CellChat：細(xì)胞間相互作用分析利器

前言

我們知道，細(xì)胞間信息傳遞方式一個(gè)是細(xì)胞表面配受體的相互作用密幔，另一個(gè)通過(guò)細(xì)胞產(chǎn)生的可溶性小分子萍歉，即細(xì)胞因子。在單細(xì)胞數(shù)據(jù)分析中下游坟乾，有時(shí)候我們想看某幾種細(xì)胞類(lèi)型之間的相互作用迹辐，就有人推薦我們做一個(gè)配受體分析。那什么是配受體糊渊？我們?cè)谖恼?a href="http://www.reibang.com/p/49613adce465" target="_blank">Cell-Cell Interaction Database|| 單細(xì)胞配受體庫(kù)你還在文章的附錄里找嗎？中提到配受體其實(shí)是細(xì)胞的特定蛋白慧脱，蛋白追溯到基因表達(dá)上就是基因?qū)Α?/p>

Inference and analysis of cell-cell communication using CellChat
Suoqin Jin, Christian F. Guerrero-Juarez, Lihua Zhang, Ivan Chang, Peggy Myung, Maksim V. Plikus, Qing Nie
bioRxiv 2020.07.21.214387; doi: https://doi.org/10.1101/2020.07.21.214387

今天渺绒，我們就用CellChat來(lái)分析一下我們的PBMC數(shù)據(jù)，看看配受體分析的一般流程菱鸥。

除了從任何給定的scRNA-seq數(shù)據(jù)推斷細(xì)胞間通信外宗兼，CellChat還提供了進(jìn)一步的數(shù)據(jù)探索、分析和可視化功能氮采。

它能夠分析細(xì)胞與細(xì)胞間的通訊殷绍，以獲得細(xì)胞發(fā)展軌跡上的連續(xù)狀態(tài)。
該方法結(jié)合社會(huì)網(wǎng)絡(luò)分析鹊漠、模式識(shí)別和多種學(xué)習(xí)方法主到，可以定量地描述和比較推斷出的細(xì)胞間通信網(wǎng)絡(luò)。
它提供了一個(gè)易于使用的工具來(lái)提取和可視化推斷網(wǎng)絡(luò)信息躯概。例如登钥，它可以隨時(shí)預(yù)測(cè)所有細(xì)胞群的主要信號(hào)輸入和輸出，以及這些細(xì)胞群和信號(hào)如何協(xié)調(diào)在一起實(shí)現(xiàn)功能娶靡。
它提供了幾個(gè)可視化輸出牧牢，以方便用戶引導(dǎo)的直觀數(shù)據(jù)解釋。

devtools::install_github("sqjin/CellChat")

CellChat需要兩個(gè)輸入:

一個(gè)是細(xì)胞的基因表達(dá)數(shù)據(jù)，
另一個(gè)是細(xì)胞標(biāo)簽(即細(xì)胞標(biāo)簽)塔鳍。

對(duì)于基因表達(dá)數(shù)據(jù)矩陣伯铣，基因應(yīng)該在帶有行名的行中，cell應(yīng)該在帶有名稱(chēng)的列中轮纫。CellChat分析的輸入是均一化的數(shù)據(jù)(Seurat@assay$RNA@data)腔寡。如果用戶提供counts數(shù)據(jù)，可以用normalizeData函數(shù)來(lái)均一化蜡感。對(duì)于細(xì)胞的信息蹬蚁，需要一個(gè)帶有rownames的數(shù)據(jù)格式作為CellChat的輸入。

這兩個(gè)文件在我們熟悉的Seurat對(duì)象中是很容易找到的郑兴，一個(gè)是均一化之后的數(shù)據(jù)犀斋，一個(gè)是細(xì)胞類(lèi)型在metadata中。那么就讓我們開(kāi)始chat之旅吧情连。

數(shù)據(jù)配置

首先叽粹，我們加載包和引入實(shí)例數(shù)據(jù)。

library(CellChat)
library(ggplot2)
library(ggalluvial)
library(svglite)
library(Seurat)
library(SeuratData)
options(stringsAsFactors = FALSE)

我們用Seurat給出的pbmc3k.final數(shù)據(jù)集却舀，大部分的計(jì)算已經(jīng)存在其對(duì)象中了：

pbmc3k.final

An object of class Seurat 
13714 features across 2638 samples within 1 assay 
Active assay: RNA (13714 features, 2000 variable features)
 2 dimensional reductions calculated: pca, umap


 pbmc3k.final@commands$FindClusters  # 你也看一看作者的其他命令虫几，Seurat是記錄其分析過(guò)程的。
Command: FindClusters(pbmc3k.final, resolution = 0.5)
Time: 2020-04-30 12:54:53
graph.name : RNA_snn 
modularity.fxn : 1 
resolution : 0.5 
method : matrix 
algorithm : 1 
n.start : 10 
n.iter : 10 
random.seed : 0 
group.singletons : TRUE 
verbose : TRUE

按照我們剛才說(shuō)的挽拔，我們?cè)赟eurat對(duì)象中提出CellChat需要的數(shù)據(jù)：

data.input  <- pbmc3k.final@assays$RNA@data
identity = data.frame(group =pbmc3k.final$seurat_annotations   , row.names = names(pbmc3k.final$seurat_annotations)) # create a dataframe consisting of the cell labels
unique(identity$group) # check the cell labels

[1] Memory CD4 T B            CD14+ Mono   NK           CD8 T        Naive CD4 T  FCGR3A+ Mono DC           Platelet    
Levels: Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet

創(chuàng)建一個(gè)Cell Chat對(duì)象辆脸。

cellchat <- createCellChat(data = data.input)
cellchat

An object of class CellChat 
 13714 genes.
 2638 cells.

summary(cellchat)

Length    Class     Mode 
       1 CellChat       S4

S4 類(lèi)學(xué)會(huì)了嗎？

在學(xué)習(xí)單細(xì)胞數(shù)據(jù)分析工具的時(shí)候螃诅，在知道了要干嘛之后啡氢，第二步就是看數(shù)據(jù)格式，俗稱(chēng)：?jiǎn)渭?xì)胞數(shù)據(jù)格式术裸。我們?cè)?a href="http://www.reibang.com/p/7560f4fd0d77" target="_blank">聽(tīng)說(shuō)你的單細(xì)胞對(duì)象需要一個(gè)思維導(dǎo)圖倘是？，曾給出一個(gè)簡(jiǎn)單的可視化數(shù)據(jù)結(jié)構(gòu)的方法：導(dǎo)圖袭艺。

library(mindr)
(out <- capture.output(str(cellchat)))
out2 <- paste(out, collapse="\n")
mm(gsub("\\.\\.@","# ",gsub("\\.\\. ","#",out2)),type ="text")

當(dāng)然搀崭，我們可以用str來(lái)看，就是有點(diǎn)冗長(zhǎng)：

> str(cellchat)
Formal class 'CellChat' [package "CellChat"] with 14 slots
  ..@ data.raw      : num[0 , 0 ] 
  ..@ data          :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
  .. .. ..@ i       : int [1:2238732] 29 73 80 148 163 184 186 227 229 230 ...
  .. .. ..@ p       : int [1:2639] 0 779 2131 3260 4220 4741 5522 6304 7094 7626 ...
  .. .. ..@ Dim     : int [1:2] 13714 2638
  .. .. ..@ Dimnames:List of 2
  .. .. .. ..$ : chr [1:13714] "AL627309.1" "AP006222.2" "RP11-206L10.2" "RP11-206L10.9" ...
  .. .. .. ..$ : chr [1:2638] "AAACATACAACCAC" "AAACATTGAGCTAC" "AAACATTGATCAGC" "AAACCGTGCTTCCG" ...
  .. .. ..@ x       : num [1:2238732] 1.64 1.64 2.23 1.64 1.64 ...
  .. .. ..@ factors : list()
  ..@ data.signaling: num[0 , 0 ] 
  ..@ data.scale    : num[0 , 0 ] 
  ..@ data.project  : num[0 , 0 ] 
  ..@ net           : list()
  ..@ netP          : list()
  ..@ meta          :'data.frame':  0 obs. of  0 variables
Formal class 'data.frame' [package "methods"] with 4 slots
  .. .. ..@ .Data    : list()
  .. .. ..@ names    : chr(0) 
  .. .. ..@ row.names: int(0) 
  .. .. ..@ .S3Class : chr "data.frame"
  ..@ idents        :Formal class 'factor' [package "methods"] with 3 slots
  .. .. ..@ .Data   : int(0) 
  .. .. ..@ levels  : chr(0) 
  .. .. ..@ .S3Class: chr "factor"
  ..@ DB            : list()
  ..@ LR            : list()
  ..@ var.features  : logi(0) 
  ..@ dr            : list()
  ..@ options       : list()

