10X单细胞（10X空间转录组）拷贝数变化分析之 SCEVAN

2022-01-21 本文已影响0人单细胞空间交响乐

隔离的第12天，孤独散去，前路未知，但必须前进。这一篇我们来分享一个方法，检验单细胞拷贝数变化的方法，之前分享过了两个方法，分别是10X单细胞（10X空间转录组）CNV分析之inferCNVpy、10X单细胞（10X空间转录组）CNV分析回顾之CopyKAT，基本上掌握了这两个方法就可以了，今天再分享一个，了解三个方法的原理，基本对这一项分析有了深入的理解了。

今天分享的方法文献在A fast variational algorithm to detect the clonal copy number substructure of tumors from single-cell data | bioRxiv，我们来看看这个方法。

SCEVAN 是一个 R 包，它从 scRNA 数据的原始计数矩阵开始，通过将肿瘤微环境的非恶性细胞与恶性细胞分离，自动对活检中存在的细胞进行分类，并表征这些恶性细胞的克隆结构。它识别具有不同拷贝数架构的细胞亚群，并报告每个亚群的特定和共享变化。该工具的目的是通过允许以非常简单且完全无人监督的方式执行整个分析来自动化整个分析。

安装

library(devtools)
install_github("miccec/yaGST")
install_github("AntonioDeFalco/SCEVAN")
library(SCEVAN)

Usage

Single-sample analysis

A single call (pipelineCNA) allows the execution of the entire analysis of classification and characterization of clonal structure.

count_mtx : Count matrix with genes on rows (both Gene Symbol or Ensembl ID are allowed) and cells on columns.
sample : Sample name to save results (optional)
par_cores : Number of cores to run the pipeline (optional)
norm_cells : vectors of normal cells if the classification is already known and you are only interested in the clonal structure (optional)
SUBCLONES : Boolean value TRUE if you are interested in analysing the clonal structure and FALSE if you are only interested in the classification of malignant and non-malignant cells (optional)

results <- pipelineCNA(count_mtx)

Multi-sample analysis

A single call (compareClonalStructure) allows the comparison of clonal profiles of the different samples.

count_mtx1 : Count matrix of sample 1.
count_mtx2 : Count matrix of sample 2.
samp_1 : Name of sample 1.
samp_2 : Name of sample 2.
par_cores : Number of cores to run the pipeline (optional)

compareClonalStructure(count_mtx1, count_mtx2, samp_1, samp_2)

Integration with Seurat

Integration of information obtained with SCEVAN (aneuploidy/diploid, subclones) into Seurat object.

count_mtx : Count matrix of sample.

results <- pipelineCNA(count_mtx)

#Create Seurat Object with SCEVAN info
seurObj <- Seurat::CreateSeuratObject(count_mtx, meta.data = results)

#or add SCEVAN info to an existing Seurat object
seurObj <-Seurat::AddMetaData(seurObj, metadata = results)

示例代码

library(SCEVAN)
results <- SCEVAN::pipelineCNA(count_mtx, sample = "MGH106", par_cores = 20, SUBCLONES = TRUE)

输出结果

head(results)

class confidentNormal subclone
MGH106-P7-E10 tumor <NA> 3
MGH106-P2-B01 tumor <NA> 3
MGH106-P2-B12 tumor <NA> 3
MGH106-P2-H07 tumor <NA> 2
MGH106-P2-E09 tumor <NA> 3
MGH106-P2-E04 tumor <NA> 3

list.files(path = "./output", pattern = "MGH106")
##  [1] " MGH106 vega_output"                             
##  [2] " MGH106_subclone1 vega_output"                   
##  [3] " MGH106_subclone2 vega_output"                   
##  [4] " MGH106_subclone3 vega_output"                   
##  [5] " MGH106onlytumor vega_output"                    
##  [6] "MGH106_mtx_vega.txt"                             
##  [7] "MGH106_subclone1_mtx_vega.txt"                   
##  [8] "MGH106_subclone2_mtx_vega.txt"                   
##  [9] "MGH106_subclone3_mtx_vega.txt"                   
## [10] "MGH106- DEchr12:48926474:50821122_subclones.png" 
## [11] "MGH106- DEchr3:112585577:198043720_subclones.png"
## [12] "MGH106- DEchr3:409417:14489349_subclones.png"    
## [13] "MGH106-DEchr12_subclones.png"                    
## [14] "MGH106-DEchr3_subclones.png"                     
## [15] "MGH106CloneTree.png"                             
## [16] "MGH106consensus.png"                             
## [17] "MGH106heatmap_subclones.png"                     
## [18] "MGH106heatmap.png"                               
## [19] "MGH106OncoHeat.png"                              
## [20] "MGH106OncoHeat2.png"                             
## [21] "MGH106onlytumor_mtx_vega.txt"                    
## [22] "MGH106onlytumorheatmap.png"                      
## [23] "MGH106pathwayAnalysis_subclones1.png"            
## [24] "MGH106pathwayAnalysis_subclones2.png"            
## [25] "MGH106pathwayAnalysis_subclones3.png"            
## [26] "MGH106plotCNline.png"                            
## [27] "MGH106tsne_CNA.png"                              
## [28] "MGH106tsne_scRNA.png"