空间转录组与单细胞转录组联合分析——MIA，代码分享（Nature Biotechnology :）

原文：Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas | Nature Biotechnology

研究者采用 MIA 联合 scRNAseq 和 ST 数据，分析原发性胰腺导管腺癌（PDAC）的组织结构。大家好，

MIA 首先使用以下步骤来描述细胞类型特异性基因集和组织区域特异性基因集：

在 scRNAseq 数据中，识别每个细胞类型中比其余的细胞都高表达的基因，定义细胞类型基因集。
基于 ST 数据，确定各个空间区域相对于其他区域有显著高表达的基因集（空间区域基因集）。
然后，MIA 计算每一对细胞类型基因集的特异性和区域特异性，并采用超几何分布来评估显著的富集或耗竭。

可以看到MIA需要我们提供单细胞marker基因集和空间marker基因基因集合（最好是同一套样本同时做了空转和单细胞，如果不是同一套，可能对生物学解释有些影响，但是不影响生信分析流程）

完整代码，放在文末，这里分别说下所需要的单细胞和空转输入数据

空转数据输入格式

> ####st-----> cluster_gene_stat=FindAllMarkers(d.all,only.pos = TRUE,logfc.threshold = 0.9)Calculating cluster cluster2  |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  Calculating cluster cluster4  |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=01s  Calculating cluster cluster1  |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  Calculating cluster cluster3  |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=03s  Calculating cluster cluster5  |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  Calculating cluster cluster0  |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  Calculating cluster cluster7Calculating cluster cluster6  |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=02s  Calculating cluster cluster8  |++++++++++++++++++++++++++++++++++++++++++++++++++| 100% elapsed=00s  > head(cluster_gene_stat)               p_val avg_log2FC pct.1 pct.2     p_val_adj  cluster   geneMarco  1.168778e-259  1.9388057 0.874 0.298 2.268598e-255 cluster2  MarcoWfdc21 1.246929e-191  1.5790076 0.836 0.361 2.420289e-187 cluster2 Wfdc21Chil3  2.075188e-149  1.7852619 0.995 0.946 4.027939e-145 cluster2  Chil3Plet1  2.197103e-129  1.2324047 0.870 0.518 4.264576e-125 cluster2  Plet1Ccl6   8.553776e-111  1.2698564 1.000 0.949 1.660288e-106 cluster2   Ccl6Ly6i   9.178082e-100  0.9324478 0.972 0.550  1.781466e-95 cluster2   Ly6i> table(cluster_gene_stat$cluster)cluster2 cluster4 cluster1 cluster3 cluster5 cluster0 cluster7 cluster6 cluster8        7      142       31      247        7       10        0      120        7 > # Initialize a dataframe for us to store values in:> st.clusts=paste0("cluster",seq(0,8,1))> head(cluster_gene_stat)               p_val avg_log2FC pct.1 pct.2     p_val_adj  cluster   geneMarco  1.168778e-259  1.9388057 0.874 0.298 2.268598e-255 cluster2  MarcoWfdc21 1.246929e-191  1.5790076 0.836 0.361 2.420289e-187 cluster2 Wfdc21Chil3  2.075188e-149  1.7852619 0.995 0.946 4.027939e-145 cluster2  Chil3Plet1  2.197103e-129  1.2324047 0.870 0.518 4.264576e-125 cluster2  Plet1Ccl6   8.553776e-111  1.2698564 1.000 0.949 1.660288e-106 cluster2   Ccl6Ly6i   9.178082e-100  0.9324478 0.972 0.550  1.781466e-95 cluster2   Ly6i> st.marker.list=split(cluster_gene_stat,f = cluster_gene_stat$cluster)> st.marker.list = lapply(st.marker.list,rownames)> head(st.marker.list)$cluster2[1] "Marco"  "Wfdc21" "Chil3"  "Plet1"  "Ccl6"   "Ly6i"   "Ctsk"  $cluster4  [1] "Cdhr4"         "Rsph1"         "Gabrp"         "Ccdc153"       "Dnah5"         "Foxj1"         "1110017D15Rik" "Lrrc23"         [9] "Cfap43"        "Cdhr3"         "Dnali1"        "Pifo"          "Scgb1a1"       "Ak7"           "Tmem212"       "Gm19935"       [17] "Cyp2f2"        "Dnah6"         "Cfap65"        "1700007K13Rik" "Fam183b"       "Cyp2s1"        "Cfap206"       "Nme9"          [25] "1700016K19Rik" "Mgst1"         "BC051019"      "AU040972"      "Wfdc2"         "Meig1"         "Fmo3"          "Cfap126"       [33] "Mapk15"        "Tctex1d4"      "Acta2"         "Cckar"         "Drc3"          "Scgb3a2"       "Rbp4"          "Dynlrb2"       [41] "Cldn10"        "B430010I23Rik" "Riiad1"        "3300002A11Rik" "Nme5"          "Ldhb"          "1700024G13Rik" "Hp"            [49] "Cbr2"          "Tspan1"        "Anxa8"         "Odf3b"         "Cnn1"          "Ccdc17"        "Mlf1"          "Dcn"           [57] "Mgat3"         "Cxcl17"        "Slc16a11"      "Gpx2"          "Chad"          "Clic6"         "5330417C22Rik" "Gsta4"         [65] "Retnla"        "Myh11"         "Calml4"        "Cd55"          "Cygb"          "1700094D03Rik" "Cd24a"         "Alas1"         [73] "Actg2"         "Mmp2"          "Lypd2"         "Aldh1a7"       "Myl9"          "Tpm2"          "1700088E04Rik" "Tubb4b"        [81] "Lrrc51"        "Elof1"         "C4b"           "Vpreb3"        "Igfbp5"        "Ccl21a"        "Arhgdig"       "Pon1"          [89] "Igfbp4"        "Csrp2"         "Map1b"         "Chchd10"       "Endog"         "Col14a1"       "Tagln"         "Por"           [97] "Nupr1"         "Dcxr"          "Cyp2a5"        "Pcp4l1"        "Mustn1"        "Net1"          "Traf3ip1"      "Fbln1"        [105] "Aebp1"         "Selenbp1"      "Enah"          "Adamts2"       "Des"           "Pi16"          "Gsto1"         "Ltf"          [113] "Muc5b"         "Actc1"         "Aox3"          "Ces1d"         "Tmem107"       "Bphl"          "Serpinf1"      "C3"           [121] "Tst"           "Tff2"          "Pigr"          "Aldh1a1"       "Scgb1c1"       "Cpe"           "Aldh3b1"       "Tppp3"        [129] "Gstm1"         "Clec3b"        "Scgb3a1"       "Gsta3"         "Bpifa1"        "Bpifb1"        "Igha"          "Reg3g"        [137] "Igfbp6"        "Gsn"           "Jchain"        "Igkc"          "Iglc1"         "Cfd"          $cluster1 [1] "Lcn2"    "Saa3"    "Lrg1"    "Ccl2"    "Sftpd"   "Chil1"   "Slc26a4" "Ctsc"    "Itih4"   "Slpi"    "Il33"    "Fabp5"   "Hc"     [14] "Ly6i1"   "Cd74"    "Clu"     "Fasn"    "Muc1"    "Spp1"    "Igha1"   "Igkc1"   "Ccl7"    "Ctss"    "Wfdc17"  "Jchain1" "Ptgs1"  [27] "Npc2"    "Tgfbi"   "Ighg2c"  "Ighg2b"  "Ighg1"  $cluster3  [1] "Mmp12"    "Clec4n"   "Gpnmb"    "Lgals3"   "Lilr4b"   "Prdx1"    "Lilrb4a"  "Ccl9"     "Psap"     "Clec4d"   "Clec4e"   [12] "Itgb2"    "Il1rn"    "Ftl1"     "Lhfpl2"   "Ltbp2"    "Fth1"     "Ctsb"     "Cstb"     "S100a4"   "Pla2g7"   "Ctss1"    [23] "Spp11"    "Ctsd"     "Capg"     "Atp6v0c"  "Cd68"     "Ctsz"     "Cyba"     "Tyrobp"   "Cd63"     "Litaf"    "Tcirg1"   [34] "Bcl2a1b"  "Cybb"     "Esd"      "AA467197" "Slc7a11"  "Fn1"      "Hvcn1"    "Fcer1g"   "Lpl"      "Cd52"     "Ftl1-ps1" [45] "Lipa"     "Csf2rb"   "Fabp51"   "Fcgr2b"   "Saa31"    "Pld3"     "Fam20c"   "Mpeg1"    "Trem2"    "Col3a1"   "Ccl61"    [56] "Pgam1"    "Tmsb10"   "Acod1"    "Adam8"    "Sirpa"    "Plin2"    "Pkm"      "Col5a2"   "Itgax"    "F10"      "Creg1"    [67] "Slc11a1"  "Arpc1b"   "Sh3bgrl3" "Igf1"     "Grn"      "Eif4a1"   "Slc15a3"  "Ccl3"     "Col1a1"   "Rnf128"   "Lyz2"     [78] "Col1a2"   "Serpine2" "Txn1"     "Wfdc171"  "H2-D1"    "Mmp19"    "Lgmn"     "Eln"      "Sfrp1"    "Ctsa"     "Rnh1"     [89] "Tnfrsf1b" "Tnfaip2"  "Fxyd5"    "Rgs1"     "Pgd"      "Cd53"     "Timp1"    "Ifi30"    "F7"       "Ccl21"    "Ncf2"    [100] "Ninj1"    "Fcgr3"    "Lgals1"   "Vmp1"     "Lcp1"     "Msr1"     "Anxa1"    "Gapdh"    "Gpx1"     "Csf2ra"   "Col5a1"  [111] "Atox1"    "Anpep"    "Prkcd"    "Atp6v1e1" "Col4a1"   "Sulf1"    "Ctsl"     "Hexa"     "Atp6v0d2" "Cd44"     "Rilpl2"  [122] "Gusb"     "Sgk1"     "Plaur"    "Cd741"    "Igfbp7"   "Bhlhe40"  "Csf2rb2"  "Mdk"      "Atp6v0b"  "Cotl1"    "Ptafr"   [133] "Msrb1"    "Mgp"      "Fbn1"     "Spi1"     "Ppic"     "Lat2"     "Plek"     "B4galt5"  "Gpr137b"  "Laptm5"   "Mfap5"   [144] "Itgam"    "Cxcl2"    "Ncf1"     "Cd9"      "Tlr2"     "Txnrd1"   "Acp5"     "Tnc"      "Mmp21"    "Fndc1"    "Junb"    [155] "Psmd8"    "Marcksl1" "Atp6v1b2" "Cd300c2"  "Tuba1c"   "Emp3"     "Cd84"     "Fstl1"    "Pirb"     "Slfn2"    "Card19"  [166] "Slpi1"    "Basp1"    "Aprt"     "Bst2"     "Hmox1"    "Prelid1"  "Bst1"     "Mfsd12"   "Cxcl12"   "Myo1f"    "Sgpl1"   [177] "Rhoc"     "Col4a2"   "Apoe"     "Glipr1"   "Sh3pxd2b" "Sbno2"    "Mif"      "Myo5a"    "Plxnd1"   "Clic1"    "Socs3"   [188] "Alox5ap"  "Ctsk1"    "Lgals3bp" "Ncf4"     "Blvrb"    "Thbs2"    "Cyth4"    "Fmod"     "Cpxm1"    "Srxn1"    "Ms4a6d"  [199] "Pycard"   "Tgfbi1"   "Prdx5"    "Cd14"     "Cxcl10"   "Ctsh"     "Col18a1"  "Ccl71"    "Clu1"     "Cndp2"    "Atp6v1c1"[210] "Eno1"     "Pmepa1"   "Colgalt1" "Cilp"     "Bmp1"     "Unc93b1"  "Col6a3"   "Mt1"      "Sema4d"   "Isg15"    "C1qtnf6" [221] "Aebp11"   "Ccdc80"   "Il1b"     "Npc21"    "Grem1"    "Iigp1"    "Ccl4"     "Nrep"     "S100a8"   "C1qb"     "Man2b1"  [232] "Abca1"    "Igha2"    "Irf7"     "Cxcl9"    "Igkc2"    "Jchain2"  "Slfn4"    "C1qa"     "C1qc"     "Ifit3"    "Rsad2"   [243] "S100a9"   "Ighg2b1"  "Ifit1"    "Ighg2c1"  "Ighg11"  $cluster5[1] "Scgb3a21" "Cyp2f21"  "Inmt"     "Hbb-bs"   "Hba-a2"   "Hba-a1"   "Hbb-bt"  $cluster0 [1] "Inmt1"   "Hba-a11" "Hbb-bs1" "Hbb-bt1" "Hba-a21" "Fmo2"    "Pcolce2" "Cyp4b1"  "Tspan7"  "Hpgd"

