格式），如果是 .tiff 格式需要進(jìn)行格式轉(zhuǎn)換，注意轉(zhuǎn)換時(shí)分辨率可適當(dāng)調(diào)小，以避免 .png 格式的圖片太大而讀取失敗
需注意的是Seurat對象名稱必須是“object”

object?<-?Create_object(

FilePath = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/’,

barcode_pos_file = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/barcodes_pos.tsv.gz’,

out_path = ‘C:/Users/R/Desktop/temp/Cluster/’,

png_path = ‘C:/Users/R/Desktop/temp/he.png’,

min.cells = 10, #一個(gè)基因至少在n個(gè)細(xì)胞中表達(dá)才被保留，可自行調(diào)整，默認(rèn)值10

min.features = 100, #一個(gè)細(xì)胞至少有n個(gè)基因才被保留，可自行調(diào)整，默認(rèn)值100

dims = 1:30, #選擇多少pc進(jìn)行后續(xù)分析，可自行調(diào)整，默認(rèn)1：30

resolution = 0.5, #設(shè)置下游分析的“粒度”，值越高得到的聚類數(shù)目越多，可自行調(diào)整，默認(rèn)0.5

point_size = 3, #點(diǎn)的大小，可自行根據(jù)矩陣文件level調(diào)整，level越小需設(shè)置的值越小

width = 12, #輸出圖片的寬度，可自行調(diào)整，默認(rèn)12

height = 5, #輸出圖片的高度，可自行調(diào)整，默認(rèn)5

Cluster = T, #是否進(jìn)行聚類分析，默認(rèn)F

label = T #是否輸出帶標(biāo)簽的聚類圖

)

3、UMI統(tǒng)計(jì)

object?<-?Create_object(

FilePath = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/’,

barcode_pos_file = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/barcodes_pos.tsv.gz’,

out_path = ‘C:/Users/R/Desktop/temp/UMI_stat/’,

png_path = ‘C:/Users/R/Desktop/temp/he.png’,

point_size = 3, #同上

width = 12, #同上

height = 5, #同上

UMI_stat = T) #是否統(tǒng)計(jì)UMI

4、nFeature 統(tǒng)計(jì)

object?<-?Create_object(

FilePath = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/’,

barcode_pos_file = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/barcodes_pos.tsv.gz’,

out_path = ‘C:/Users/R/Desktop/temp/Gene_stat/’,

png_path = ‘C:/Users/R/Desktop/temp/he.png’,

point_size = 2, #同上

width = 12, #同上

height = 5, #同上

nFeature_stat = T) #是否統(tǒng)計(jì)nFeature

5、輸出每個(gè)cluster的marker gene，并繪制單個(gè)基因的表達(dá)熱圖

object?<-?Create_object(

FilePath = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/’,

barcode_pos_file = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/barcodes_pos.tsv.gz’,

out_path = ‘C:/Users/R/Desktop/temp/Single_gene_1/’,

png_path = ‘C:/Users/R/Desktop/temp/he.png’,

point_size = 2, #同上

Gene_stat = T, #是否進(jìn)行mark gene繪制

top_gene = 1, #每個(gè)cluster取top多少mark gene， 可自行調(diào)整，值不宜設(shè)置太大

min.pct = 0.25, #一個(gè)基因在任何兩群細(xì)胞中的占比不能低于多少， 可自行調(diào)整

logfc.threshold = 0.25， #差異倍數(shù)閾值， 可自行調(diào)整

markpic_width = 8, #小提琴圖和tsne圖寬

markpic_height = 12, #小提琴圖和tsne圖長)

6、繪制某個(gè)或某些基因聚類圖

object?<-?Create_object(

FilePath = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/’,

barcode_pos_file = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/barcodes_pos.tsv.gz’,

out_path = ‘C:/Users/R/Desktop/temp/Test/Single_gene_2/’,

png_path = ‘C:/Users/R/Desktop/temp/he.png’,

point_size = 2.6, #同上

Gene_stat = T, #是否進(jìn)行mark gene繪制

Custom_gene = T, #是否進(jìn)行自定義gene繪制

alpha_continuous = c(0.5,1) #根據(jù)基因表達(dá)量調(diào)整透明度范圍

gene_list = c(‘Hpca’)) #繪制的基因名，可以輸入多個(gè)

選擇黑色背景突出顯示

object?<-?Create_object(

FilePath = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/’,

barcode_pos_file = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/barcodes_pos.tsv.gz’,

out_path = ‘C:/Users/R/Desktop/temp/Test/Single_gene_2/’,

png_path = ‘C:/Users/R/Desktop/temp/he.png’,

point_size = 2.6, #同上

Gene_stat = T, #是否進(jìn)行mark gene繪制

Custom_gene = T, #是否進(jìn)行自定義gene繪制

dark_background = T, #黑色背景

gene_list = c(‘Hpca’)) #繪制的基因名，可以輸入多個(gè)

7、繪制單個(gè)cluster聚類圖

object?<-?Create_object(

FilePath = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/’,

barcode_pos_file = ‘E:/AAAWork/BSTViewer_project/subdata/L13_heAuto/barcodes_pos.tsv.gz’,

out_path = ‘C:/Users/R/Desktop/temp/TestL6/single/’,

png_path = ‘C:/Users/R/Desktop/temp/he.png’,

point_size = 2, #同上

Single_cluster = T #是否繪制單個(gè)cluster圖)