Immunarch包也可以用于處理單細(xì)胞配對鏈數(shù)據(jù)艺演，單細(xì)胞支持目前處于開發(fā)版本却紧。為了訪問它，我們需要通過執(zhí)行以下命令來安裝該軟件包的最新開發(fā)版本：
install.packages ( "devtools" );
devtools :: install_github ( "immunomind/immunarch" , ref = "dev" )
在Immunarch中胎撤，讀取配對鏈免疫組庫數(shù)據(jù)使用
repLoad函數(shù)并指定.mode = "paired"參數(shù)晓殊。目前我們僅支持10X Genomics。
我們可以使用select_barcodes函數(shù)通過特定barcode條形碼對免疫組庫進(jìn)行子集化伤提，也可以使用select_clusters函數(shù)選取創(chuàng)建特定聚類群或特定患者的數(shù)據(jù)集巫俺。
使用Immunarch包內(nèi)置的單細(xì)胞配對鏈數(shù)據(jù)集
# 加載所需的R包
library(immunarch)
# 加載內(nèi)置數(shù)據(jù)集
data(scdata)
# 查看數(shù)據(jù)信息
names(scdata)
# [1] "data" "meta" "bc_patient" "bc_cluster"
head(scdata$meta)
# A tibble: 1 x 1
# Sample
# <chr>
#1 flu
head(scdata$bc_patient)
# GCTGGGTTCAAACCGT-1 CAGTCCTCATGGTAGG-1 GGAAAGCGTCTTCAAG-1 CACAAACGTAAACGCG-1 CATGACATCCTCGCAT-1
# "PatientA" "PatientA" "PatientA" "PatientA" "PatientA"
# ATCCACCCAAGTCTGT-1
# "PatientA"
head(scdata$bc_cluster)
#CAGTCCTTCGCGCCAA-1 TCGTAGATCTTCGGTC-1 CACACAAGTCAATACC-1 CGATGTAGTCGGCTCA-1 CTGTTTATCCTCTAGC-1
# "Activ" "Activ" "Activ" "Activ" "Activ"
# CACACTCCACGACTCG-1
# "Activ"
加載配對鏈數(shù)據(jù)
要加載您自己的數(shù)據(jù)集，請使用該repLoad函數(shù)肿男。目前介汹，我們僅對 10X Genomics 數(shù)據(jù)實施了配對鏈數(shù)據(jù)支持却嗡。將數(shù)據(jù)集加載到 R 的工作示例：
file_path <- paste0(system.file(package = "immunarch"), "/extdata/sc/flu.csv.gz")
igdata <- repLoad(file_path, .mode = "paired")
## == Step 1/3: loading repertoire files... ==
## Processing "<initial>" ...
## -- Parsing "/private/var/folders/5d/g0z_tj9n3qd9r2b4tr8pp5sm0000gp/T/RtmpyOULE7/temp_libpath106e61c9ecf7b/immunarch/extdata/sc/flu.csv.gz" -- 10x (filt.contigs)
## Warning: The following named parsers don't match the column names:
## sample,barcode,is_cell,contig_id,high_confidence,length,chain,v_gene,d_gene,j_gene,c_gene,full_length,productive,cdr3,cdr3_nt,reads,umis,raw_clonotype_id,raw_consensus_id