我們把metadata信息加到CellChat對(duì)象中猾编，這個(gè)寫(xiě)法跟Seurat很像啊瘤睹。

cellchat <- addMeta(cellchat, meta = identity, meta.name = "labels")
cellchat <- setIdent(cellchat, ident.use = "labels") # set "labels" as default cell identity
levels(cellchat@idents) # show factor levels of the cell labels

[1] "Naive CD4 T"  "Memory CD4 T" "CD14+ Mono"   "B"            "CD8 T"        "FCGR3A+ Mono" "NK"   


groupSize <- as.numeric(table(cellchat@idents)) # number of cells in each cell group

[1] 697 483 480 344 271 162 155  32  14

導(dǎo)入配受體數(shù)據(jù)庫(kù)

CellChat提供了人和小鼠的配受體數(shù)據(jù)庫(kù)，分別可以用CellChatDB.human,CellChatDB.mouse來(lái)導(dǎo)入答倡。來(lái)看一下這個(gè)數(shù)據(jù)庫(kù)的結(jié)構(gòu)吧默蚌。

CellChatDB <- CellChatDB.human 
(out3 <- capture.output(str(CellChatDB)))
out4 <- paste(out3, collapse="\n")
mm(gsub("\\$","# ",gsub("\\.\\. ","#",out4)),type ="text")

這個(gè)數(shù)據(jù)庫(kù)的信息是很全面的：

>  colnames(CellChatDB$interaction)
 [1] "interaction_name"   "pathway_name"       "ligand"             "receptor"           "agonist"            "antagonist"         "co_A_receptor"     
 [8] "co_I_receptor"      "evidence"           "annotation"         "interaction_name_2"
> CellChatDB$interaction[1:4,1:4]
                       interaction_name pathway_name ligand      receptor
TGFB1_TGFBR1_TGFBR2 TGFB1_TGFBR1_TGFBR2         TGFb  TGFB1     TGFbR1_R2
TGFB2_TGFBR1_TGFBR2 TGFB2_TGFBR1_TGFBR2         TGFb  TGFB2     TGFbR1_R2
TGFB3_TGFBR1_TGFBR2 TGFB3_TGFBR1_TGFBR2         TGFb  TGFB3     TGFbR1_R2
TGFB1_ACVR1B_TGFBR2 TGFB1_ACVR1B_TGFBR2         TGFb  TGFB1 ACVR1B_TGFbR2
> head(CellChatDB$cofactor)
                            cofactor1 cofactor2 cofactor3 cofactor4 cofactor5 cofactor6 cofactor7 cofactor8 cofactor9 cofactor10 cofactor11 cofactor12
ACTIVIN antagonist                FST                                                                                                                 
ACTIVIN inhibition receptor     BAMBI                                                                                                                 
ANGPT inhibition receptor 1      TIE1                                                                                                                 
ANGPT inhibition receptor 2     PTPRB                                                                                                                 
BMP antagonist                   NBL1     GREM1     GREM2      CHRD       NOG      BMP3    LEFTY1    LEFTY2                                           
BMP inhibition receptor         BAMBI                                                                                                                 
                            cofactor13 cofactor14 cofactor15 cofactor16
ACTIVIN antagonist                                                     
ACTIVIN inhibition receptor                                            
ANGPT inhibition receptor 1                                            
ANGPT inhibition receptor 2                                            
BMP antagonist                                                         
BMP inhibition receptor                                                
> head(CellChatDB$complex)
             subunit_1 subunit_2 subunit_3 subunit_4
Activin AB       INHBA     INHBB                    
Inhibin A         INHA     INHBA                    
Inhibin B         INHA     INHBB                    
IL12AB           IL12A     IL12B                    
IL23 complex     IL12B     IL23A                    
IL27 complex      IL27      EBI3                    
> head(CellChatDB$geneInfo)
             Symbol                           Name EntrezGene.ID Ensembl.Gene.ID      MGI.ID                                          Gene.group.name
HGNC:5         A1BG         alpha-1-B glycoprotein             1 ENSG00000121410 MGI:2152878                    Immunoglobulin like domain containing
HGNC:37133 A1BG-AS1           A1BG antisense RNA 1        503538 ENSG00000268895                                                       Antisense RNAs
HGNC:24086     A1CF APOBEC1 complementation factor         29974 ENSG00000148584 MGI:1917115                             RNA binding motif containing
HGNC:7          A2M          alpha-2-macroglobulin             2 ENSG00000175899 MGI:2449119 C3 and PZP like, alpha-2-macroglobulin domain containing
HGNC:27057  A2M-AS1            A2M antisense RNA 1        144571 ENSG00000245105                                                       Antisense RNAs
HGNC:23336    A2ML1   alpha-2-macroglobulin like 1        144568 ENSG00000166535             C3 and PZP like, alpha-2-macroglobulin domain containing

其實(shí)是記錄了許多許多受配體相關(guān)的通路信息，不像有的配受體庫(kù)只有一個(gè)基因?qū)ξ邸＿@樣绸吸，我們就可以更加扎實(shí)地把腳落到pathway上面了鼻弧。在CellChat中，我們還可以先擇特定的信息描述細(xì)胞間的相互作者锦茁，這個(gè)可以理解為從特定的側(cè)面來(lái)刻畫(huà)細(xì)胞間相互作用,比用一個(gè)大的配體庫(kù)又精細(xì)了許多呢攘轩。

CellChatDB.use <- subsetDB(CellChatDB, search = "Secreted Signaling") # use Secreted Signaling for cell-cell communication analysis
cellchat@DB <- CellChatDB.use # set the used database in the object

有哪些可以選擇的側(cè)面呢？

>  unique(CellChatDB$interaction$annotation)
[1] "Secreted Signaling" "ECM-Receptor"       "Cell-Cell Contact"

預(yù)處理

對(duì)表達(dá)數(shù)據(jù)進(jìn)行預(yù)處理码俩，用于細(xì)胞間的通信分析度帮。首先在一個(gè)細(xì)胞組中識(shí)別過(guò)表達(dá)的配體或受體，然后將基因表達(dá)數(shù)據(jù)投射到蛋白-蛋白相互作用(PPI)網(wǎng)絡(luò)上稿存。如果配體或受體過(guò)表達(dá)笨篷，則識(shí)別過(guò)表達(dá)配體和受體之間的相互作用。

cellchat <- subsetData(cellchat) # subset the expression data of signaling genes for saving computation cost
future::plan("multiprocess", workers = 4) # do parallel  這里似乎有一些bug，在Linux上居然不行。de了它泄伪。
cellchat <- identifyOverExpressedGenes(cellchat)
 cellchat <- identifyOverExpressedInteractions(cellchat)
cellchat <- projectData(cellchat, PPI.human)

相互作用推斷

然后季俩，我們通過(guò)為每個(gè)相互作用分配一個(gè)概率值并進(jìn)行置換檢驗(yàn)來(lái)推斷生物意義上的細(xì)胞-細(xì)胞通信松邪。

# cellchat <- computeCommunProb(cellchat)  注意這個(gè)函數(shù)如果你可以用就用，這個(gè)是作者的。
mycomputeCommunProb <-edit(computeCommunProb)  # computeCommunProb內(nèi)部似乎有一些bug，同一套數(shù)據(jù)在window10上沒(méi)事辜贵，到了Linux上有報(bào)錯(cuò)。發(fā)現(xiàn)是computeExpr_antagonist這個(gè)函數(shù)有問(wèn)題归形，(matrix(1, nrow = 1, ncol = length((group))))托慨，中應(yīng)為(matrix(1, nrow = 1, ncol = length(unique(group))))？ 不然矩陣返回的不對(duì)暇榴。de了它厚棵。
environment(mycomputeCommunProb) <- environment(computeCommunProb)
cellchat <- mycomputeCommunProb(cellchat)  # 這兒是我de過(guò)的。

關(guān)于這個(gè)bug跺撼。我在GitHub上向作者提出了窟感，并在20200727得到答復(fù)：已經(jīng)修訂讨彼。大家遇到問(wèn)題也可以直接在GitHub上提問(wèn)和回復(fù)歉井。下面是例子（與本文無(wú)關(guān)）：