###########################

最终得到空转中的数据，整理出下面两个对象

st.clusts，是一个向量

st.marker.list，是一个列表，元素就是每个区域的marker基因，列表的names就构成了st.lusts

st.clusts[1] "cluster0" "cluster1" "cluster2" "cluster3" "cluster4" "cluster5" "cluster6" "cluster7" "cluster8"> st.marker.list$cluster2[1] "Marco"  "Wfdc21" "Chil3"  "Plet1"  "Ccl6"   "Ly6i"   "Ctsk"  $cluster4  [1] "Cdhr4"         "Rsph1"         "Gabrp"         "Ccdc153"       "Dnah5"         "Foxj1"         "1110017D15Rik" "Lrrc23"         [9] "Cfap43"        "Cdhr3"         "Dnali1"        "Pifo"          "Scgb1a1"       "Ak7"           "Tmem212"       "Gm19935"       [17] "Cyp2f2"        "Dnah6"         "Cfap65"        "1700007K13Rik" "Fam183b"       "Cyp2s1"        "Cfap206"       "Nme9"          [25] "1700016K19Rik" "Mgst1"         "BC051019"      "AU040972"      "Wfdc2"         "Meig1"         "Fmo3"          "Cfap126"       [33] "Mapk15"        "Tctex1d4"      "Acta2"         "Cckar"         "Drc3"          "Scgb3a2"       "Rbp4"          "Dynlrb2"       [41] "Cldn10"        "B430010I23Rik" "Riiad1"        "3300002A11Rik" "Nme5"          "Ldhb"          "1700024G13Rik" "Hp"            [49] "Cbr2"          "Tspan1"        "Anxa8"         "Odf3b"         "Cnn1"          "Ccdc17"        "Mlf1"          "Dcn"           [57] "Mgat3"         "Cxcl17"        "Slc16a11"      "Gpx2"          "Chad"          "Clic6"         "5330417C22Rik" "Gsta4"         [65] "Retnla"        "Myh11"         "Calml4"        "Cd55"          "Cygb"          "1700094D03Rik" "Cd24a"         "Alas1"         [73] "Actg2"         "Mmp2"          "Lypd2"         "Aldh1a7"       "Myl9"          "Tpm2"          "1700088E04Rik" "Tubb4b"        [81] "Lrrc51"        "Elof1"         "C4b"           "Vpreb3"        "Igfbp5"        "Ccl21a"        "Arhgdig"       "Pon1"          [89] "Igfbp4"        "Csrp2"         "Map1b"         "Chchd10"       "Endog"         "Col14a1"       "Tagln"         "Por"           [97] "Nupr1"         "Dcxr"          "Cyp2a5"        "Pcp4l1"        "Mustn1"        "Net1"          "Traf3ip1"      "Fbln1"        [105] "Aebp1"         "Selenbp1"      "Enah"          "Adamts2"       "Des"           "Pi16"          "Gsto1"         "Ltf"          [113] "Muc5b"         "Actc1"         "Aox3"          "Ces1d"         "Tmem107"       "Bphl"          "Serpinf1"      "C3"           [121] "Tst"           "Tff2"          "Pigr"          "Aldh1a1"       "Scgb1c1"       "Cpe"           "Aldh3b1"       "Tppp3"        [129] "Gstm1"         "Clec3b"        "Scgb3a1"       "Gsta3"         "Bpifa1"        "Bpifb1"        "Igha"          "Reg3g"        [137] "Igfbp6"        "Gsn"           "Jchain"        "Igkc"          "Iglc1"         "Cfd"          $cluster1 [1] "Lcn2"    "Saa3"    "Lrg1"    "Ccl2"    "Sftpd"   "Chil1"   "Slc26a4" "Ctsc"    "Itih4"   "Slpi"    "Il33"    "Fabp5"   "Hc"     [14] "Ly6i1"   "Cd74"    "Clu"     "Fasn"    "Muc1"    "Spp1"    "Igha1"   "Igkc1"   "Ccl7"    "Ctss"    "Wfdc17"  "Jchain1" "Ptgs1"  [27] "Npc2"    "Tgfbi"   "Ighg2c"  "Ighg2b"  "Ighg1"  $cluster3  [1] "Mmp12"    "Clec4n"   "Gpnmb"    "Lgals3"   "Lilr4b"   "Prdx1"    "Lilrb4a"  "Ccl9"     "Psap"     "Clec4d"   "Clec4e"   [12] "Itgb2"    "Il1rn"    "Ftl1"     "Lhfpl2"   "Ltbp2"    "Fth1"     "Ctsb"     "Cstb"     "S100a4"   "Pla2g7"   "Ctss1"    [23] "Spp11"    "Ctsd"     "Capg"     "Atp6v0c"  "Cd68"     "Ctsz"     "Cyba"     "Tyrobp"   "Cd63"     "Litaf"    "Tcirg1"   [34] "Bcl2a1b"  "Cybb"     "Esd"      "AA467197" "Slc7a11"  "Fn1"      "Hvcn1"    "Fcer1g"   "Lpl"      "Cd52"     "Ftl1-ps1" [45] "Lipa"     "Csf2rb"   "Fabp51"   "Fcgr2b"   "Saa31"    "Pld3"     "Fam20c"   "Mpeg1"    "Trem2"    "Col3a1"   "Ccl61"    [56] "Pgam1"    "Tmsb10"   "Acod1"    "Adam8"    "Sirpa"    "Plin2"    "Pkm"      "Col5a2"   "Itgax"    "F10"      "Creg1"    [67] "Slc11a1"  "Arpc1b"   "Sh3bgrl3" "Igf1"     "Grn"      "Eif4a1"   "Slc15a3"  "Ccl3"     "Col1a1"   "Rnf128"   "Lyz2"     [78] "Col1a2"   "Serpine2" "Txn1"     "Wfdc171"  "H2-D1"    "Mmp19"    "Lgmn"     "Eln"      "Sfrp1"    "Ctsa"     "Rnh1"     [89] "Tnfrsf1b" "Tnfaip2"  "Fxyd5"    "Rgs1"     "Pgd"      "Cd53"     "Timp1"    "Ifi30"    "F7"       "Ccl21"    "Ncf2"    [100] "Ninj1"    "Fcgr3"    "Lgals1"   "Vmp1"     "Lcp1"     "Msr1"     "Anxa1"    "Gapdh"    "Gpx1"     "Csf2ra"   "Col5a1"  [111] "Atox1"    "Anpep"    "Prkcd"    "Atp6v1e1" "Col4a1"   "Sulf1"    "Ctsl"     "Hexa"     "Atp6v0d2" "Cd44"     "Rilpl2"  [122] "Gusb"     "Sgk1"     "Plaur"    "Cd741"    "Igfbp7"   "Bhlhe40"  "Csf2rb2"  "Mdk"      "Atp6v0b"  "Cotl1"    "Ptafr"   [133] "Msrb1"    "Mgp"      "Fbn1"     "Spi1"     "Ppic"     "Lat2"     "Plek"     "B4galt5"  "Gpr137b"  "Laptm5"   "Mfap5"   [144] "Itgam"    "Cxcl2"    "Ncf1"     "Cd9"      "Tlr2"     "Txnrd1"   "Acp5"     "Tnc"      "Mmp21"    "Fndc1"    "Junb"    [155] "Psmd8"    "Marcksl1" "Atp6v1b2" "Cd300c2"  "Tuba1c"   "Emp3"     "Cd84"     "Fstl1"    "Pirb"     "Slfn2"    "Card19"  [166] "Slpi1"    "Basp1"    "Aprt"     "Bst2"     "Hmox1"    "Prelid1"  "Bst1"     "Mfsd12"   "Cxcl12"   "Myo1f"    "Sgpl1"   [177] "Rhoc"     "Col4a2"   "Apoe"     "Glipr1"   "Sh3pxd2b" "Sbno2"    "Mif"      "Myo5a"    "Plxnd1"   "Clic1"    "Socs3"   [188] "Alox5ap"  "Ctsk1"    "Lgals3bp" "Ncf4"     "Blvrb"    "Thbs2"    "Cyth4"    "Fmod"     "Cpxm1"    "Srxn1"    "Ms4a6d"  [199] "Pycard"   "Tgfbi1"   "Prdx5"    "Cd14"     "Cxcl10"   "Ctsh"     "Col18a1"  "Ccl71"    "Clu1"     "Cndp2"    "Atp6v1c1"[210] "Eno1"     "Pmepa1"   "Colgalt1" "Cilp"     "Bmp1"     "Unc93b1"  "Col6a3"   "Mt1"      "Sema4d"   "Isg15"    "C1qtnf6" [221] "Aebp11"   "Ccdc80"   "Il1b"     "Npc21"    "Grem1"    "Iigp1"    "Ccl4"     "Nrep"     "S100a8"   "C1qb"     "Man2b1"  [232] "Abca1"    "Igha2"    "Irf7"     "Cxcl9"    "Igkc2"    "Jchain2"  "Slfn4"    "C1qa"     "C1qc"     "Ifit3"    "Rsad2"   [243] "S100a9"   "Ighg2b1"  "Ifit1"    "Ighg2c1"  "Ighg11"  $cluster5[1] "Scgb3a21" "Cyp2f21"  "Inmt"     "Hbb-bs"   "Hba-a2"   "Hba-a1"   "Hbb-bt"  $cluster0 [1] "Inmt1"   "Hba-a11" "Hbb-bs1" "Hbb-bt1" "Hba-a21" "Fmo2"    "Pcolce2" "Cyp4b1"  "Tspan7"  "Hpgd"   $cluster7character(0)$cluster6  [1] "Kcnj3"    "Myl1"     "Mybphl"   "Tmem182"  "Trdn"     "Art1"     "Myom2"    "Hamp"     "Tbx20"    "Hrc"      "Fndc5"    [12] "Eef1a2"   "Casq2"    "Sbk3"     "Gm15543"  "Ank1"     "Pgam2"    "Ryr2"     "Smpx"     "Txlnb"    "Srl"      "Myoz2"    [23] "Obscn"    "Ldb3"     "Sln"      "Ttn"      "Smyd1"    "Csrp3"    "Ckmt2"    "Actn2"    "Ckm"      "Cox8b"    "Hspb7"    [34] "Myl7"     "Tcap"     "Myl4"     "Tnnc1"    "Tnni3"    "Cmya5"    "Pln"      "Mb"       "Tnnt2"    "Myh6"     "Cox7a1"   [45] "Cox6a2"   "Fabp3"    "Actc11"   "Atp2a2"   "Ankrd1"   "Tnnt1"    "Myl3"     "Slc2a4"   "Mybpc3"   "Aldh1b1"  "Scara5"   [56] "Nppa"     "Fhl2"     "Coq8a"    "Popdc2"   "Cpe1"     "Myom1"    "mt-Co3"   "Dcn1"     "Tpm1"     "mt-Co2"   "Pi161"    [67] "Eno3"     "Pam"      "Slc25a4"  "Pde4dip"  "mt-Co1"   "mt-Nd1"   "Asb2"     "mt-Nd3"   "Car3"     "mt-Nd4"   "mt-Cytb"  [78] "Got1"     "Pygm"     "Pfkm"     "Ndrg2"    "Cfd1"     "mt-Nd2"   "Igfbp51"  "Hspb6"    "mt-Atp6"  "Cfh"      "Fxyd6"    [89] "Fbln11"   "Tmem38a"  "Clec3b1"  "Gsn1"     "Hadhb"    "Art3"     "Htra3"    "Mdh1"     "Atp5b"    "Atp5g1"   "Lum"     [100] "Aco2"     "Pdlim5"   "Col14a11" "Dsp"      "Mdh2"     "Acsl1"    "Cryab"    "mt-Nd5"   "Fxyd1"    "Idh3a"    "Pdha1"   [111] "Prss23"   "Uqcrfs1"  "Cycs"     "Got2"     "Acadm"    "Mmrn1"    "F13a1"    "Fabp4"    "Ccl8"     "Ccl21a1" $cluster8[1] "Myl71"  "Sln1"   "Myl41"  "Myh61"  "Tnnt21" "Tnni31" "Tcap1"

