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Different result of "Visualize average top pairs genes expression for training data" #38

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hyjforesight opened this issue Jun 10, 2021 · 2 comments

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@hyjforesight
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Hello Yuqi,
When I am running the "Visualize average top pairs genes expression for training data" part, there comes a big list of missing genes
image
and a Warning message:
In brewer.pal(n = 12, name = "Spectral") :
n too large, allowed maximum for palette Spectral is 11
Returning the palette you asked for with that many colors

The result is like this, not like what you show in the tutorial.
image

Could you please tell me how to fix this issue?
Thanks!
Best,
YJ

@yuqiyuqitan
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Collaborator

Hi YJ,

I don't have enough information about what you did to figure out what went wrong. Can you elaborate?

@hyjforesight
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Hello Yuqi,
Please check the following coding. Thanks!

stPark = utils_loadObject("sampTab_Park_MouseKidney_062118.rda")

expPark = utils_loadObject("expMatrix_Park_MouseKidney_Oct_12_2018.rda")
dim(expPark)
[1] 16272 43745
[1] 16272 43745
Error: unexpected '[' in "["

genesPark = rownames(expPark)

rm(expPark)
gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 2069336 110.6 4191592 223.9 2572041 137.4
Vcells 4421116 33.8 71591799 546.3 72832775 555.7

expTMraw = utils_loadObject("expMatrix_TM_Raw_Oct_12_2018.rda")
dim(expTMraw)
[1] 23433 24936
[1] 23433 24936
Error: unexpected '[' in "["

stTM = utils_loadObject("sampTab_TM_053018.rda")
dim(stTM)
[1] 24936 17
[1] 24936 17
Error: unexpected '[' in "["

stTM<-droplevels(stTM)

commonGenes = intersect(rownames(expTMraw), genesPark)
length(commonGenes)
[1] 13831
[1] 13831
Error: unexpected '[' in "["

expTMraw = expTMraw[commonGenes,]

set.seed(100) #can be any random seed number
stList = splitCommon(sampTab=stTM, ncells=100, dLevel="newAnn")
alveolar macrophage : Category alveolar macrophage has 62 samples. Note this category has a samller number than ncells. 62
B cell : 3134
bladder urothelial cell : 759
bladder_mesenchymal : 859
cardiac muscle cell : Category cardiac muscle cell has 60 samples. Note this category has a samller number than ncells. 60
cardiac_fibroblast : 222
chondrocyte-like : 165
endocardial cell : Category endocardial cell has 52 samples. Note this category has a samller number than ncells. 52
endothelial cell : 1890
erythroblast : 152
erythrocyte : Category erythrocyte has 74 samples. Note this category has a samller number than ncells. 74
granulocyte : 520
hematopoietic precursor cell : 117
hepatocyte : 882
keratinocyte : 1203
kidney capillary endothelial cell : 117
kidney proximal straight tubule epithelial cell : 618
kidney_duct_epithelial : 355
late pro-B cell : 141
limb_mesenchymal : 540
luminal epithelial cell of mammary gland : 137
lung_mammary_stromal : 2072
macrophage : 1340
mammary_basal_cell : 115
monocyte : 370
natural killer cell : 600
neuroendocrine cell : 282
skeletal muscle satellite cell : 190
T cell : 1823
tongue_basal_cell : 1726
trachea_epithelial : 434
trachea_mesenchymal : 3925
stTrain = stList[[1]]
expTrain = expTMraw[,rownames(stTrain)]