進(jìn)入GitHub倉(cāng)庫(kù)：https://github.com/sqjin/CellChat，點(diǎn)擊Issues

就可以經(jīng)行提交問(wèn)題了哈误，對(duì)話框是支持markerdown語(yǔ)法的哩至。如我們的例子。

這個(gè)對(duì)話有兩點(diǎn)值得我們學(xué)習(xí)：

提問(wèn)者說(shuō)的很清楚蜜自，代碼具體到哪一行菩貌，而且給出了示例。
回答者很快檢查代碼重荠，并做了回應(yīng)箭阶。

好了，我們可以接著往下走了。

推測(cè)細(xì)胞間在信號(hào)通路水平上的通訊仇参。我們還通過(guò)計(jì)算與每個(gè)信號(hào)通路相關(guān)的所有配體-受體相互作用的通信概率來(lái)推斷信號(hào)通路水平上的通信概率嘹叫。
注:推測(cè)的每個(gè)配體-受體對(duì)的細(xì)胞間通信網(wǎng)絡(luò)和每個(gè)信號(hào)通路分別存儲(chǔ)在“net”和“netP”槽中。

我們可以通過(guò)計(jì)算鏈路的數(shù)量或匯總通信概率來(lái)計(jì)算細(xì)胞間的聚合通信網(wǎng)絡(luò)诈乒。

cellchat <- computeCommunProbPathway(cellchat)
cellchat <- aggregateNet(cellchat)

讓我們看看這結(jié)果罩扇。

> cellchat@netP$pathways
 [1] "TGFb"       "NRG"        "PDGF"       "CCL"        "CXCL"       "MIF"        "IL2"        "IL6"        "IL10"       "IL1"        "CSF"       
[12] "IL16"       "IFN-II"     "LT"         "LIGHT"      "FASLG"      "TRAIL"      "BAFF"       "CD40"       "VISFATIN"   "COMPLEMENT" "PARs"      
[23] "FLT3"       "ANNEXIN"    "GAS"        "GRN"        "GALECTIN"   "BTLA"       "BAG"       
> head(cellchat@LR$LRsig)
                       interaction_name pathway_name ligand      receptor      agonist      antagonist           co_A_receptor            co_I_receptor
TGFB1_TGFBR1_TGFBR2 TGFB1_TGFBR1_TGFBR2         TGFb  TGFB1     TGFbR1_R2 TGFb agonist TGFb antagonist                         TGFb inhibition receptor
TGFB1_ACVR1B_TGFBR2 TGFB1_ACVR1B_TGFBR2         TGFb  TGFB1 ACVR1B_TGFbR2 TGFb agonist TGFb antagonist                         TGFb inhibition receptor
TGFB1_ACVR1C_TGFBR2 TGFB1_ACVR1C_TGFBR2         TGFb  TGFB1 ACVR1C_TGFbR2 TGFb agonist TGFb antagonist                         TGFb inhibition receptor
TGFB1_ACVR1_TGFBR1   TGFB1_ACVR1_TGFBR1         TGFb  TGFB1   ACVR1_TGFbR                                                                              
WNT10A_FZD1_LRP5       WNT10A_FZD1_LRP5          WNT WNT10A     FZD1_LRP5  WNT agonist  WNT antagonist WNT activation receptor  WNT inhibition receptor
WNT10A_FZD2_LRP5       WNT10A_FZD2_LRP5          WNT WNT10A     FZD2_LRP5  WNT agonist  WNT antagonist WNT activation receptor  WNT inhibition receptor
                                          evidence         annotation      interaction_name_2
TGFB1_TGFBR1_TGFBR2                 KEGG: hsa04350 Secreted Signaling TGFB1 - (TGFBR1+TGFBR2)
TGFB1_ACVR1B_TGFBR2                 PMID: 27449815 Secreted Signaling TGFB1 - (ACVR1B+TGFBR2)
TGFB1_ACVR1C_TGFBR2                 PMID: 27449815 Secreted Signaling TGFB1 - (ACVR1C+TGFBR2)
TGFB1_ACVR1_TGFBR1                  PMID: 29376829 Secreted Signaling  TGFB1 - (ACVR1+TGFBR1)
WNT10A_FZD1_LRP5    KEGG: hsa04310; PMID: 23209157 Secreted Signaling    WNT10A - (FZD1+LRP5)
WNT10A_FZD2_LRP5    KEGG: hsa04310; PMID: 23209159 Secreted Signaling    WNT10A - (FZD2+LRP5)

可視化

在推斷細(xì)胞-細(xì)胞通信網(wǎng)絡(luò)的基礎(chǔ)上，CellChat為進(jìn)一步的探索怕磨、分析和可視化提供了各種功能喂饥。

通過(guò)結(jié)合社會(huì)網(wǎng)絡(luò)分析、模式識(shí)別和多種學(xué)習(xí)方法的綜合方法肠鲫，t可以定量地描述和比較推斷出的細(xì)胞-細(xì)胞通信網(wǎng)絡(luò)员帮。
它提供了一個(gè)易于使用的工具來(lái)提取和可視化推斷網(wǎng)絡(luò)的高階信息。例如滩届，它可以隨時(shí)預(yù)測(cè)所有細(xì)胞群的主要信號(hào)輸入和輸出集侯，以及這些細(xì)胞群和信號(hào)如何協(xié)調(diào)在一起實(shí)現(xiàn)功能。

你可以使用層次圖或圈圖可視化每個(gè)信號(hào)通路帜消。如果使用層次圖可視化通信網(wǎng)絡(luò)棠枉，請(qǐng)定義vertex.receiver，它是一個(gè)數(shù)字向量泡挺，給出作為第一個(gè)層次結(jié)構(gòu)圖中的目標(biāo)的細(xì)胞組的索引辈讶。我們可以使用netVisual_aggregate來(lái)可視化信號(hào)路徑的推斷通信網(wǎng)絡(luò)，并使用netVisual_individual來(lái)可視化與該信號(hào)路徑相關(guān)的單個(gè)L-R對(duì)的通信網(wǎng)絡(luò)娄猫。

在層次圖中贱除，實(shí)體圓和空心圓分別表示源和目標(biāo)。圓的大小與每個(gè)細(xì)胞組的細(xì)胞數(shù)成比例媳溺。邊緣顏色與信源一致月幌。線越粗，信號(hào)越強(qiáng)悬蔽。這里我們展示了一個(gè)MIF信號(hào)網(wǎng)絡(luò)的例子扯躺。所有顯示重要通信的信令路徑都可以通過(guò)cellchat@netP$pathways訪問(wèn)。

>cellchat@netP$pathways
 [1] "TGFb"       "NRG"        "PDGF"       "CCL"        "CXCL"       "MIF"        "IL2"        "IL6"        "IL10"       "IL1"       
[11] "CSF"        "IL16"       "IFN-II"     "LT"         "LIGHT"      "FASLG"      "TRAIL"      "BAFF"       "CD40"       "VISFATIN"  
[21] "COMPLEMENT" "PARs"       "FLT3"       "ANNEXIN"    "GAS"        "GRN"        "GALECTIN"   "BTLA"       "BAG"

levels(cellchat@idents) 
vertex.receiver = seq(1,4) # a numeric vector
# check the order of cell identity to set suitable vertex.receiver
#cellchat@LR$LRsig$pathway_name
#cellchat@LR$LRsig$antagonist
pathways.show <- "MIF"
# netVisual_aggregate(cellchat, signaling = pathways.show,  vertex.receiver = vertex.receiver, vertex.size = groupSize)   # 原函數(shù)
mynetVisual_aggregate(cellchat, signaling = pathways.show,  vertex.receiver = vertex.receiver, vertex.size = groupSize)  原函數(shù)這里似乎有一個(gè)和igraph相關(guān)的小問(wèn)題在不同igraph可能會(huì)表現(xiàn)bug蝎困，不巧我遇到了录语，de了它。

經(jīng)典的配受體圈圖：

mynetVisual_aggregate(cellchat, signaling = c("MIF"), layout = "circle", vertex.size = groupSize,pt.title=20,vertex.label.cex = 1.7)

計(jì)算和可視化每個(gè)配體-受體對(duì)整個(gè)信號(hào)通路的貢獻(xiàn)度禾乘。

netAnalysis_contribution(cellchat, signaling = pathways.show)

識(shí)別細(xì)胞群的信號(hào)轉(zhuǎn)導(dǎo)作用澎埠，通過(guò)計(jì)算每個(gè)細(xì)胞群的網(wǎng)絡(luò)中心性指標(biāo)，CellChat允許隨時(shí)識(shí)別細(xì)胞間通信網(wǎng)絡(luò)中的主要發(fā)送者始藕、接收者蒲稳、調(diào)解者和影響者氮趋。

cellchat <- netAnalysis_signalingRole(cellchat, slot.name = "netP") # the slot 'netP' means the inferred intercellular communication network of signaling pathways