##
## == Step 2/3: checking metadata files and merging files... ==
##
## Processing "<initial>" ...
## -- Metadata file not found; creating a dummy metadata...
##
## == Step 3/3: processing paired chain data... ==
##
## Done!
查看加載成功后的數(shù)據(jù)信息
igdata$meta
## # A tibble: 1 x 1
## Sample
## <chr>
## 1 flu
head(igdata$data[[1]][c(1:7, 16, 17)])
## Clones Proportion
## 1 3 3e-04
## 2 3 3e-04
## 3 2 2e-04
## 4 2 2e-04
## 5 2 2e-04
## 6 2 2e-04
## CDR3.nt
## 1 TGTGCACACACCACCGAACTCTATTGTACTAATGGTGTATGCTATGGGGGCTACTTTGACTACTGG;TGCCAACAGTATAATAGTTATTCGTGGACGTTC
## 2 TGTGCGAGGCTATGGGGTTGGGGATTACTCTACTGG;TGCACCTCATATGCAGGCAGCAACAATTTGGTATTC
## 3 TGTACCGCTCATGGTAGGGAGGGTACTTTTGATCTCTGG;TGTCAACAATATGATAATCTCCCTCGGTACACTTTT
## 4 TGTGCAAGAGACGACTTTGCTTCGGGGGGTCGACACTTTGGCTGCTGG;TGTCAGCAGTCTGGTAACGCACCTCGAACTTTT
## 5 TGTGCAAGAGATCTGGACTACATGGACGTCTGG;TGTCAACAGAGTTACAGTACCCCTCGAACTTTT
## 6 TGTGCAAGAGGTTTAATACCCTCAGTTAGTGGCTACGACTACTACTACTACTACGGTATGGACGTCTGG;TGTCAATCAGCAGACAGCAGTGGTACTTATGAGGTATTC
## CDR3.aa V.name D.name
## 1 CAHTTELYCTNGVCYGGYFDYW;CQQYNSYSWTF IGHV2-5;IGKV1-5 IGHD2-8;None
## 2 CARLWGWGLLYW;CTSYAGSNNLVF IGHV4-59;IGLV2-11 IGHD3-10;None
## 3 CTAHGREGTFDLW;CQQYDNLPRYTF IGHV3-15;IGKV1-33 IGHD2-15;None
## 4 CARDDFASGGRHFGCW;CQQSGNAPRTF IGHV1-2;IGKV3-20 IGHD3-10;None
## 5 CARDLDYMDVW;CQQSYSTPRTF IGHV3-13;IGKV1D-39 None;None
## 6 CARGLIPSVSGYDYYYYYGMDVW;CQSADSSGTYEVF IGHV3-74;IGLV3-25 IGHD5-12;None
## J.name chain Barcode
## 1 IGHJ4;IGKJ1 IGH;IGK AGTAGTCAGTGTACTC-1;GGCGACTGTACCGAGA-1;TTGAACGGTCACCTAA-1
## 2 IGHJ4;IGLJ2 IGH;IGL AGAGCGACACCTTGTC-1;ATTGGTGAGACCTAGG-1;TCTTCGGAGGTGATTA-1
## 3 IGHJ3;IGKJ2 IGH;IGK CGCGGTATCCTCTAGC-1;TGAGCATCAGGAACGT-1
## 4 IGHJ4;IGKJ2 IGH;IGK ACTGTCCAGACGCAAC-1;CACACTCTCCGTTGTC-1
## 5 IGHJ6;IGKJ2 IGH;IGK AGGTCCGAGTCAAGCG-1;GGCGTGTTCTCTAGGA-1
## 6 IGHJ6;IGLJ2 IGH;IGL ACTGAGTCAAGCGATG-1;CTGCTGTCACGCATCG-1
提取barcode子集
要按barcode條形碼對數(shù)據(jù)進(jìn)行子集化，請使用該select_barcodes函數(shù)嘹承。
barcodes <- c("AGTAGTCAGTGTACTC-1", "GGCGACTGTACCGAGA-1", "TTGAACGGTCACCTAA-1")
new_df <- select_barcodes(scdata$data[[1]], barcodes)
new_df
## CDR3.nt
## 1 TGTGCACACACCACCGAACTCTATTGTACTAATGGTGTATGCTATGGGGGCTACTTTGACTACTGG;TGCCAACAGTATAATAGTTATTCGTGGACGTTC
## CDR3.aa V.name D.name J.name V.end
## 1 CAHTTELYCTNGVCYGGYFDYW;CQQYNSYSWTF IGHV2-5;IGKV1-5 NA IGHJ4;IGKJ1 NA
## D.start D.end J.start VJ.ins VD.ins DJ.ins Sequence chain raw_clonotype_id
## 1 NA NA NA NA NA NA NA IGH;IGK 14
## ContigID Clones Barcode
## 1 NA 3 AGTAGTCAGTGTACTC-1;GGCGACTGTACCGAGA-1;TTGAACGGTCACCTAA-1
## Proportion
## 1 1
提取特定病人的數(shù)據(jù)集