system.time(class_info<-scn_train(stTrain = stTrain, expTrain = expTrain, nTopGenes = 10, nRand = 70, nTrees = 1000, nTopGenePairs = 25, dLevel = "newAnn", colName_samp = "cell"))
Sample table has been prepared
Expression data has been normalized
Finding classification genes
Done testing
There are 484 classification genes
Finding top pairs
nPairs = 190 for alveolar macrophage
nPairs = 190 for B cell
nPairs = 190 for bladder urothelial cell
nPairs = 190 for bladder_mesenchymal
nPairs = 190 for cardiac muscle cell
nPairs = 190 for cardiac_fibroblast
nPairs = 190 for chondrocyte-like
nPairs = 190 for endocardial cell
nPairs = 190 for endothelial cell
nPairs = 190 for erythroblast
nPairs = 190 for erythrocyte
nPairs = 190 for granulocyte
nPairs = 190 for hematopoietic precursor cell
nPairs = 190 for hepatocyte
nPairs = 190 for keratinocyte
nPairs = 190 for kidney capillary endothelial cell
nPairs = 190 for kidney proximal straight tubule epithelial cell
nPairs = 190 for kidney_duct_epithelial
nPairs = 190 for late pro-B cell
nPairs = 190 for limb_mesenchymal
nPairs = 190 for luminal epithelial cell of mammary gland
nPairs = 190 for lung_mammary_stromal
nPairs = 190 for macrophage
nPairs = 190 for mammary_basal_cell
nPairs = 190 for monocyte
nPairs = 190 for natural killer cell
nPairs = 190 for neuroendocrine cell
nPairs = 190 for skeletal muscle satellite cell
nPairs = 190 for T cell
nPairs = 190 for tongue_basal_cell
nPairs = 190 for trachea_epithelial
nPairs = 190 for trachea_mesenchymal
There are 797 top gene pairs
Finished pair transforming the data
Number of missing genes 0
All Done
user system elapsed
616.27 22.44 643.94

#validate data
stTestList = splitCommon(sampTab=stList[[2]], ncells=100, dLevel="newAnn") #normalize validation data so that the assessment is as fair as possible
alveolar macrophage : Category alveolar macrophage has 3 samples. Note this category has a samller number than ncells. 3
B cell : 3034
bladder urothelial cell : 659
bladder_mesenchymal : 759
cardiac muscle cell : Category cardiac muscle cell has 3 samples. Note this category has a samller number than ncells. 3
cardiac_fibroblast : 122
chondrocyte-like : Category chondrocyte-like has 65 samples. Note this category has a samller number than ncells. 65
endocardial cell : Category endocardial cell has 3 samples. Note this category has a samller number than ncells. 3
endothelial cell : 1790
erythroblast : Category erythroblast has 52 samples. Note this category has a samller number than ncells. 52
erythrocyte : Category erythrocyte has 3 samples. Note this category has a samller number than ncells. 3
granulocyte : 420
hematopoietic precursor cell : Category hematopoietic precursor cell has 17 samples. Note this category has a samller number than ncells. 17
hepatocyte : 782
keratinocyte : 1103
kidney capillary endothelial cell : Category kidney capillary endothelial cell has 17 samples. Note this category has a samller number than ncells. 17
kidney proximal straight tubule epithelial cell : 518
kidney_duct_epithelial : 255
late pro-B cell : Category late pro-B cell has 41 samples. Note this category has a samller number than ncells. 41
limb_mesenchymal : 440
luminal epithelial cell of mammary gland : Category luminal epithelial cell of mammary gland has 37 samples. Note this category has a samller number than ncells. 37
lung_mammary_stromal : 1972
macrophage : 1240
mammary_basal_cell : Category mammary_basal_cell has 15 samples. Note this category has a samller number than ncells. 15
monocyte : 270
natural killer cell : 500
neuroendocrine cell : 182
skeletal muscle satellite cell : Category skeletal muscle satellite cell has 90 samples. Note this category has a samller number than ncells. 90
T cell : 1723
tongue_basal_cell : 1626
trachea_epithelial : 334
trachea_mesenchymal : 3825
stTest = stTestList[[1]]
expTest = expTMraw[commonGenes,rownames(stTest)]

#predict
classRes_val_all = scn_predict(cnProc=class_info[['cnProc']], expDat=expTest, nrand = 50)
Loaded in the cnProc
All Done

tm_heldoutassessment = assess_comm(ct_scores = classRes_val_all, stTrain = stTrain, stQuery = stTest, dLevelSID = "cell", classTrain = "newAnn", classQuery = "newAnn", nRand = 50)

plot_PRs(tm_heldoutassessment)

plot_metrics(tm_heldoutassessment)