···
netVisual_signalingRole(cellchat, signaling = pathways.show, width = 12, height = 2.5, font.size = 10)
···

識(shí)別特定細(xì)胞群的全局通信模式和主要信號(hào)。除了探索單個(gè)通路的詳細(xì)通訊外江耀，一個(gè)重要的問(wèn)題是多個(gè)細(xì)胞群和信號(hào)通路如何協(xié)調(diào)運(yùn)作凭峡。CellChat采用模式識(shí)別方法來(lái)識(shí)別全局通信模式以及每個(gè)小群的關(guān)鍵信號(hào)。

識(shí)別分泌細(xì)胞外向交流模式决记。隨著模式數(shù)量的增加摧冀，可能會(huì)出現(xiàn)冗余的模式，使得解釋通信模式變得困難系宫。我們選擇了5種模式作為默認(rèn)模式索昂。一般來(lái)說(shuō)，當(dāng)模式的數(shù)量大于2時(shí)就可以認(rèn)為具有生物學(xué)意義扩借。

nPatterns = 5 
# 同樣在這里遇到了bug椒惨，難道說(shuō)是我沒(méi)有安裝好嗎，de了它潮罪。
# cellchat <- myidentifyCommunicationPatterns(cellchat, pattern = "outgoing", k = nPatterns)  
myidentifyCommunicationPatterns <- edit(identifyCommunicationPatterns)
environment(myidentifyCommunicationPatterns) <- environment(identifyCommunicationPatterns)
cellchat <- myidentifyCommunicationPatterns(cellchat, pattern = "outgoing", k = nPatterns)

# Visualize the communication pattern using river plot
netAnalysis_river(cellchat, pattern = "outgoing")

# Visualize the communication pattern using dot plot
netAnalysis_dot(cellchat, pattern = "outgoing")

識(shí)別目標(biāo)細(xì)胞的傳入(incoming)通信模式康谆。

netAnalysis_river(cellchat, pattern = "incoming")

netAnalysis_dot(cellchat, pattern = "incoming")

作為結(jié)尾有大量的空間，我們得以先看看cellchat配受體推斷的結(jié)構(gòu)是如何的嫉到。

> head(cellchat@LR$LRsig)
                       interaction_name pathway_name ligand      receptor      agonist      antagonist           co_A_receptor            co_I_receptor
TGFB1_TGFBR1_TGFBR2 TGFB1_TGFBR1_TGFBR2         TGFb  TGFB1     TGFbR1_R2 TGFb agonist TGFb antagonist                         TGFb inhibition receptor
TGFB1_ACVR1B_TGFBR2 TGFB1_ACVR1B_TGFBR2         TGFb  TGFB1 ACVR1B_TGFbR2 TGFb agonist TGFb antagonist                         TGFb inhibition receptor
TGFB1_ACVR1C_TGFBR2 TGFB1_ACVR1C_TGFBR2         TGFb  TGFB1 ACVR1C_TGFbR2 TGFb agonist TGFb antagonist                         TGFb inhibition receptor
TGFB1_ACVR1_TGFBR1   TGFB1_ACVR1_TGFBR1         TGFb  TGFB1   ACVR1_TGFbR                                                                              
WNT10A_FZD1_LRP5       WNT10A_FZD1_LRP5          WNT WNT10A     FZD1_LRP5  WNT agonist  WNT antagonist WNT activation receptor  WNT inhibition receptor
WNT10A_FZD2_LRP5       WNT10A_FZD2_LRP5          WNT WNT10A     FZD2_LRP5  WNT agonist  WNT antagonist WNT activation receptor  WNT inhibition receptor
                                          evidence         annotation      interaction_name_2
TGFB1_TGFBR1_TGFBR2                 KEGG: hsa04350 Secreted Signaling TGFB1 - (TGFBR1+TGFBR2)
TGFB1_ACVR1B_TGFBR2                 PMID: 27449815 Secreted Signaling TGFB1 - (ACVR1B+TGFBR2)
TGFB1_ACVR1C_TGFBR2                 PMID: 27449815 Secreted Signaling TGFB1 - (ACVR1C+TGFBR2)
TGFB1_ACVR1_TGFBR1                  PMID: 29376829 Secreted Signaling  TGFB1 - (ACVR1+TGFBR1)
WNT10A_FZD1_LRP5    KEGG: hsa04310; PMID: 23209157 Secreted Signaling    WNT10A - (FZD1+LRP5)
WNT10A_FZD2_LRP5    KEGG: hsa04310; PMID: 23209159 Secreted Signaling    WNT10A - (FZD2+LRP5)
> head(cellchat@dr)
list()
> head(cellchat@data)
6 x 2638 sparse Matrix of class "dgCMatrix"
   [[ suppressing 70 column names 'AAACATACAACCAC', 'AAACATTGAGCTAC', 'AAACATTGATCAGC' ... ]]
                                                                                                                                                      
AL627309.1    . . . . . . . . . . . .        . . . . . . . . .        . . . . . . . . . . . . .       . . . . . . . .       .        . . . . . . . . .
AP006222.2    . . . . . . . . . . . .        . . . . . . . . .        . . . . . . . . . . . . .       . . . . . . . .       .        . . . . . . . . .
RP11-206L10.2 . . . . . . . . . . . .        . . . . . . . . .        . . . . . . . . . . . . .       . . . . . . . .       .        . . . . . . . . .
RP11-206L10.9 . . . . . . . . . . . .        . . . . . . . . .        . . . . . . . . . . . . .       . . . . . . . .       .        . . . . . . . . .
LINC00115     . . . . . . . . . . . .        . . . . . . . . .        . . . . . . . . . . . . .       . . . . . . . .       .        . . . . . . . . .
NOC2L         . . . . . . . . . . . 1.646272 . . . . . . . . 1.398186 . . . . . . . . . . . . 1.89939 . . . . . . . 1.36907 1.721224 . . . . . . . . .
                                                                                    
AL627309.1    . . . .        .        . .        . . .        . . . . . . . . ......
AP006222.2    . . . .        .        . .        . . .        . . . . . . . . ......
RP11-206L10.2 . . . .        .        . .        . . .        . . . . . . . . ......
RP11-206L10.9 . . . .        .        . .        . . .        . . . . . . . . ......
LINC00115     . . . .        .        . .        . . .        . . . . . . . . ......
NOC2L         . . . 1.568489 1.678814 . 1.253835 . . 3.791113 . . . . . . . . ......

 .....suppressing 2568 columns in show(); maybe adjust 'options(max.print= *, width = *)'
 ..............................
> head(cellchat@idents)
[1] Memory CD4 T B            Memory CD4 T CD14+ Mono   NK           Memory CD4 T
Levels: Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
> head(cellchat@meta)
                     labels
AAACATACAACCAC Memory CD4 T
AAACATTGAGCTAC            B
AAACATTGATCAGC Memory CD4 T
AAACCGTGCTTCCG   CD14+ Mono
AAACCGTGTATGCG           NK
AAACGCACTGGTAC Memory CD4 T
> head(cellchat@netP$pathways)
[1] "TGFb" "NRG"  "PDGF" "CCL"  "CXCL" "MIF" 
> head(cellchat@netP$prob)
[1] 0 0 0 0 0 0
> head(cellchat@netP$centr)
$TGFb
$TGFb$outdeg
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
0.000000e+00 5.798502e-07 2.634094e-05 0.000000e+00 1.108822e-06 9.977646e-06 9.953461e-06 2.840617e-07 3.475282e-06 

$TGFb$indeg
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
0.000000e+00 1.002762e-05 1.384499e-05 0.000000e+00 7.596075e-06 1.270618e-05 5.256794e-06 5.744824e-07 1.713913e-06 

$TGFb$hub
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.00000000   0.02278982   1.00000000   0.00000000   0.04484954   0.37878876   0.37787064   0.01116456   0.13193619 

$TGFb$authority
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.00000000   0.74712407   1.00000000   0.00000000   0.56314554   0.86435263   0.37969073   0.04280264   0.11659336 

$TGFb$eigen
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.01217244   0.31304003   1.00000000   0.01217244   0.25802457   0.58202001   0.37843282   0.02320534   0.12622971 

$TGFb$page_rank
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.02054795   0.13742492   0.21555291   0.02054795   0.11208641   0.31212523   0.09458943   0.02724384   0.05988138 

$TGFb$betweenness
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
           0            0           24            0            0           10            0            0            0 

$TGFb$flowbet
[1] 0.000000e+00 4.342669e-06 2.862661e-05 0.000000e+00 6.752863e-06 2.460332e-05 1.254051e-05 1.032200e-06 6.967716e-06