要創(chuàng)建具有特定病人免疫組庫的新數(shù)據(jù)集窗价，請使用以下select_clusters函數(shù)：
scdata_pat <- select_clusters(scdata, scdata$bc_patient, "Patient")
names(scdata_pat$data)
## [1] "flu_PatientA" "flu_PatientB" "flu_PatientC"
scdata_pat$meta
## # A tibble: 3 x 3
## Sample Patient.source Patient
## <chr> <chr> <chr>
## 1 flu_PatientA flu PatientA
## 2 flu_PatientB flu PatientB
## 3 flu_PatientC flu PatientC
提取特定聚類群的數(shù)據(jù)集
要創(chuàng)建具有特定聚類群免疫組庫的新數(shù)據(jù)集，請使用該select_clusters函數(shù)叹卷。您可以在創(chuàng)建特定于患者的數(shù)據(jù)集后應(yīng)用此函數(shù)以獲取特定于患者的細(xì)胞簇特定免疫組庫撼港，例如特定患者的記憶 B 細(xì)胞組庫：
scdata_cl <- select_clusters(scdata_pat, scdata$bc_cluster, "Cluster")
names(scdata_cl$data)
## [1] "flu_PatientA_Activ" "flu_PatientA_Memory" "flu_PatientA_Naive"
## [4] "flu_PatientB_Activ" "flu_PatientB_Memory" "flu_PatientB_Naive"
## [7] "flu_PatientC_Activ" "flu_PatientC_Memory" "flu_PatientC_Naive"
scdata_cl$meta
## # A tibble: 9 x 5
## Sample Patient.source Patient Cluster.source Cluster
## <chr> <chr> <chr> <chr> <chr>
## 1 flu_PatientA_Activ flu PatientA flu_PatientA Activ
## 2 flu_PatientA_Memory flu PatientA flu_PatientA Memory
## 3 flu_PatientA_Naive flu PatientA flu_PatientA Naive
## 4 flu_PatientB_Activ flu PatientB flu_PatientB Activ
## 5 flu_PatientB_Memory flu PatientB flu_PatientB Memory
## 6 flu_PatientB_Naive flu PatientB flu_PatientB Naive
## 7 flu_PatientC_Activ flu PatientC flu_PatientC Activ
## 8 flu_PatientC_Memory flu PatientC flu_PatientC Memory
## 9 flu_PatientC_Naive flu PatientC flu_PatientC Naive
探索和計算統(tǒng)計數(shù)據(jù)
對于單細(xì)胞配對鏈數(shù)據(jù)，immunarch包中的可視化函數(shù)可以同樣的適用骤竹。
p1 <- repOverlap(scdata_cl$data) %>% vis()
p2 <- repDiversity(scdata_cl$data) %>% vis()
target <- c("CARAGYLRGFDYW;CQQYGSSPLTF", "CARATSFYYFHHW;CTSYTTRTTLIF", "CARDLSRGDYFPYFSYHMNVW;CQSDDTANHVIF", "CARGFDTNAFDIW;CTAWDDSLSGVVF", "CTREDYW;CMQTIQLRTF")
p3 <- trackClonotypes(scdata_cl$data, target, .col = "aa") %>% vis()
## Warning in melt.data.table(.data): id.vars and measure.vars are internally
## guessed when both are 'NULL'. All non-numeric/integer/logical type columns are
## considered id.vars, which in this case are columns [CDR3.aa]. Consider providing
## at least one of 'id' or 'measure' vars in future.
(p1 + p2) / p3
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