Closed ixxmu closed 1 year ago
前面我们提到过 髓系免疫细胞的细分,只要是单核,树突,巨噬,粒细胞。其中单核还可以区分成为了:
我们前面已经对免疫细胞里面的髓系和B细胞细分亚群进行了简单的介绍:
但是之前的髓系免疫细胞细分的时候其实并没有中性粒细胞亚群,因为绝大部分早期的10x技术产出的单细胞转录组数据里面其实很难区分出来中性粒细胞亚群,具体原因大家很容易去10x的官网看到。后来我做了更新,而且我把这些髓系单细胞亚群的基因也提取出来了,做成为了代码给大家:
th=theme(axis.text.x = element_text(angle = 45,
vjust = 0.5, hjust=0.5))
myeloids = list(
Mac=c("C1QA","C1QB","C1QC","SELENOP","RNASE1","DAB2","LGMN","PLTP","MAF","SLCO2B1"),
mono=c("VCAN","FCN1","CD300E","S100A12","EREG","APOBEC3A","STXBP2","ASGR1","CCR2","NRG1"),
neutrophils = c("FCGR3B","CXCR2","SLC25A37","G0S2","CXCR1","ADGRG3","PROK2","STEAP4","CMTM2" ),
pDC = c("GZMB","SCT","CLIC3","LRRC26","LILRA4","PACSIN1","CLEC4C","MAP1A","PTCRA","C12orf75"),
DC1 = c("CLEC9A","XCR1","CLNK","CADM1","ENPP1","SNX22","NCALD","DBN1","HLA-DOB","PPY"),
DC2 = c( "CD1C","FCER1A","CD1E","AL138899.1","CD2","GPAT3","CCND2","ENHO","PKIB","CD1B"),
DC3 = c("HMSD","ANKRD33B","LAD1","CCR7","LAMP3","CCL19","CCL22","INSM1","TNNT2","TUBB2B")
)
p <- DotPlot(sce.all, features = myeloids,
assay='RNA' ,group.by = 'celltype' ) +th
p
ggsave(plot=p, filename="check_myeloids_marker_by_celltype.pdf")
蛮方便的,大家可以复制粘贴我的代码去自己的单细胞项目里面的髓系免疫细胞里面赶快看看哦。
但是最近看到了一个文章:《Analysis of Donor Pancreata Definesthe Transcriptomic Signature and Microenvironment of Early Neoplastic Lesions》它把髓系免疫细胞区分成为了:
如下所示的可视化:
这样就很尴尬, 上面的classical和nonclassical明明是单核细胞啊,为什么这个文章把它名字给巨噬细胞呢?就因为是单核巨噬系统?但是这里面的巨噬细胞就很清楚啦,很早之前我们就总结过虽然虽然M1和M2的分类深入人心,但是在单细胞水平里面正确的做法可能是放弃M1和M2,详见:M1和M2的巨噬细胞差异就在CD86和CD163吗,很多单细胞文章都表明了巨噬细胞的M1和M2极化相关基因在单细胞水平是正相关,所以他们是无法区分成为M1和M2。正确的做法应该是TREM2联合SPP1,去和FOLR2基因具有排他性,这样的二分类模式!
目前,巨噬细胞可以二分类,单核细胞也可以二分类,树突细胞有点麻烦是pDC加上3个DC,粒细胞呢虽然也很复杂但是它比较少见。
强烈建议你推荐给身边的博士后以及年轻生物学PI,多一点数据认知,让他们的科研上一个台阶:
https://mp.weixin.qq.com/s/H9-Y4KGcEFb6cGrNb8iknw