$TGFb$info
[1] 0.00000000 0.16628670 0.19401551 0.00000000 0.12870372 0.18191312 0.16895822 0.03556505 0.12455769


$NRG
$NRG$outdeg
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
1.116774e-10 1.024289e-10 2.194763e-10 5.436629e-11 5.792191e-11 1.166520e-10 4.634672e-11 1.511780e-11 1.629172e-12 

$NRG$indeg
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 7.256165e-10 

$NRG$hub
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
 0.508835533  0.466696996  1.000000000  0.247709130  0.263909627  0.531501345  0.211169583  0.068881216  0.007422998 

$NRG$authority
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
4.163336e-17 4.163336e-17 4.163336e-17 4.163336e-17 4.163336e-17 4.163336e-17 4.163336e-17 4.163336e-17 1.000000e+00 

$NRG$eigen
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.36342198   0.33332567   0.71422288   0.17691953   0.18849029   0.37961042   0.15082215   0.04919654   1.00000000 

$NRG$page_rank
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.01666667   0.01666667   0.01666667   0.01666667   0.01666667   0.01666667   0.01666667   0.01666667   0.86666667 

$NRG$betweenness
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
           0            0            0            0            0            0            0            0            0 

$NRG$flowbet
[1] 0 0 0 0 0 0 0 0 0

$NRG$info
[1] 0 0 0 0 0 0 0 0 0


$PDGF
$PDGF$outdeg
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
2.117157e-10 5.254122e-10 1.830680e-09 0.000000e+00 3.046756e-10 1.195279e-09 6.457814e-10 1.492427e-10 0.000000e+00 

$PDGF$indeg
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
9.596760e-10 7.355168e-10 1.375790e-09 0.000000e+00 4.145239e-10 1.028332e-09 2.501300e-10 9.881712e-11 0.000000e+00 

$PDGF$hub
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.09759699   0.32222056   1.00000000   0.00000000   0.18684898   0.65291566   0.35275497   0.08152314   0.00000000 

$PDGF$authority
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
9.058608e-01 6.942716e-01 1.000000e+00 2.363558e-17 3.912788e-01 6.197010e-01 2.361036e-01 7.182571e-02 2.363558e-17 

$PDGF$eigen
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.44237332   0.51181753   1.00000000   0.07396075   0.29250188   0.67517921   0.29135234   0.07823533   0.07396075 

$PDGF$page_rank
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.15091590   0.12046482   0.24044555   0.02054795   0.07685927   0.27934926   0.05452706   0.03634225   0.02054795 

$PDGF$betweenness
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
           1            0           18            0            0            5            0            0            0 

$PDGF$flowbet
[1] 8.857166e-10 1.204604e-09 4.049689e-09 0.000000e+00 8.517939e-10 3.745196e-09 1.048193e-09 4.458839e-10 0.000000e+00

$PDGF$info
[1] 0.16144948 0.14611532 0.20300365 0.00000000 0.10956327 0.17885050 0.14080069 0.06021709 0.00000000


$CCL
$CCL$outdeg
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
1.682814e-04 6.442088e-04 9.328993e-04 9.764691e-05 4.601953e-03 1.067399e-05 2.613615e-03 5.048297e-05 2.374245e-04 

$CCL$indeg
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
1.013085e-03 1.208426e-03 4.952297e-04 5.869028e-04 3.900117e-03 1.125963e-04 1.773075e-03 7.483047e-05 1.929230e-04 

$CCL$hub
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
 0.050735945  0.193934101  0.210819077  0.029282445  1.000000000  0.003249727  0.551908511  0.013914236  0.052892139 

$CCL$authority
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.30095289   0.35990610   0.14750945   0.17431275   1.00000000   0.03323390   0.45558530   0.02222082   0.04989215 

$CCL$eigen
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.17214374   0.27750548   0.17861545   0.09964869   1.00000000   0.01772801   0.50285164   0.01802822   0.05152917 

$CCL$page_rank
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.08937815   0.10366984   0.05186354   0.05878616   0.41583926   0.02465234   0.19773523   0.02202754   0.03604793 

$CCL$betweenness
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
           0            0            0            0           56            0            0            0            0 

$CCL$flowbet
[1] 6.253950e-04 1.206020e-03 1.184412e-03 4.216339e-04 7.464863e-03 7.286026e-05 3.851205e-03 1.024123e-04 5.393918e-04

$CCL$info
[1] 0.13488584 0.13862093 0.12659975 0.11726949 0.15963716 0.03961851 0.15306688 0.04024833 0.09005310


$CXCL
$CXCL$outdeg
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 2.948861e-08 

$CXCL$indeg
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
6.251119e-09 5.660697e-09 4.984283e-09 2.735102e-09 2.997064e-09 3.851281e-09 2.461799e-09 4.823805e-10 6.488065e-11 

$CXCL$hub
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
           0            0            0            0            0            0            0            0            1 

$CXCL$authority
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  1.00000000   0.90554935   0.79734257   0.43753795   0.47944431   0.61609465   0.39381731   0.07716707   0.01037905 

$CXCL$eigen
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
   0.5394037    0.4884566    0.4300895    0.2360096    0.2586140    0.3323237    0.2124265    0.0416242    1.0000000 

$CXCL$page_rank
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
   0.1198308    0.1181000    0.1161172    0.1095240    0.1102919    0.1127960    0.1087229    0.1029205    0.1016966 

$CXCL$betweenness
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
           0            0            0            0            0            0            0            0            0 

$CXCL$flowbet
[1] 0 0 0 0 0 0 0 0 0

$CXCL$info
[1] 0.12994155 0.12702636 0.12305974 0.10129559 0.10488823 0.11427509 0.09707279 0.03583427 0.16660638


$MIF
$MIF$outdeg
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
0.0012989751 0.0039272021 0.0006234461 0.0006401726 0.0005135156 0.0002049902 0.0003848437 0.0001321595 0.0000000000 

$MIF$indeg
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
0.0005188736 0.0008184262 0.0007859180 0.0035144980 0.0009227472 0.0008137752 0.0001170739 0.0002339928 0.0000000000 

$MIF$hub
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
4.252550e-01 1.000000e+00 2.238501e-01 2.095786e-01 1.680262e-01 7.360549e-02 1.160678e-01 4.315756e-02 2.774719e-18 

$MIF$authority
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
2.769140e-01 4.020539e-01 2.249636e-01 1.000000e+00 3.209851e-01 2.590427e-01 6.228011e-02 7.151140e-02 4.690529e-18 

$MIF$eigen
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.40785736   1.00000000   0.28217435   0.81714092   0.31062247   0.21639268   0.11882053   0.07323643   0.01492405 

$MIF$page_rank
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
  0.02128513   0.02564654   0.12732754   0.50874503   0.11392566   0.11715499   0.01911107   0.04839913   0.01840491 

$MIF$betweenness
 Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet 
           0           10            0           17           14            0           11            0            0 

$MIF$flowbet
[1] 0.0010772004 0.0004430504 0.0013253722 0.0018828736 0.0013830050 0.0007361476 0.0002572374 0.0005064761 0.0000000000

$MIF$info
[1] 0.10896205 0.16504074 0.11589344 0.17947163 0.13549734 0.10051455 0.12311142 0.07150883 0.00000000