单细胞数据输入格式

单细胞中，整理出下面两个对象

sc.clusts，单细胞的每个细胞类型名称，是个向量

cellType_marker，单细胞的marker基因，列表形式，其names就是sc.clusts

> sc.clusts [1] "Inmt fibroblast"      "Hhip fibroblast"      "Universal fibroblast" "Grem1 fibroblast"     "Myofibroblast"        [6] "Monocyte"             "AM3"                  "AM2"                  "NK cell"              "AM1"                 [11] "Dendritic cell"       "Endothelial cell-2"   "Cycling basal cell"   "B cell"               "Neutrophil"          [16] "T cell"               "IM"                   "AT2 cell-2"           "Igha+ AT2  cell"      "Endothelial cell-1"  [21] "AT1 cell"             "Clara cell"           "Ciliated cell"        "AT2 cell-1"           "Ig-producing B cell" > cellType_marker$`Inmt fibroblast`  [1] "Inmt"      "Gpx3"      "Sod3"      "Fmo2"      "Serping1"  "Bgn"       "Mfap4"     "Pcolce2"   "Sparcl1"   "Npnt"      [11] "Ccn1"      "Limch1"    "Fhl1"      "Ogn"       "Ltbp4"     "Clec3b"    "Rbp1"      "Timp3"     "Col1a2"    "Mxra8"     [21] "Mettl7a1"  "Prelp"     "Cxcl14"    "Plpp3"     "Ptgis"     "Plxdc2"    "Cfh"       "Col1a1"    "Col3a1"    "Aldh1a1"   [31] "Tcf21"     "C7"        "Ppp1r14a"  "Rarres2"   "Pdgfra"    "Olfml3"    "Fxyd1"     "Nbl1"      "Cdo1"      "Adh1"      [41] "Mylk"      "Pcolce"    "Sept4"     "Selenbp1"  "Serpinh1"  "Serpine2"  "Spon1"     "Col6a1"    "Hspb1"     "Gpc3"      [51] "Dpt"       "Nfib"      "Cald1"     "Colec12"   "Loxl1"     "Col6a2"    "Cp"        "Itga8"     "C1s1"      "Serpina3n" [61] "Atp1a2"    "Crispld2"  "Dpep1"     "Efemp1"    "Gpm6b"     "Prex2"     "Nr2f2"     "Ces1d"     "Myh10"     "Rcn3"      [71] "Gas6"      "Fbln1"     "Mamdc2"    "Gsta3"     "Mfap5"     "Fkbp9"     "Mmp2"      "Vcam1"     "Col6a3"    "Ms4a4d"    [81] "Abca8a"    "Tnxb"      "C1ra"      "Cryab"     "Slc38a5"   "Nebl"      "Scarf2"    "Vegfd"     "Nox4"      "F2r"       [91] "Sdc2"      "Col13a1"   "Gstt1"     "Palld"     "Ccn5"      "Cpq"       "Tmem204"   "Cdh11"     "Myo1b"     "Ppic"     [101] "Sparc"     "Dbp"       "Gstm2"     "Rnase4"    "Gng11"     "Selenom"   "C4b"       "Mgp"       "Igfbp7"    "Hsd11b1"  [111] "Fermt2"    "Csrp1"     "Slc43a3"   "Nedd4"     "Mfge8"     "Tns1"      "Cd81"      "Tmem176a"  "Nupr1"     "Id3"      [121] "Tmem176b"  "Pmp22"     "Lbh"       "Tpm1"      "Igfbp6"    "Gsn"       "Ecm1"      "Klf9"      "Zbtb20"    "Oat"      [131] "Gyg"       "Dpysl2"    "Timp2"     "Cebpd"     "Macf1"     "Apoe"      "Nenf"      "Sptbn1"    "Tuba1a"    "C3"       [141] "Egr1"      "Aldh2"     "Gstm1"     "Ctsl"      "Jun"      $`Hhip fibroblast` [1] "Hhip"          "Enpp2"         "Aspn"          "Igfbp3"        "Cyp2e1"        "Pcsk5"         "Cdh4"          "Sgcg"          [9] "Mustn1"        "Grem2"         "6330403K07Rik" "Lum"           "Sod3"          "Rarres2"       "Ltbp3"         "Igfbp5"       [17] "Ltbp4"         "Prelp"         "Tnxb"          "Tagln"         "Ddr2"          "Des"           "Fxyd1"         "Gm13889"      [25] "Serpine2"      "Ogn"           "Dpt"           "Auts2"         "Tpm2"          "Lama4"         "Bgn"           "Ptgis"        [33] "Atp1a2"        "Fmo2"          "Sdc2"          "Tgfbr3"        "Col1a1"        "Col6a3"        "Col1a2"        "Mdk"          [41] "Serping1"      "Col3a1"        "Palld"         "Nfib"          "Olfml2b"       "Myl9"          "Mfap5"         "Sparcl1"      [49] "Timp3"         "Igfbp7"        "Crispld2"      "Fstl1"         "Rcn3"          "Pam"           "Prnp"          "Mylk"         [57] "Gpx3"          "Acta2"         "Serpinh1"      "Cavin3"        "Mgp"           "Sparc"         "Cd81"          "P2ry14"       [65] "Dcn"           "Tmem176b"      "Hmcn1"         "Igf1"          "Selenom"       "Adamts10"      "Cald1"         "Zbtb20"       [73] "Nedd4"         "Csrp1"         "Nfia"          "Klf9"          "Gsn"           "Crip2"         "Tmem176a"      "Nfix"         [81] "Tpm1"          "Sdc4"          "Nenf"          "Ctsl"          "Nupr1"         "Lpp"           "Dst"           "Gstm1"        [89] "Id3"           "Laptm4a"       "Apoe"          "Thbs1"         "Cebpd"        $`Universal fibroblast`  [1] "Dcn"       "Clec3b"    "Mgp"       "Serping1"  "Inmt"      "Col1a2"    "Igfbp7"    "Timp3"     "Sparc"     "Igfbp4"    [11] "Col3a1"    "Pcolce2"   "Col1a1"    "Bgn"       "Igfbp6"    "Aebp1"     "Dpt"       "Fbln1"     "Ltbp4"     "Mfap5"     [21] "Cfh"       "Cygb"      "Plpp3"     "Rarres2"   "Serpinf1"  "Gpc3"      "Sparcl1"   "Rbp1"      "Nbl1"      "Sod3"      [31] "C1s1"      "Pcolce"    "Ccn1"      "Ogn"       "Selenom"   "Dpep1"     "Fmo2"      "Serpinh1"  "Adh1"      "Fxyd1"     [41] "C1ra"      "Fstl1"     "Cd34"      "Gpx3"      "Rnase4"    "Rcn3"      "Nfib"      "Plxdc2"    "Mmp2"      "Rbp4"      [51] "Abi3bp"    "C4b"       "Abca8a"    "Col6a2"    "Ptgis"     "Tnxb"      "Akap12"    "Mfap4"     "Fhl1"      "Col14a1"   [61] "Col6a1"    "Gas6"      "Slc43a3"   "Adamts2"   "C7"        "Loxl1"     "Cavin3"    "Gas1"      "Ddr2"      "Efemp1"    [71] "Mxra8"     "Bicc1"     "Ccl11"     "Htra3"     "Gstm2"     "Fbn1"      "Entpd2"    "Pdgfra"    "Mmp23"     "Cxcl12"    [81] "Meg3"      "Cpq"       "Tcf21"     "Prelp"     "Timp1"     "Lhfp"      "Rbms3"     "Scara5"    "Cald1"     "Ccdc80"    [91] "Csrp2"     "Pam"       "Crtap"     "Pmp22"     "Nedd4"     "Ecm1"      "Id3"       "Cd81"      "Nenf"      "Timp2"    [101] "Pi16"      "Nfix"      "Vkorc1"    "Il11ra1"   "Nupr1"     "C3"        "Gsn"       "Pdlim2"    "Zbtb20"    "Cd302"    [111] "Cebpd"     "Serpinb6a" "Tuba1a"    "Klf9"      "Ctsl"      "Mt2"       "Ly6c1"     "Ly6a"      "Sptbn1"    "Gstm1"    [121] "Selenop"   "Jun"       "Laptm4a"   "Egr1"      "Apoe"      "Mt1"      $`Grem1 fibroblast` [1] "Col6a3"   "Mmp2"     "Col6a2"   "Grem1"    "Fbn1"     "Col5a1"   "Tnc"      "Nrep"     "Col6a1"   "Pcolce"   "Col5a2"  [12] "Col1a1"   "Serpine2" "Col1a2"   "Timp1"    "Aebp1"    "Bgn"      "Col3a1"   "Fgfr1"    "Serpinh1" "Rbp1"     "Adh1"    [23] "Nbl1"     "Cald1"    "Gpx3"     "Sod3"     "Mfap4"    "Olfml3"   "Cp"       "Mxra8"    "Serping1" "Dcn"      "Hmcn1"   [34] "Colec12"  "Mylk"     "Sparcl1"  "Sparc"    "Rarres2"  "Mfap5"    "Rcn3"     "Nfib"     "Col4a1"   "Fermt2"   "Ltbp4"   [45] "Ppic"     "Igfbp7"   "Ccn1"     "Fmo2"     "Tpm1"     "Fstl1"    "Timp3"    "Gng11"    "Nedd4"    "Mgp"      "Saa3"    [56] "Mmp14"    "Pmepa1"   "Cfh"      "Igfbp4"   "Nupr1"    "Plpp3"    "Tmem176b" "Pbx1"     "Tmem176a" "Tcf4"     "Inmt"    [67] "Zbtb20"   "Id3"      "Fn1"      "Gsn"     $Myofibroblast  [1] "Tagln"    "Myl9"     "Tpm2"     "Myh11"    "Cald1"    "Mustn1"   "Sod3"     "Ppp1r14a" "Mylk"     "Actc1"    "Des"      [12] "Cnn1"     "Fxyd1"    "Ltbp4"    "Cpe"      "Map1b"    "Lmod1"    "Itih4"    "Eln"      "Serpine2" "Gucy1a1"  "Actg2"    [23] "Itga8"    "Prss23"   "Gucy1b1"  "Postn"    "Smtn"     "Ndrg2"    "Col18a1"  "Synpo2"   "Cdh13"    "Hspg2"    "Lamb2"    [34] "Notch3"   "Pdgfrb"   "Ccn2"     "Cox4i2"   "Npnt"     "Lmcd1"    "Ccl19"    "Sh3bgr"   "Bgn"      "Lhfp"     "Rarres2"  [45] "Tnxb"     "Hspb6"    "Sparcl1"  "Col6a2"   "Nr2f2"    "Gm13889"  "Snhg18"   "Pde5a"    "Aebp1"    "Fhl1"     "Cryab"    [56] "Acta2"    "Tinagl1"  "Col1a2"   "Mxra8"    "Tgfb1i1"  "Cavin3"   "Col3a1"   "Col6a1"   "Timp3"    "Igfbp5"   "Fstl1"    [67] "Ogn"      "Serpinh1" "Selenom"  "Tm4sf1"   "Fermt2"   "Col1a1"   "Rcn3"     "Pls3"     "Sparc"    "Fblim1"   "Tpm1"     [78] "Igfbp7"   "Rbp1"     "Mfge8"    "Hspb1"    "Nedd4"    "Clu"      "Cavin1"   "Pam"      "Ecm1"     "Cnn3"     "Bcam"     [89] "Nfia"     "Itga1"    "Csrp2"    "Col4a1"   "Ppp1r12b" "Ccn1"     "Tns1"     "Ckb"      "Crip2"    "Csrp1"    "Thra"    [100] "Cd81"     "Mgp"      "Klf9"     "Mcam"     "Gpx3"     "Rbpms"    "Id3"      "Lpp"      "Tsc22d1"  "Filip1l"  "Dst"     [111] "Nenf"     "Zbtb20"   "Gsn"      "Epas1"    "Dstn"     "Slc25a4"  "Selenow"  "Actn1"    "Itgb1"    "Gstm1"    "Flna"    $Monocyte [1] "Plac8"  "Ms4a6c" "Ifitm3" "S100a4" "Csf1r"  "Pld4"   "Cybb"   "Ifitm6" "Pou2f2" "Napsa"  "Apoe"   "Ccr2"   "Ace"   $AM3 [1] "Gpnmb"    "Spp1"     "Ccl2"     "Fabp5"    "Inhba"    "Esd"      "Cd63"     "Cd68"     "Ctsb"     "Lgals3"   "Cstb"    [12] "Capg"     "Rnh1"     "Ctss"     "Anxa4"    "Rgcc"     "Vat1"     "Ctsz"     "Emp1"     "Lgmn"     "Grn"      "Ftl1-ps1"[23] "Pgam1"    "Anxa5"    "Ccl7"    $AM2[1] "S100a1"   "Fabp4"    "Atp6v0d2" "Ctsk"     "Fabp5"    "Lpl"      "Mt1"      "Gstm1"    "Chil3"   $`NK cell` [1] "Gzma"      "Ccl5"      "Nkg7"      "AW112010"  "Il2rb"     "Irf8"      "Prf1"      "Klrb1c"    "Gzmb"      "Serpinb9" [11] "Ctsw"      "Ms4a4b"    "Klrd1"     "Klre1"     "Ncr1"      "Klra4"     "Klra8"     "Serpinb6b" "Klrk1"     "Sh2d2a"   [21] "Ptprcap"   "Sytl3"     "Pik3r1"    "Ifngr1"    "Klra7"     "Sept1"     "Klra9"     "Cma1"     $AM1 [1] "Lpl"      "Plet1"    "Chil3"    "Ear2"     "Abcg1"    "Mrc1"     "Ear1"     "Ltc4s"    "Tcf7l2"   "Axl"      "Il18"    [12] "Hebp1"    "Mt1"      "Atp6v0d2" "Sirpa"    "Nceh1"    "Krt19"    "Fabp1"    "Krt79"    "Klhdc4"   "Plin2"    "Lmo4"    [23] "Ptms"     "Aplp2"    "Sgk1"     "Cidec"    "Cd164"    "Dstn"     "Sept9"    "Ctsd"     "S100a1"   "Wfdc21"   "Ptpn12"  $`Dendritic cell`[1] "H2-Aa"  "H2-Eb1" "H2-Ab1" "Cd74"   "Ifi30"  "S100a4" "Cxcl16"$`Endothelial cell-2` [1] "Emp2"     "Igfbp7"   "Ramp2"    "Ly6c1"    "Cldn5"    "Kdr"      "Cdh5"     "Cyp4b1"   "Adgrf5"   "Epas1"    "Tspan7"  [12] "Icam2"    "Calcrl"   "Tmem100"  "Pmp22"    "Kitl"     "Egfl7"    "Bcam"     "Crip2"    "Pcdh1"    "Cavin2"   "Slc9a3r2"[23] "Pecam1"   "Fmo1"     "Acvrl1"   "Slco2a1"  "Sema3f"   "Aqp1"     "Ednrb"    "Tbx3"     "Esam"     "Cd34"     "Fibin"   [34] "Eng"      "Sept4"    "Stmn2"    "Clic5"    "Scn7a"    "Podxl"    "Ecscr"    "Clu"      "Prx"      "Tmem204"  "Tspan18" [45] "Col4a1"   "Plpp1"    "Hspb1"    "Tbx2"     "Clec1a"   "Tmcc2"    "Rgs12"    "Myct1"    "Sema6a"   "Col4a2"   "Itga3"   [56] "Foxf1"    "Myzap"    "Car4"     "Hpgd"     "Cav1"     "Timp3"    "Nhlrc2"   "Nrp1"     "Krt80"    "Cav2"     "Ly6a"    [67] "Ace"      "Bmpr2"    "Thbd"     "Cd36"     "Id3"      "Anxa3"    "Ctla2a"   "Ehd4"     "S1pr1"    "Ptp4a3"   "Selenop" [78] "Sptbn1"   "Tmem176a" "Fkbp1a"   "Tspan13"  "App"      "Clic4"   $`Cycling basal cell`[1] "Pclaf" "Stmn1" "Mki67" "Birc5"$`B cell` [1] "Cd79a"   "Ly6d"    "Ebf1"    "Cd79b"   "H2-Eb1"  "Ighm"    "H2-Aa"   "Igkc"    "H2-DMb2" "H2-Ab1"  "Cd74"    "Fcmr"    "Iglc2"  [14] "Ms4a1"   "H2-Ob"   "Ccr7"    "Ighd"    "Iglc3"   "Mef2c"   "Cd19"    "H2-Oa"   "Cd37"    "Bank1"   "Mzb1"    "Fcrla"   "Scd1"   [27] "Cd55"    "H2-DMa"  "Ets1"   $Neutrophil [1] "S100a9"        "S100a8"        "Retnlg"        "Il1r2"         "Hdc"           "Csf3r"         "G0s2"          "Ifitm1"        [9] "Lmnb1"         "Acod1"         "Il1b"          "Slpi"          "Pglyrp1"       "Trem1"         "Clec4d"        "Mmp9"         [17] "Mxd1"          "C5ar1"         "Cxcr2"         "Grina"         "Lrg1"          "Hp"            "Ifitm2"        "Slc16a3"      [25] "Lcn2"          "Slc7a11"       "Ccrl2"         "H2-Q10"        "Marcksl1"      "Clec4e"        "Cd300ld"       "Cxcl2"        [33] "Lst1"          "Isg15"         "Hcar2"         "Ets2"          "Pla2g7"        "Gadd45b"       "Tnfaip2"       "Msrb1"        [41] "Cd14"          "Stfa2l1"       "Ccr1"          "Srgn"          "Arg2"          "Wfdc17"        "Ptgs2"         "Sorl1"        [49] "Sirpb1b"       "Nfkbiz"        "Slfn1"         "Snx20"         "Alox5ap"       "2310001H17Rik"$`T cell` [1] "Cd3d"   "Cd3e"   "Cd3g"   "Ms4a4b" "Trbc2"  "Lat"    "Il7r"   "Thy1"   "Ets1"   "Gramd3" "Cd28"   "H2-Q7" $IM [1] "C1qb"   "C1qa"   "C1qc"   "Ms4a7"  "Pf4"    "Mafb"   "Trem2"  "Apoe"   "Lgmn"   "Ccl7"   "H2-Eb1" "H2-Ab1" "H2-Aa" $`AT2 cell-2` [1] "Wfdc2"         "Cyp2f2"        "Sftpa1"        "Selenbp1"      "Sftpb"         "Ldhb"          "Aldh1a1"       "Sftpd"         [9] "Gsta4"         "Cxcl15"        "Gsta3"         "Gstm2"         "B430010I23Rik" "Clic3"         "Sec14l3"       "Retnla"       [17] "Cbr2"          "Scgb3a2"       "Dcxr"          "Nupr1"         "Scgb1a1"       "Mgst1"         "Cyb5a"         "Hp"           [25] "Prdx6"        $`Igha+ AT2  cell` [1] "Igkv13-85" "Hbb-bs"    "Ighv1-64"  "Scgb3a1"   "Jchain"    "Hbb-bt"    "Spp1"      "Mgp"       "Sftpc"     "Scgb3a2"  [11] "Igha"      "Scgb1a1"  $`Endothelial cell-1` [1] "Ramp2"    "Epas1"    "Tspan7"   "Ptprb"    "Adgrf5"   "Cdh5"     "Hpgd"     "Egfl7"    "Ly6c1"    "Calcrl"   "Gpihbp1" [12] "Cldn5"    "Plvap"    "Pltp"     "Tmem100"  "Ly6a"     "Cav1"     "Cavin2"   "Tm4sf1"   "Pecam1"   "Eng"      "Slco2a1" [23] "Ctla2a"   "Sema3c"   "Cyyr1"    "Crip2"    "Clec14a"  "Slc9a3r2" "Ace"      "Sptbn1"   "Acvrl1"   "Cd36"     "Ehd4"    [34] "Cd93"     "Aqp1"     "Bmpr2"    "Itga1"    "Id3"      "Sparc"    "Esam"     "BC028528" "Icam2"    "Thbd"     "S100a16" [45] "Col4a1"   "Plpp1"    "Fmo1"     "Cav2"     "Cavin1"   "Cyp4b1"   "Clec1a"   "Tek"      "Adgrl4"   "Scn7a"    "Flt1"    [56] "Podxl"    "Cxcl12"   "Kit"      "Tie1"     "Foxf1"    "Acer2"    "Ece1"     "Ecscr"    "Cd200"    "Gng11"    "Nfib"    [67] "Slc43a3"  "Tjp1"     "Col4a2"   "Heg1"     "Myzap"    "Glp1r"    "Lyve1"    "Itga6"    "Pakap.1"  "Fermt2"   "Rasip1"  [78] "Pcdh17"   "Jup"      "Kdr"      "Arhgef12" "Hmcn1"    "Bmp6"     "Clic5"    "Dlc1"     "Tcf4"     "S1pr1"    "Ccdc85b" [89] "Clec2d"   "Jun"      "Fkbp1a"   "Clic4"    "Tspan13"  "Selenop" $`AT1 cell` [1] "Ager"     "Cldn18"   "Krt7"     "Clic3"    "Myh14"    "Akap5"    "Cyp2b10"  "Rtkn2"    "Mal2"     "Igfbp2"   "Aqp5"    [12] "Lmo7"     "Ndnf"     "Myo1b"    "Tspan8"   "Gprc5a"   "Limch1"   "Cryab"    "Clic5"    "Emp2"     "Sec14l3"  "Bcam"    [23] "Sparc"    "Cystm1"   "Igfbp7"   "Crip2"    "Timp3"    "Mettl7a1" "Hopx"     "Scd2"     "Pmp22"    "Spint2"   "Ndst1"   [34] "Vegfa"   $`Clara cell` [1] "Scgb3a1" "Scgb3a2" "Bpifa1"  "Bpifb1"  "Reg3g"   "Wfdc2"   "Cyp2f2"  "Mgp"     "Scgb1a1" "Cbr2"    "Sftpc"   "Hbb-bs" $`Ciliated cell`[1] "Dynlrb2" "Hbb-bs"  "Hbb-bt"  "Cbr2"   $`AT2 cell-1` [1] "Sftpc"   "Cbr2"    "Sftpa1"  "Wfdc2"   "Sftpb"   "Sftpd"   "Retnla"  "Cyp2f2"  "Scgb3a2" "Scgb1a1" "Chil1"  $`Ig-producing B cell` [1] "Iglv1"     "Mzb1"      "Iglc1"     "Derl3"     "Eaf2"      "Iglc3"     "Jchain"    "Iglc2"     "Igha"      "Igkc"     [11] "Txndc5"    "Cd79a"     "Edem2"     "Tent5c"    "Creld2"    "Prdx4"     "Ly6d"      "Lman1"     "Trp53inp1" "Sdf2l1"   [21] "Pdia4"     "Edem1"     "Fkbp2"     "Xbp1"      "Sec11c"    "Manf"      "Ssr4"      "Hsp90b1"   "Spcs1"     "Igkv1-110"[31] "Ly6a"