#Create a name vector label used later in classification heatmap where the values are cell types/ clusters and names are the sample names

nrand = 50
sla = as.vector(stTest$newAnn)
names(sla) = as.vector(stTest$cell)
slaRand = rep("rand", nrand)
names(slaRand) = paste("rand_", 1:nrand, sep='')
sla = append(sla, slaRand) #include in the random cells profile created

sc_hmClass(classMat = classRes_val_all,grps = sla, max=300, isBig=TRUE)

plot_attr(classRes=classRes_val_all, sampTab=stTest, nrand=nrand, dLevel="newAnn", sid="cell")
Warning message:
In depth(path) : reached elapsed time limit

gpTab = compareGenePairs(query_exp = expTest, training_exp = expTrain, training_st = stTrain, classCol = "newAnn", sampleCol = "cell", RF_classifier = class_info$cnProc$classifier, numPairs = 20, trainingOnly= TRUE)

train = findAvgLabel(gpTab = gpTab, stTrain = stTrain, dLevel = "newAnn")

hm_gpa_sel(gpTab, genes = class_info$cnProc$xpairs, grps = train, maxPerGrp = 50)
Missing genes: Ear2_Ifitm3,Ear2_Ubb,Abcg1_Ubc,Ear2_Ifitm2,Abcg1_Ubb,Abcg1_Nfkbia,Mpeg1_Ifitm3,Mpeg1_Ubb,Il18_Nfkbia,Mpeg1_Ifitm2,Sirpa_Ifitm2,Il18_Ifitm3,Il1rn_Nfkbia,Nceh1_Ubc,Il18_Jun,Klhdc4_Ubc,Il1rn_S100a6,Il1rn_Jun,Sirpa_Jun,Sirpa_Xist,Nceh1_Xist,Pla2g15_Xist,Ccl6_S100a6,Nceh1_Cd63,Pla2g15_Cd63,H2-Ob_Txn1,Cd79b_Txn1,Cd79a_Txn1,H2-Eb1_Itm2b,H2-Aa_Itm2b,H2-Ob_Ifitm3,H2-Ob_Ifitm2,H2-Oa_S100a6,H2-Oa_Ifitm3,H2-Oa_Anxa2,Cd79a_S100a6,Cd79b_Ifitm2,Cd79b_Ifitm3,H2-Eb1_Ifitm2,H2-Eb1_Anxa2,H2-Aa_Dstn,H2-Aa_S100a6,Cd37_Anxa2,Cd37_Dstn,Cd19_Dstn,H2-Ab1_Cd63,Cd19_Cd63,H2-Ab1_Cd9,Cd19_Cd9,Upk1a_Lgals1,Upk1a_Vim,Ivl_Nfkbia,Ivl_Vim,Ivl_Aldh2,Upk1b_Ifitm3,Foxq1_Hspa8,Upk1b_Aldh2,Upk1b_Emp3,Akr1b8_Ifitm3,Akr1b8_S100a10,Sprr1a_Hspa8,Foxq1_B2m,Krt23_Nfkbia,Krt23_S100a10,Krt23_Ifitm3,Akr1b8_Nfkbia,2200002D01Rik_S100a10,Krt7_Hspa8,2200002D01Rik_B2m,Foxq1_Lgals1,Sprr1a_B2m,Sprr1a_Lgals1,Krt7_Xist,Mmp23_Xist,Tcf21_Xist,Bmp4_Xist,Serpina3n_Chchd10,Serpina3n_Ucp2,Serpina3n_Coro1a,Mmp23_Ucp2,Bmp4_Chchd10,Bmp4_Srgn,Mmp23_Cd52,Col12a1_Cd24a,Col12a1_Srgn,Col12a1_Cd52,Thbs2_Srgn,Thbs2_Cd24a,Thbs2_Rac2,Htra1_Cd24a,Col1a2_Col3a1,Htra1_Coro1a,Htra1_Laptm5,Tnni3_Rps19,Tnni3_Ftl1,Tnni3_Actb,Smpx_Actb,Tnnt2_Rps19,Tnnt2_Actb,Tnnc1_Ppia,Tnnc1_H3f3b,Cox8b_Actg1,Pln_Myl6,Cox6a2_Rps19,Tnnt2_Ptma,Tnnc1_Actg1,Cox8b_Ptma,Cox8b_H3f3b,Csrp3_Ppia,Smpx_Myl6,Cox6a2_Ftl1,Cox6a2_Ppia,Smpx_Actg1,Csrp3_Ftl1,Pln_H3f3b,Csrp3_Myl6,Pln_Ptma,Ttn_Cfl1,Tcf21_Fosb,Matn2_Fosb,Cygb_Fosb,Col15a1_Btg1,Tcf21_Ier5,Matn2_Lgals3,Matn2_Ier5,Col15a1_Ier5,Htra3_Btg1,Tcf21_Btg1,Scn7a_Atp1a1,Scn7a_Lgals3,Scn7a_Spint2,Htra3_Slc25a5,Col15a1_Slc25a5,Cygb_Slc25a5,Cygb_Atp1a1,Htra3_Cox5a,Cfh_Cox5a,Ccdc80_Cox5a,Cfh_Lgals3,Cfh_Ucp2,Ccdc80_Atp1a1,Ccdc80_Ucp2,Fbln1_Spint2,Fmod_Uba52,Cilp2_Ndufa4,Cilp2_Ndufb7,Thbs4_Cox6b1,Thbs4_Ndufa4,Cilp2_Atp5g2,Serpinf1_Uba52,Fmod_Cox6b1,Fmod_Atp5g2,Angptl7_H2afj,Angptl7_Uqcrfs1,Comp_Ndufa4,Angptl7_Ucp2,Comp_Cox6b1,Comp_Atp5g2,Fbln7_Uqcrq,Col12a1_Ndufb7,Col12a1_H2afj,Fbln7_Ucp2,Fbln7_H2afj,Abi3bp_Uqcrq,Timp1_Uqcrq,Abi3bp_Ndufb7,Npr3_Jund,Npr3_Junb,Npr3_S100a6,Hmcn1_S100a6,Foxc1_Mt1,Mmrn2_Jund,Hmcn1_Jund,Hmcn1_Mt1,Mmrn2_Junb,Foxc1_Junb,Bace2_S100a6,Mmrn2_Fos,Bace2_Atf4,Bace2_Mt1,Foxc1_Fos,Ptgs1_Fos,Ptgs1_Ier3,Ptgs1_Atf4,Cgnl1_Atf4,Cgnl1_Mt2,Cgnl1_Fosb,Sdpr_Fosb,Sdpr_Ier3,Sdpr_Mt2,Eng_Ier3,Gpihbp1_Rpl12,Gpihbp1_Ndufa13,Gpihbp1_Atp5e,Rnd1_Rps28,Cdh5_Ndufa13,Cdh5_Cox8a,Ly6c1_Rps9,Ly6c1_Rpsa,Cdh5_Prdx5,Ly6c1_Rps28,Rnd1_Rpl12,Apold1_Ndufa13,Apold1_Rpl12,Rnd1_Rps9,Esam_Cox8a,Esam_Atp5e,Apold1_Prdx5,Fabp4_Rps9,Flt1_Prdx5,Fabp4_Rps28,Fabp4_Cox8a,Flt1_