每個(gè)pattern有outgoing和ingoing兩種沃暗。


> head(cellchat@netP$pattern$outgoing$pattern$cell)
     CellGroup   Pattern Contribution
1  Naive CD4 T Pattern 1 9.182571e-01
2 Memory CD4 T Pattern 1 8.643879e-01
3   CD14+ Mono Pattern 1 6.958107e-04
4            B Pattern 1 8.943340e-01
5        CD8 T Pattern 1 8.497941e-02
6 FCGR3A+ Mono Pattern 1 2.351798e-05
> head(cellchat@netP$pattern$outgoing$pattern$signaling)
    Pattern Signaling Contribution
1 Pattern 1      TGFb 1.509635e-08
2 Pattern 2      TGFb 5.851347e-01
3 Pattern 3      TGFb 2.021400e-01
4 Pattern 4      TGFb 4.466321e-08
5 Pattern 5      TGFb 2.127253e-01
6 Pattern 1       NRG 3.333424e-01
> head(cellchat@netP$pattern$outgoing$data)
                   TGFb       NRG      PDGF         CCL CXCL        MIF         IL2        IL6        IL10          IL1          CSF IL16      IFN-II
Naive CD4 T  0.00000000 0.5088355 0.1156487 0.036567375    0 0.33076349 1.000000000 0.21361180 0.017388599 1.043256e-04 0.0006363636    0 0.004454402
Memory CD4 T 0.02201327 0.4666970 0.2870039 0.139985939    0 1.00000000 0.948036204 0.22211580 1.000000000 1.150654e-04 0.0006048585    0 0.004707477
CD14+ Mono   1.00000000 1.0000000 1.0000000 0.202718122    0 0.15875069 0.000000000 0.09461735 0.005818249 1.000000e+00 0.0010788329    0 0.005461241
B            0.00000000 0.2477091 0.0000000 0.021218579    0 0.16300984 0.009150461 0.02181469 0.003863723 2.876928e-05 0.0002110580    0 0.001720322
CD8 T        0.04209499 0.2639096 0.1664276 1.000000000    0 0.13075865 0.475620565 0.12534217 0.527133566 4.519162e-05 0.0003131413    0 0.003303116
FCGR3A+ Mono 0.37878860 0.5315013 0.6529157 0.002319449    0 0.05219751 0.000000000 0.03752352 0.253673778 7.630358e-05 1.0000000000    0 0.004745991
                    LT     LIGHT      FASLG      TRAIL         BAFF         CD40 VISFATIN COMPLEMENT PARs         FLT3      ANNEXIN        GAS
Naive CD4 T  1.0000000 0.0000000 0.12801302 0.00000000 1.987539e-04 0.0052298348        0  1.0000000    0 1.0000000000 0.3515932720 0.02399186
Memory CD4 T 0.8516886 1.0000000 0.85744830 0.09989685 2.286423e-04 1.0000000000        0  0.9403386    0 0.6925428133 1.0000000000 0.03584303
CD14+ Mono   0.0512085 0.0000000 1.00000000 1.00000000 1.000000e+00 0.0080996253        0  0.8803694    0 0.0006179983 0.7171291990 0.02706222
B            0.5629699 0.0000000 0.06312626 0.00000000 8.393504e-05 0.0003093270        0  0.3587101    0 0.0003490343 0.0003780528 0.01054186
CD8 T        0.1842115 0.0000000 0.08407400 0.00000000 6.513411e-05 0.0008636328        0  0.5033253    1 0.0004055095 0.4595993742 0.01898338
FCGR3A+ Mono 0.0832080 0.2745868 0.63644930 0.93360412 3.279022e-01 0.0044454725        1  0.3187685    0 0.0002367928 0.2119665274 0.01193921
                   GRN  GALECTIN      BTLA       BAG
Naive CD4 T  0.0000000 0.0000000 0.0000000 1.0000000
Memory CD4 T 0.0000000 0.0000000 1.0000000 0.9388102
CD14+ Mono   1.0000000 0.8983294 0.0000000 0.7920962
B            0.0000000 0.0000000 0.5998942 0.4454517
CD8 T        0.0000000 0.0000000 0.0000000 0.4831780
FCGR3A+ Mono 0.1277283 1.0000000 0.2785847 0.3247730
> cellchat@net
$prob
, , TGFB1_TGFBR1_TGFBR2

              Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet
Naive CD4 T  1.222691e-11 1.692462e-09 2.264589e-09 4.620186e-12 1.291360e-09 1.960243e-09 8.655394e-10 9.634429e-11 2.629338e-10
Memory CD4 T 2.270338e-09 3.142597e-07 4.204920e-07 8.578932e-10 2.397814e-07 3.639734e-07 1.607142e-07 1.788942e-08 4.882008e-08
CD14+ Mono   2.719456e-08 3.763876e-06 5.036034e-06 1.027602e-08 2.871745e-06 4.358185e-06 1.924748e-06 2.142640e-07 5.844517e-07
B            3.582287e-12 4.958639e-10 6.634879e-10 1.353639e-12 3.783474e-10 5.743193e-10 2.535890e-10 2.822731e-11 7.703534e-11
CD8 T        1.736672e-09 2.403890e-07 3.216497e-07 6.562368e-10 1.834175e-07 2.784145e-07 1.229360e-07 1.368429e-08 3.734375e-08
FCGR3A+ Mono 1.030133e-08 1.425741e-06 1.907620e-06 3.892565e-09 1.087800e-06 1.650808e-06 7.290809e-07 8.116246e-08 2.213748e-07
NK           1.027623e-08 1.422259e-06 1.902958e-06 3.883081e-09 1.085141e-06 1.646755e-06 7.272983e-07 8.096435e-08 2.208291e-07
DC           1.112404e-09 1.539695e-07 2.060130e-07 4.203442e-10 1.174768e-07 1.783002e-07 7.873805e-08 8.764877e-09 2.391283e-08
Platelet     3.590036e-09 4.966840e-07 6.644667e-07 1.356569e-09 3.789035e-07 5.745492e-07 2.539314e-07 2.827603e-08 7.699129e-08

, , TGFB1_ACVR1B_TGFBR2

              Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet
Naive CD4 T  8.440868e-12 3.075855e-10 4.274550e-10 3.315884e-12 2.229500e-10 3.681800e-10 1.570298e-10 1.834846e-11 4.756356e-11
Memory CD4 T 1.567331e-09 5.711352e-08 7.937122e-08 6.157055e-10 4.139808e-08 6.836461e-08 2.915780e-08 3.407004e-09 8.831697e-09
CD14+ Mono   1.877381e-08 6.841044e-07 9.506996e-07 7.375044e-09 4.958626e-07 8.188301e-07 3.492476e-07 4.080909e-08 1.057772e-07
B            2.473037e-12 9.011756e-11 1.252374e-10 9.715001e-13 6.532072e-11 1.078708e-10 4.600719e-11 5.375799e-12 1.393535e-11
CD8 T        1.198914e-09 4.368838e-08 6.071417e-08 4.709778e-10 3.166702e-08 5.229470e-08 2.230394e-08 2.606152e-09 6.755695e-09
FCGR3A+ Mono 7.111536e-09 2.591388e-07 3.601247e-07 2.793674e-09 1.878326e-07 3.101709e-07 1.322948e-07 1.545849e-08 4.006799e-08
NK           7.094210e-09 2.585072e-07 3.592468e-07 2.786868e-09 1.873748e-07 3.094142e-07 1.319723e-07 1.542082e-08 3.997016e-08
DC           7.679496e-10 2.798377e-08 3.888915e-08 3.016789e-10 2.028365e-08 3.349550e-08 1.428628e-08 1.669323e-09 4.327040e-09
Platelet     2.478389e-09 9.030435e-08 1.254923e-07 9.736029e-10 6.545434e-08 1.080686e-07 4.610002e-08 5.386992e-09 1.395861e-08

, , TGFB1_ACVR1C_TGFBR2

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            0            0          0 0     0            0  0  0        0
Memory CD4 T           0            0          0 0     0            0  0  0        0
CD14+ Mono             0            0          0 0     0            0  0  0        0
B                      0            0          0 0     0            0  0  0        0
CD8 T                  0            0          0 0     0            0  0  0        0
FCGR3A+ Mono           0            0          0 0     0            0  0  0        0
NK                     0            0          0 0     0            0  0  0        0
DC                     0            0          0 0     0            0  0  0        0
Platelet               0            0          0 0     0            0  0  0        0

, , TGFB1_ACVR1_TGFBR1

              Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet
Naive CD4 T  1.189109e-11 3.873823e-10 4.965448e-10 4.544316e-12 2.846539e-10 4.232163e-10 1.881368e-10 2.208094e-11 6.074030e-11
Memory CD4 T 2.207939e-09 7.192901e-08 9.219821e-08 8.437887e-10 5.285441e-08 7.858227e-08 3.493314e-08 4.099982e-09 1.127813e-08
CD14+ Mono   2.644406e-08 8.614599e-07 1.104207e-06 1.010590e-08 6.330077e-07 9.410925e-07 4.183726e-07 4.910372e-08 1.350587e-07
B            3.484106e-12 1.135035e-10 1.454883e-10 1.331490e-12 8.340397e-11 1.240029e-10 5.512432e-11 6.469743e-12 1.779699e-11
CD8 T        1.688886e-09 5.501955e-08 7.052374e-08 6.454268e-10 4.042910e-08 6.010862e-08 2.672085e-08 3.136136e-09 8.626777e-09
FCGR3A+ Mono 1.001622e-08 3.262944e-07 4.182392e-07 3.827814e-09 2.397636e-07 3.564543e-07 1.584664e-07 1.859898e-08 5.115538e-08
NK           9.993118e-09 3.255413e-07 4.172736e-07 3.818983e-09 2.392101e-07 3.556306e-07 1.581005e-07 1.855606e-08 5.103702e-08
DC           1.081809e-09 3.524210e-08 4.517296e-08 4.134256e-10 2.589626e-08 3.850073e-08 1.711561e-08 2.008818e-09 5.525462e-09
Platelet     3.490750e-09 1.137069e-07 1.457441e-07 1.334030e-09 8.355043e-08 1.241924e-07 5.521981e-08 6.481446e-09 1.781969e-08