制备好上述数据之后，运行下面代码

N <- length(st.clusts) M <- length(sc.clusts)MIA.results <- matrix(0,nrow = M, ncol = N)row.names(MIA.results) <- sc.clustscolnames(MIA.results) <- st.clustshead(MIA.results)# Gene universegene.universe <- length(rownames(cluster_gene_stat))# Loop over ST clustersfor (i in 1:N) {  # Then loop over SC clusters  # i=1  for (j in 1:M) {    genes1 <- st.marker.list[[st.clusts[i]]]    genes2 <- sc.marker.list[[sc.clusts[j]]]        # Hypergeometric        A <- length(intersect(genes1,genes2))    B <- length(genes1)    C <- length(genes2)    enr <- -log10(phyper(A, B, gene.universe-B, C, lower.tail = FALSE))    dep <- -log10(1-phyper(A, B, gene.universe-B, C, lower.tail = FALSE))    if (enr < dep) {      MIA.results[j,i] = -dep    } else {      MIA.results[j,i] = enr    }  }}# Some results were -Inf...check why this is the case...MIA.results[is.infinite(MIA.results)] <- 0MIA.resultspheatmap::pheatmap(MIA.results,scale ='row' )MIA.results2=MIA.results %>%as.matrix()MIA.results2[ MIA.results >5 ] =5pheatmap::pheatmap(MIA.results2,scale ='row' )# Visualize as heatmaplibrary(reshape2)library(ggplot2)library(dplyr)library(Seurat)heatmap_df <- data.frame('Cell types' = melt(MIA.results)[,1],                         'Tissue regions' = melt(MIA.results)[,2],                         enrichment = melt(MIA.results)[,3])range(heatmap_df$enrichment)head(heatmap_df)boxplot(heatmap_df$enrichment)#根据具体数值，设置最大值和最小值heatmap_df[abs(heatmap_df$enrichment) >7,]$enrichment=7ggplot(data = heatmap_df, aes(x = Tissue.regions, y = Cell.types, fill = enrichment)) +  geom_tile() +   scale_fill_gradient2(low = "navyblue", high = "red", mid = "white",                        midpoint = 0, limit = c(-7,7), space = "Lab",                        name="Enrichment \n -log10(p)") +  ylim(heatmap_df$Cell.types %>% levels() %>% sort() %>% rev())+  theme_minimal()+RotatedAxis() library(reshape2)library(ggplot2)library(dplyr)library(Seurat)library(scales)heatmap_df <- data.frame('Cell types' = melt(MIA.results)[,1],                         'Tissue regions' = melt(MIA.results)[,2],                         enrichment = melt(MIA.results)[,3])head(heatmap_df)ggplot(data = heatmap_df, aes(x = Tissue.regions, y = Cell.types, fill = enrichment)) +  geom_tile() +   scale_fill_gradient2(low = "blue", high = "red",mid = 'white',                        midpoint = 0, limit = c(-1,1), space = "Lab",oob=squish,                       name="Enrichment \n -log10(p)") +  ylim(heatmap_df$Cell.types %>% levels() %>% sort() %>% rev())+  theme_minimal()+RotatedAxis()