H2afj,Rasip1_H2afj,Ptprb_H2afj,Flt1_Atp5e,Slc4a1_Nme2,Alas2_Hspa8,Hba-a2_Ybx1,Alas2_Rps21,Hba-a2_Nme2,Alas2_Ppia,Hba-a2_Hsp90ab1,Snca_Ybx1,Snca_Hsp90ab1,Slc4a1_Ybx1,Snca_Nme2,Slc4a1_Hspa8,Hba-a1_Hspa8,Hba-a1_Actg1,Hba-a1_Hsp90ab1,Ube2l6_Actg1,Car2_Rpl36,Car2_Ppia,Fech_Ppia,Fech_Rpl36,Ube2l6_Rpl38,Fech_Rpl38,Car2_Rpl38,Ube2l6_Rps21,Slc25a37_Actg1,Folr2_Cd9,Folr2_Crip2,Folr2_S100a16,C1qb_Crip2,C1qc_Crip2,C1qc_Cd9,C1qc_Nedd4,C1qb_Nedd4,C1qb_Serpinh1,C1qa_Nedd4,C1qa_Cd9,C1qa_Serpinh1,Csf1r_Anxa1,Pf4_Anxa1,Aif1_Anxa1,Pf4_Csrp1,Aif1_Csrp1,Pf4_Tsc22d1,Hpgd_S100a16,Csf1r_Csrp1,Hpgd_Hspb1,Aif1_Tsc22d1,Csf1r_Tsc22d1,Hpgd_Nfib,Fcgr3_S100a16,Cd177_Nme2,Cd177_Hsp90ab1,Ngp_Rpl41,Trem3_Nme2,Ifitm6_Rpl10,Pglyrp1_Rpl41,Ifitm6_Rplp1,Ifitm6_Rpl35,Ltf_Rpl41,Trem3_Hsp90ab1,Pglyrp1_Eef1a1,Pglyrp1_Rpl10,Cd177_Rpl14,Ltf_Rplp1,Ltf_Rpl35,Ngp_Rpl10,Ngp_Rplp1,Camp_Eef1a1,Camp_Rpl35,Camp_Rps2,Trem3_Rpl14,Lcn2_Eef1a1,Lcn2_Rps2,S100a9_Rps2,S100a9_Rpl14,Prtn3_S100a6,Prtn3_Ubc,Myb_Gsn,Prtn3_Fth1,Myb_Id3,Cmtm7_Ubc,Rgs18_Gsn,Plac8_Fth1,Atp8b4_S100a6,Ramp1_Ubc,Ramp1_Gsn,Phgdh_Lmna,Ramp1_S100a6,Atp8b4_Ptms,Atp8b4_Ahnak,Rgs18_Ptms,Phgdh_Ptms,Phgdh_Id3,Rgs18_Id3,BC035044_Ahnak,Clec12a_Ahnak,BC035044_Crip2,BC035044_Lmna,Clec12a_Crip2,Serpina1c_Rpl23a,Serpina1c_Rps9,Serpina1c_Rpl21,Serpina1b_Rpl23a,Serpina1b_Rps9,Serpina1b_Tmsb4x,Apoa1_Rpl23a,Apoa1_Rps9,Apoa1_Rpl21,Apoa2_Rps23,Serpina1a_Rpl21,Serpina1a_Rpl9,Serpina1a_Rpl13,Apoc3_Rpl9,Apoc3_Rplp2,Apoc3_Rpl13,Alb_Rplp2,Apoa2_Rpl9,Apoa2_Rplp2,Alb_Actg1,Apoc4_Tmsb4x,Alb_Rpl13,Serpina1d_Tmsb4x,Apoc4_Actg1,Serpina1d_Actg1,Them5_Fth1,S100a14_Fth1,Calml3_Fth1,Calml3_Gpx4,Ovol1_Gpx4,Rab25_Gpx4,Aldh3b2_Arpc1b,Sbsn_Ftl1,Them5_Ftl1,Rab25_Ftl1,Tgm1_Arpc1b,Tgm1_Cyba,Tgm1_B2m,Calml3_B2m,Them5_Arpc1b,Aldh3b2_B2m,Ovol1_H2-K1,Aldh3b2_Serinc3,Ovol1_Serinc3,Sbsn_H2-K1,S100a14_H2-K1,Sbsn_Vim,Lgals7_Xist,S100a14_Serinc3,Lgals7_Cyba,Meis2_Gsn,Meis2_Cd63,Clec14a_Gsn,Slc9a3r2_Gsn,Plscr2_Cd63,Clec14a_Cd63,Meis2_Mt1,Emcn_Rplp0,Podxl_Mt1,Clec14a_Cebpb,Slc9a3r2_Rpsa,Slc9a3r2_Rplp0,Ptprb_Mt1,Ptprb_Mt2,Emcn_Rpsa,Emcn_Rps27a,Ptprb_Lgals1,Podxl_Mt2,Kdr_Lgals1,Podxl_Sdc4,Egfl7_Lgals1,Kdr_Cebpb,Egfl7_Rpsa,Kdr_Sdc4,Plscr2_Sdc4,Tmem27_Rps6,Slc34a1_H3f3b,Slc34a1_Rpl9,Tmem27_Eif1,Tmem27_Rpl9,Slc34a1_Rps6,Miox_Eif1,Miox_Rpl9,Acsm2_Tmsb4x,Acsm2_H3f3b,Miox_Rps4x,Acsm2_H2-D1,Akr1c21_Rps6,Akr1c21_Tmsb4x,Slc22a8_Tmsb10,Slc22a8_Tmsb4x,Akr1c21_H3f3b,Lrp2_Tmsb10,Fut9_H2-D1,Fut9_Myl12a,Lrp2_Myl12a,Lrp2_H2-D1,Slc22a8_Myl12a,Fut9_Tmsb10,Pdzk1_Rps4x,Kcnj1_Arpc1b,Kng2_B2m,Egf_B2m,Kcnj1_B2m,Ppp1r1a_Rpl4,Egf_Rps16,Egf_Rpl4,Ppp1r1a_Rps6,Wfdc15b_Rps16,Wfdc15b_Rpl4,Wfdc15b_Rpl10,Ppp1r1a_Tmsb4x,Kcnj1_Tmsb4x,Umod_Rps16,Umod_Rpl10,Umod_Rps19,Tmem213_Arpc1b,Sostdc1_Tmsb4x,Clcnkb_Arpc1b,Klk1_Rps6,Klk1_Rpl18a,Klk1_Rps19,Kng2_Rps6,Sostdc1_Rpl18a,Kng2_Rps27a,Pou2af1_Rabac1,Lrmp_Aldoa,Vpreb3_Aldoa,Lrmp_Itm2b,Lmnb1_Itm2b,Pafah1b3_Aldoa,Vpreb3_Rabac1,Lrmp_Rabac1,Pou2af1_Anxa5,Uhrf1_Ifitm3,Pou2af1_Laptm4a,Cenpm_Anxa2,Uhrf1_Anxa2,Cenpm_Ifitm3,Pafah1b3_Laptm4a,Pafah1b3_Anxa2,Top2a_Ifitm3,Cenpm_Anxa5,Uhrf1_Anxa5,Top2a_S100a6,Ezh2_Laptm4a,2810417H13Rik_S100a6,Top2a_Cd63,Ezh2_S100a6,Ifi205_Slc25a5,Ifi205_Ucp2,Ifi205_Cox6b1,Mnda_Arhgdib,Mnda_Ucp2,Mnda_Taldo1,Clec3b_Uqcr11,Clec3b_Cox6b1,Clec3b_Ndufa4,Gfpt2_Cox6b1,Col5a3_Uqcr11,Nid1_Ndufa4,Col5a3_Slc25a5,Itm2a_Uqcr11,Itm2a_Ndufa4,Itm2a_Slc25a5,Col5a3_Taldo1,Gfpt2_Spint2,Fbln2_Spint2,Tnxb_Taldo1,Gfpt2_Cd24a,Tnxb_Spint2,Fbln2_Ucp2,Tnxb_Arhgdib,Fbln2_Cd24a,Cldn7_Gstm1,Cldn3_Gstm1,Cldn3_Mgp,Krt19_Gstm1,Cldn3_Id3,Cldn7_Btg2,Krt19_Lgals1,Ptn_Id3,Krt19_Mgp,Ptn_Sparc,Cldn7_Mgp,Ptn_Aldh2,St14_Btg2,Prlr_Aldh2,Krt18_Aldh2,Epcam_Btg2,St14_Id3,St14_Sparc,Krt18_Lgals1,Krt18_Sparc,Krt8_Lgals1,Epcam_Cd47,Sod3_Tpt1,Sod3_Hspa8,Inmt_Eef1a1,Inmt_Uba52,Ppp1r14a_Hspa8,Sod3_Hsp90ab1,Pcolce2_Hspa8,Ppp1r14a_Hsp90ab1,Fhl1_Hsp90ab1,Inmt_Tpt1,Ppp1r14a_Cox4i1,Pcolce2_Fau,Pcolce2_Tpt1,Npnt_Gapdh,Lrp4_Gapdh,Fhl1_Uba52,Limch1_Cox4i1,Lrp4_Pabpc1,Limch1_Gapdh,Fhl1_Cox4i1,Npnt_Pabpc1,Npnt_Cox5a,Tbx2_Pabpc1,Lrp4_Cox5a,Limch1_Cox5a,Il1b_Dstn,Il1b_Jun,Il1b_Pebp1,Bcl2a1d_Dstn,H2-DMb1_Pebp1,Cd83_Pebp1,Aif1_Mgst1,Cd83_Jun,Bcl2a1d_Mgst1,H2-DMb1_Dstn,Cd83_Tubb4b,Aif1_Tubb4b,Bcl2a1b_Mgst1,Bcl2a1b_Tubb4b,Bcl2a1d_Jun,Aif1_Gstm1,Bcl2a1b_Nedd4,H2-DMb1_Gstm1,H2-Aa_Crip2,H2-Aa_Nedd4,H2-Aa_S100a16,H2-Eb1_Nedd4,H2-Eb1_S100a16,H2-Eb1_Serpinh1,H2-Ab1_Crip2,Fst_Crip1,Tpm2_Itm2b,Tagln_Crip1,Fst_Cst3,Tagln_Cst3,Fst_Dusp1,Tpm2_Serf2,Acta2_Itm2b,Acta2_Crip1,Tagln_Itm2b,Acta2_Cst3,Cda_Ndufv3,Arl4c_Sh3bgrl3,Fermt1_Btg2,Palld_Btg2,Fermt1_Ndufv3,Fermt1_Fos,Slpi_Sh3bgrl3,Palld_Dusp1,Palld_Zfp36,Tpm2_Fos,Arl4c_Serf2,Cxcl14_Serf2,Cxcl14_Fos,Cda_Dusp1,Ccr2_Mt1,Ccr2_Cd9,Ccr2_Zfp36l1,Ms4a6c_Mt1,Pld4_Cd81,Ms4a6c_Cd81,F13a1_Mt1,F13a1_Cd63,F13a1_Cd81,Ms4a6c_Cd63,Ms4a4c_Zfp36l1,Ms4a4c_Hmgn1,Tifab_Hmgn1,Ms4a4c_Sdc4,Pld4_Zfp36l1,Pld4_Cd63,Tifab_Cd9,Tifab_Sdc4,Ly86_Hmgn1,Ccl9_Sdc4,Ccl9_Cd9,Ccl9_Lmna,Ly86_Lmna,Ly86_Igfbp7,Lyz1_Lmna,Ncr1_App,Ncr1_Dstn,Ncr1_Ifitm3,Klrb1c_Mt1,Klrb1c_Gpx1,Klrb1c_App,Gzma_Gpx1,Klre1_Mt1,Ccl5_Fth1,Klre1_Ctsb,Gzma_Ctsb,Klre1_App,Klrk1_Gpx1,Klrk1_Ctsb,Klrk1_Ifitm3,Nkg7_Fth1,Gzmb_Mt1,Gzmb_Cd81,Gzmb_Ifitm2,Klrd1_Ifitm3,Klrd1_Ifitm2,Klrd1_Dstn,Ccl5_Dstn,Ccl5_Ifitm2,Rgs5_Rps28,Rgs5_Rps21,Myl9_Rpl39,Rgs5_Eef1b2,Plp1_Xist,Plp1_Eef1b2,Mpz_Rps28,Plp1_Rps28,Mpz_Rps21,Mpz_Eef1b2,Gm13889_Rpl38,Myl9_Rps21,Myl9_Rpl38,Sncg_Ly6e,Gm13889_Rpl39,Mbp_Uba52,Mbp