, , WNT10A_FZD1_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            0            0          0 0     0            0  0  0        0
Memory CD4 T           0            0          0 0     0            0  0  0        0
CD14+ Mono             0            0          0 0     0            0  0  0        0
B                      0            0          0 0     0            0  0  0        0
CD8 T                  0            0          0 0     0            0  0  0        0
FCGR3A+ Mono           0            0          0 0     0            0  0  0        0
NK                     0            0          0 0     0            0  0  0        0
DC                     0            0          0 0     0            0  0  0        0
Platelet               0            0          0 0     0            0  0  0        0

, , WNT10A_FZD2_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            0            0          0 0     0            0  0  0        0
Memory CD4 T           0            0          0 0     0            0  0  0        0
CD14+ Mono             0            0          0 0     0            0  0  0        0
B                      0            0          0 0     0            0  0  0        0
CD8 T                  0            0          0 0     0            0  0  0        0
FCGR3A+ Mono           0            0          0 0     0            0  0  0        0
NK                     0            0          0 0     0            0  0  0        0
DC                     0            0          0 0     0            0  0  0        0
Platelet               0            0          0 0     0            0  0  0        0

, , WNT10A_FZD3_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            0            0          0 0     0            0  0  0        0
Memory CD4 T           0            0          0 0     0            0  0  0        0
CD14+ Mono             0            0          0 0     0            0  0  0        0
B                      0            0          0 0     0            0  0  0        0
CD8 T                  0            0          0 0     0            0  0  0        0
FCGR3A+ Mono           0            0          0 0     0            0  0  0        0
NK                     0            0          0 0     0            0  0  0        0
DC                     0            0          0 0     0            0  0  0        0
Platelet               0            0          0 0     0            0  0  0        0

, , WNT10A_FZD6_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            0            0          0 0     0            0  0  0        0
Memory CD4 T           0            0          0 0     0            0  0  0        0
CD14+ Mono             0            0          0 0     0            0  0  0        0
B                      0            0          0 0     0            0  0  0        0
CD8 T                  0            0          0 0     0            0  0  0        0
FCGR3A+ Mono           0            0          0 0     0            0  0  0        0
NK                     0            0          0 0     0            0  0  0        0
DC                     0            0          0 0     0            0  0  0        0
Platelet               0            0          0 0     0            0  0  0        0

, , WNT10B_FZD1_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            0            0          0 0     0            0  0  0        0
Memory CD4 T           0            0          0 0     0            0  0  0        0
CD14+ Mono             0            0          0 0     0            0  0  0        0
B                      0            0          0 0     0            0  0  0        0
CD8 T                  0            0          0 0     0            0  0  0        0
FCGR3A+ Mono           0            0          0 0     0            0  0  0        0
NK                     0            0          0 0     0            0  0  0        0
DC                     0            0          0 0     0            0  0  0        0
Platelet               0            0          0 0     0            0  0  0        0

, , WNT10B_FZD2_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            0            0          0 0     0            0  0  0        0
Memory CD4 T           0            0          0 0     0            0  0  0        0
CD14+ Mono             0            0          0 0     0            0  0  0        0
B                      0            0          0 0     0            0  0  0        0
CD8 T                  0            0          0 0     0            0  0  0        0
FCGR3A+ Mono           0            0          0 0     0            0  0  0        0
NK                     0            0          0 0     0            0  0  0        0
DC                     0            0          0 0     0            0  0  0        0
Platelet               0            0          0 0     0            0  0  0        0

, , WNT10B_FZD3_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            0            0          0 0     0            0  0  0        0
Memory CD4 T           0            0          0 0     0            0  0  0        0
CD14+ Mono             0            0          0 0     0            0  0  0        0
B                      0            0          0 0     0            0  0  0        0
CD8 T                  0            0          0 0     0            0  0  0        0
FCGR3A+ Mono           0            0          0 0     0            0  0  0        0
NK                     0            0          0 0     0            0  0  0        0
DC                     0            0          0 0     0            0  0  0        0
Platelet               0            0          0 0     0            0  0  0        0

, , WNT10B_FZD6_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            0            0          0 0     0            0  0  0        0
Memory CD4 T           0            0          0 0     0            0  0  0        0
CD14+ Mono             0            0          0 0     0            0  0  0        0
B                      0            0          0 0     0            0  0  0        0
CD8 T                  0            0          0 0     0            0  0  0        0
FCGR3A+ Mono           0            0          0 0     0            0  0  0        0
NK                     0            0          0 0     0            0  0  0        0
DC                     0            0          0 0     0            0  0  0        0
Platelet               0            0          0 0     0            0  0  0        0

, , WNT16_FZD1_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            0            0          0 0     0            0  0  0        0
Memory CD4 T           0            0          0 0     0            0  0  0        0
CD14+ Mono             0            0          0 0     0            0  0  0        0

 [ reached getOption("max.print") -- omitted 6 row(s) and 114 matrix slice(s) ]

$pval
, , TGFB1_TGFBR1_TGFBR2

             Naive CD4 T Memory CD4 T CD14+ Mono    B CD8 T FCGR3A+ Mono   NK   DC Platelet
Naive CD4 T         1.00         1.00       1.00 1.00  1.00         1.00 1.00 0.99     0.56
Memory CD4 T        1.00         0.67       0.39 1.00  0.33         0.00 0.15 0.44     0.01
CD14+ Mono          0.87         0.00       0.00 0.80  0.00         0.00 0.00 0.00     0.00
B                   1.00         1.00       0.98 1.00  0.99         0.95 0.95 0.99     0.69
CD8 T               1.00         0.36       0.04 0.99  0.07         0.00 0.00 0.44     0.00
FCGR3A+ Mono        0.73         0.00       0.00 0.67  0.00         0.00 0.00 0.00     0.00
NK                  0.74         0.00       0.00 0.70  0.00         0.00 0.00 0.01     0.00
DC                  0.70         0.20       0.21 0.68  0.22         0.00 0.10 0.26     0.01
Platelet            0.52         0.00       0.00 0.48  0.00         0.00 0.00 0.00     0.00

, , TGFB1_ACVR1B_TGFBR2

             Naive CD4 T Memory CD4 T CD14+ Mono    B CD8 T FCGR3A+ Mono   NK   DC Platelet
Naive CD4 T         1.00         1.00       1.00 1.00  1.00         1.00 1.00 0.99     0.94
Memory CD4 T        1.00         0.73       0.39 1.00  0.48         0.00 0.24 0.46     0.02
CD14+ Mono          0.87         0.00       0.00 0.78  0.00         0.00 0.00 0.00     0.00
B                   1.00         1.00       0.99 1.00  0.99         0.97 0.96 0.99     0.92
CD8 T               0.92         0.39       0.04 0.93  0.16         0.00 0.00 0.45     0.00
FCGR3A+ Mono        0.71         0.00       0.00 0.67  0.00         0.00 0.00 0.00     0.00
NK                  0.75         0.00       0.00 0.70  0.00         0.00 0.00 0.01     0.00
DC                  0.66         0.21       0.21 0.64  0.23         0.00 0.10 0.26     0.01
Platelet            0.42         0.00       0.00 0.42  0.00         0.00 0.00 0.00     0.00

, , TGFB1_ACVR1C_TGFBR2

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            1            1          1 1     1            1  1  1        1
Memory CD4 T           1            1          1 1     1            1  1  1        1
CD14+ Mono             1            1          1 1     1            1  1  1        1
B                      1            1          1 1     1            1  1  1        1
CD8 T                  1            1          1 1     1            1  1  1        1
FCGR3A+ Mono           1            1          1 1     1            1  1  1        1
NK                     1            1          1 1     1            1  1  1        1
DC                     1            1          1 1     1            1  1  1        1
Platelet               1            1          1 1     1            1  1  1        1