MIA.results，就是最终的结果。但是这里的热图具体怎么画，其实就是各显神通了

最后附上完整版本代码

#request 2.libPaths(c( "/home/data/t040413/R/x86_64-pc-linux-gnu-library/4.2",             "/home/data/t040413/R/yll/usr/local/lib/R/site-library",               "/home/data/refdir/Rlib/", "/usr/local/lib/R/library"))setwd('/home/data/t040413/silicosis/spatial/')library(Seurat)library(dplyr)#d.all=readRDS("~/silicosis/spatial/integrated_slides/integrated_slides.rds")load("/home/data/t040413/silicosis/spatial_transcriptomics/silicosis_ST_harmony_SCT_r0.5.rds")dim(d.all)DefaultAssay(d.all)="Spatial"#visium_slides=SplitObject(object = d.all,split.by = "stim")names(d.all);dim(d.all)d.all@meta.data %>%head()head(colnames(d.all))#给d.all 添加meta信息------adata_obs=read.csv("~/silicosis/spatial/adata_obs.csv")head(adata_obs)mymeta=  paste0(d.all@meta.data$orig.ident,"_",colnames(d.all))  %>% gsub("-.*","",.)  # %>%  head()head(mymeta)tail(mymeta)#掉-及其之后内容adata_obs$col= adata_obs$spot_id %>% gsub("-.*","",.)    # %>%  head()head(adata_obs)rownames(adata_obs)=adata_obs$coladata_obs=adata_obs[mymeta,]head(adata_obs)identical(mymeta,adata_obs$col)d.all=AddMetaData(d.all,metadata = adata_obs)DefaultAssay(d.all)='Spatial'DimPlot(d.all,group.by = 'stim')DimPlot(d.all,label = TRUE)dev.off()####st-----cluster_gene_stat=FindAllMarkers(d.all,only.pos = TRUE,logfc.threshold = 0.5)head(cluster_gene_stat)table(cluster_gene_stat$cluster)# Initialize a dataframe for us to store values in:st.clusts=paste0("cluster",seq(0,8,1))head(cluster_gene_stat)st.marker.list=split(cluster_gene_stat,f = cluster_gene_stat$cluster)st.marker.list = lapply(st.marker.list,rownames)head(st.marker.list)#st.clusts=lapply(st.marker.list,rownames)st.clustsst.marker.list###sc----cellType_gene_stat =readRDS("~/silicosis/spatial2/marker_list_silicosis_nogrem1.rds")head(cellType_gene_stat)table(cellType_gene_stat$cluster)cellType_marker = list()for(i in unique(cellType_gene_stat$cluster)){ #按照标准 获得20个细胞类型的marker基因 列表  cellType_marker[[i]] = cellType_gene_stat[cellType_gene_stat$cluster==i & cellType_gene_stat$p_val_adj<0.1 &cellType_gene_stat$avg_log2FC>0.7, "gene"]}cellType_markerhead(cellType_marker)names(cellType_marker)sc.marker.list=cellType_markersc.clusts=names(cellType_marker)sc.clustscellType_markerst.clustsst.marker.listN <- length(st.clusts) M <- length(sc.clusts)MIA.results <- matrix(0,nrow = M, ncol = N)row.names(MIA.results) <- sc.clustscolnames(MIA.results) <- st.clustshead(MIA.results)# Gene universegene.universe <- length(rownames(cluster_gene_stat))# Loop over ST clustersfor (i in 1:N) {  # Then loop over SC clusters  # i=1  for (j in 1:M) {    genes1 <- st.marker.list[[st.clusts[i]]]    genes2 <- sc.marker.list[[sc.clusts[j]]]        # Hypergeometric        A <- length(intersect(genes1,genes2))    B <- length(genes1)    C <- length(genes2)    enr <- -log10(phyper(A, B, gene.universe-B, C, lower.tail = FALSE))    dep <- -log10(1-phyper(A, B, gene.universe-B, C, lower.tail = FALSE))    if (enr < dep) {      MIA.results[j,i] = -dep    } else {      MIA.results[j,i] = enr    }  }}# Some results were -Inf...check why this is the case...MIA.results[is.infinite(MIA.results)] <- 0MIA.resultspheatmap::pheatmap(MIA.results,scale ='row' )MIA.results2=MIA.results %>%as.matrix()MIA.results2[ MIA.results >5 ] =5pheatmap::pheatmap(MIA.results2,scale ='row' )# Visualize as heatmaplibrary(reshape2)library(ggplot2)library(dplyr)library(Seurat)heatmap_df <- data.frame('Cell types' = melt(MIA.results)[,1],                         'Tissue regions' = melt(MIA.results)[,2],                         enrichment = melt(MIA.results)[,3])range(heatmap_df$enrichment)head(heatmap_df)boxplot(heatmap_df$enrichment)heatmap_df[abs(heatmap_df$enrichment) >7,]$enrichment=7ggplot(data = heatmap_df, aes(x = Tissue.regions, y = Cell.types, fill = enrichment)) +  geom_tile() +   scale_fill_gradient2(low = "navyblue", high = "red", mid = "white",                        midpoint = 0, limit = c(-7,7), space = "Lab",                        name="Enrichment \n -log10(p)") +  ylim(heatmap_df$Cell.types %>% levels() %>% sort() %>% rev())+  theme_minimal()+RotatedAxis() library(reshape2)library(ggplot2)library(dplyr)library(Seurat)library(scales)heatmap_df <- data.frame('Cell types' = melt(MIA.results)[,1],                         'Tissue regions' = melt(MIA.results)[,2],                         enrichment = melt(MIA.results)[,3])head(heatmap_df)ggplot(data = heatmap_df, aes(x = Tissue.regions, y = Cell.types, fill = enrichment)) +  geom_tile() +   scale_fill_gradient2(low = "blue", high = "red",mid = 'white',                        midpoint = 0, limit = c(-1,1), space = "Lab",oob=squish,                       name="Enrichment \n -log10(p)") +  ylim(heatmap_df$Cell.types %>% levels() %>% sort() %>% rev())+  theme_minimal()+RotatedAxis()