_Rps29,Mbp_Rpl38,Gm13889_Rps29,Mustn1_Rpl39,Sncg_Xist,Mustn1_Rps10,Cryab_Rps29,Mustn1_Ly6e,Sncg_Rps10,Asb5_Ndufa3,Asb5_Gpx1,Crlf1_Clic1,Des_Ndufa3,Crlf1_Itm2b,Des_Ndufa4,Des_Gpx1,Meg3_Itm2b,Arl4d_Ndufa4,Meg3_Serf2,Crlf1_Gpx1,Akap2_Itm2b,Pdlim4_Clic1,Ncam1_Ndufa3,Chrnb1_Clic1,Ncam1_Ostf1,Chrnb1_Ly6e,Arl4d_Ly6e,Cd82_Ndufa4,Pdlim4_Ly6e,Chrnb1_Sh3bgrl3,Cd82_Serf2,Cd82_Sh3bgrl3,Arl4d_H2afj,Lat_Rps27l,Lat_Dstn,Lat_Aldh2,Lck_Rps27l,Ms4a6b_Ifitm3,Ms4a6b_Ifitm2,Ms4a6b_Cst3,Lck_Cst3,Lck_Aldh2,Ms4a4b_Rps27l,Ms4a4b_Aldh2,Ms4a4b_Ifitm3,Satb1_Ifitm2,Ltb_Dstn,Satb1_Ifitm3,Ltb_Cd81,Satb1_Cd81,Ltb_Cd63,Cd2_Cd81,Limd2_Itm2b,Gimap3_Cd63,Gimap3_Laptm4a,Wnt10a_Xist,Wnt10a_H2-K1,Wnt10a_B2m,Them5_Vim,Them5_Sepp1,S100a14_B2m,S100a14_H2-D1,Moxd1_Lgals1,Moxd1_B2m,Lgals7_H2-D1,Plek2_Serinc3,Moxd1_Vim,Lgals7_H2-K1,Plek2_Sepp1,Ckmt1_Serinc3,Ckmt1_Sepp1,Plek2_Cyba,Krt5_H2-D1,Ckmt1_Cyba,Igfbp2_Lgals1,Igfbp2_Vim,Lypd2_Vim,Lypd2_Rbm3,Lypd2_Arpc4,Tg_Vim,Tspan1_Xist,Cldn3_Xist,Tg_Ybx1,Ager_Hnrnpf,Ager_Tpm3,Ager_Vim,Cldn3_Serinc3,Cyp2f2_Sepp1,Tspan1_Serinc3,Tspan1_Ybx1,Ces1d_Sepp1,Cbr2_Ybx1,Tg_Klf2,Cldn3_Tpm3,Cyp2f2_Rbm3,Cyp2f2_Hnrnpf,Cbr2_Rbm3,Ces1d_Xist,Cbr2_Hnrnpf,Ces1d_Serinc3,Ifitm1_Sepp1,Hapln1_H2-K1,Hapln1_Ucp2,Hapln1_Xist,Wif1_Slc25a5,Wif1_Xist,Wif1_H2-D1,Scara3_Xist,Scara3_H2-D1,Scara3_H2-K1,Cpe_Atp5b,Col8a1_H2-D1,Col27a1_2010107E04Rik,Cpe_2010107E04Rik,Col27a1_Atp5b,Col27a1_Slc25a5,Col8a1_Slc25a5,Col8a1_Atp5b,Cpe_Atp5f1,Cadm1_H2-K1,Cadm1_2010107E04Rik,Cadm1_Mdh2,1500015O10Rik_Mdh2,1500015O10Rik_Ucp2,1500015O10Rik_Atp5f1,Gpc6_Mdh2
Warning message:
In brewer.pal(n = 12, name = "Spectral") :
n too large, allowed maximum for palette Spectral is 11
Returning the palette you asked for with that many colors

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