, , TGFB1_ACVR1_TGFBR1

             Naive CD4 T Memory CD4 T CD14+ Mono    B CD8 T FCGR3A+ Mono   NK   DC Platelet
Naive CD4 T         1.00         1.00       1.00 1.00  1.00         1.00 1.00 0.99     0.95
Memory CD4 T        1.00         0.75       0.46 1.00  0.38         0.00 0.22 0.47     0.02
CD14+ Mono          0.88         0.00       0.00 0.80  0.00         0.00 0.00 0.00     0.00
B                   1.00         1.00       1.00 1.00  0.99         0.97 0.98 0.99     0.91
CD8 T               0.92         0.38       0.05 0.92  0.05         0.00 0.00 0.46     0.00
FCGR3A+ Mono        0.71         0.00       0.00 0.67  0.00         0.00 0.00 0.00     0.00
NK                  0.76         0.00       0.00 0.71  0.00         0.00 0.00 0.02     0.00
DC                  0.66         0.21       0.23 0.63  0.23         0.00 0.12 0.25     0.01
Platelet            0.40         0.00       0.00 0.40  0.00         0.00 0.00 0.00     0.00

, , WNT10A_FZD1_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            1            1          1 1     1            1  1  1        1
Memory CD4 T           1            1          1 1     1            1  1  1        1
CD14+ Mono             1            1          1 1     1            1  1  1        1
B                      1            1          1 1     1            1  1  1        1
CD8 T                  1            1          1 1     1            1  1  1        1
FCGR3A+ Mono           1            1          1 1     1            1  1  1        1
NK                     1            1          1 1     1            1  1  1        1
DC                     1            1          1 1     1            1  1  1        1
Platelet               1            1          1 1     1            1  1  1        1

, , WNT10A_FZD2_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            1            1          1 1     1            1  1  1        1
Memory CD4 T           1            1          1 1     1            1  1  1        1
CD14+ Mono             1            1          1 1     1            1  1  1        1
B                      1            1          1 1     1            1  1  1        1
CD8 T                  1            1          1 1     1            1  1  1        1
FCGR3A+ Mono           1            1          1 1     1            1  1  1        1
NK                     1            1          1 1     1            1  1  1        1
DC                     1            1          1 1     1            1  1  1        1
Platelet               1            1          1 1     1            1  1  1        1

, , WNT10A_FZD3_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            1            1          1 1     1            1  1  1        1
Memory CD4 T           1            1          1 1     1            1  1  1        1
CD14+ Mono             1            1          1 1     1            1  1  1        1
B                      1            1          1 1     1            1  1  1        1
CD8 T                  1            1          1 1     1            1  1  1        1
FCGR3A+ Mono           1            1          1 1     1            1  1  1        1
NK                     1            1          1 1     1            1  1  1        1
DC                     1            1          1 1     1            1  1  1        1
Platelet               1            1          1 1     1            1  1  1        1

, , WNT10A_FZD6_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            1            1          1 1     1            1  1  1        1
Memory CD4 T           1            1          1 1     1            1  1  1        1
CD14+ Mono             1            1          1 1     1            1  1  1        1
B                      1            1          1 1     1            1  1  1        1
CD8 T                  1            1          1 1     1            1  1  1        1
FCGR3A+ Mono           1            1          1 1     1            1  1  1        1
NK                     1            1          1 1     1            1  1  1        1
DC                     1            1          1 1     1            1  1  1        1
Platelet               1            1          1 1     1            1  1  1        1

, , WNT10B_FZD1_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            1            1          1 1     1            1  1  1        1
Memory CD4 T           1            1          1 1     1            1  1  1        1
CD14+ Mono             1            1          1 1     1            1  1  1        1
B                      1            1          1 1     1            1  1  1        1
CD8 T                  1            1          1 1     1            1  1  1        1
FCGR3A+ Mono           1            1          1 1     1            1  1  1        1
NK                     1            1          1 1     1            1  1  1        1
DC                     1            1          1 1     1            1  1  1        1
Platelet               1            1          1 1     1            1  1  1        1

, , WNT10B_FZD2_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            1            1          1 1     1            1  1  1        1
Memory CD4 T           1            1          1 1     1            1  1  1        1
CD14+ Mono             1            1          1 1     1            1  1  1        1
B                      1            1          1 1     1            1  1  1        1
CD8 T                  1            1          1 1     1            1  1  1        1
FCGR3A+ Mono           1            1          1 1     1            1  1  1        1
NK                     1            1          1 1     1            1  1  1        1
DC                     1            1          1 1     1            1  1  1        1
Platelet               1            1          1 1     1            1  1  1        1

, , WNT10B_FZD3_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            1            1          1 1     1            1  1  1        1
Memory CD4 T           1            1          1 1     1            1  1  1        1
CD14+ Mono             1            1          1 1     1            1  1  1        1
B                      1            1          1 1     1            1  1  1        1
CD8 T                  1            1          1 1     1            1  1  1        1
FCGR3A+ Mono           1            1          1 1     1            1  1  1        1
NK                     1            1          1 1     1            1  1  1        1
DC                     1            1          1 1     1            1  1  1        1
Platelet               1            1          1 1     1            1  1  1        1

, , WNT10B_FZD6_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            1            1          1 1     1            1  1  1        1
Memory CD4 T           1            1          1 1     1            1  1  1        1
CD14+ Mono             1            1          1 1     1            1  1  1        1
B                      1            1          1 1     1            1  1  1        1
CD8 T                  1            1          1 1     1            1  1  1        1
FCGR3A+ Mono           1            1          1 1     1            1  1  1        1
NK                     1            1          1 1     1            1  1  1        1
DC                     1            1          1 1     1            1  1  1        1
Platelet               1            1          1 1     1            1  1  1        1

, , WNT16_FZD1_LRP5

             Naive CD4 T Memory CD4 T CD14+ Mono B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            1            1          1 1     1            1  1  1        1
Memory CD4 T           1            1          1 1     1            1  1  1        1
CD14+ Mono             1            1          1 1     1            1  1  1        1

 [ reached getOption("max.print") -- omitted 6 row(s) and 114 matrix slice(s) ]

$count
             Naive CD4 T Memory CD4 T CD14+ Mono  B CD8 T FCGR3A+ Mono NK DC Platelet
Naive CD4 T            4            9         15  5    11           21 12 14        6
Memory CD4 T          13           21         22  9    22           31 21 21       13
CD14+ Mono            12           20         25 12    23           28 26 28       14
B                      3            6         11  4     6           17  9 11        6
CD8 T                  7           13         22  7    15           27 20 19       12
FCGR3A+ Mono          12           25         28 12    22           33 26 30       15
NK                    10           19         24  9    20           26 21 23       12
DC                    13           24         25 13    21           32 22 26       18
Platelet               2            6         10  2    10           11 10 11        9

$sum
              Naive CD4 T Memory CD4 T   CD14+ Mono            B        CD8 T FCGR3A+ Mono           NK           DC     Platelet
Naive CD4 T  5.235731e-04 6.742952e-04 3.909235e-04 7.501420e-04 5.434838e-04 3.885489e-04 1.610436e-04 4.846562e-05 4.413932e-06
Memory CD4 T 1.007867e-03 1.385925e-03 6.727733e-04 1.319087e-03 1.129907e-03 6.201049e-04 4.244407e-04 1.029006e-04 2.323768e-05
CD14+ Mono   2.212146e-04 3.583798e-04 1.213175e-03 5.313253e-04 5.061446e-04 5.027468e-04 2.294104e-04 8.682125e-05 2.022770e-05
B            1.301160e-05 9.973032e-05 1.565374e-04 3.703069e-04 1.646528e-04 2.057724e-04 4.275688e-05 2.459992e-05 3.097154e-06
CD8 T        7.640382e-04 9.283023e-04 4.849123e-04 6.086610e-04 1.986549e-03 1.788599e-04 8.787072e-04 5.912427e-05 9.023021e-05
FCGR3A+ Mono 1.374292e-04 2.766033e-04 4.453398e-04 1.984605e-04 1.309001e-04 2.772841e-04 6.165247e-05 3.351834e-05 9.078602e-07
NK           4.436511e-04 4.983154e-04 3.013077e-04 3.858570e-04 1.078647e-03 9.820542e-05 4.720637e-04 3.638077e-05 4.795777e-05
DC           3.642583e-05 8.053200e-05 1.016134e-04 9.111682e-05 6.074735e-05 6.164358e-05 2.886705e-05 1.000832e-05 1.323708e-06
Platelet     2.580361e-05 3.406017e-05 1.414725e-05 1.492857e-05 9.745813e-05 3.867913e-06 4.425967e-05 2.105407e-06 4.930773e-06


head(cellchat@netP$similarity)
head(cellchat@net$count)
head(cellchat@net$prob)
head(cellchat@net$sum)
head(cellchat@DB)
head(cellchat@var.features)

github 倉(cāng)庫(kù)在：
https://github.com/sqjin/CellChat
https://www.youtube.com/watch?v=kc45au1RhNs
https://www.youtube.com/watch?v=lag9UstpYhk

老師在youtube的講解

最后編輯于：2021.01.15 10:21:03

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