emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

emb = as.matrix(og_expDat[, c("Ftsne_t2_allGenesFiltbren_1","Ftsne_t2_allGenesFiltbren_2")]) rownames(emb) <- og_expDat$V1 genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes gene = "Mcam" gene.relative.velocity.estimates(emat, nmat, deltaT=1, kCells = 100, kGenes=1, fit.quantile=fit.quantile, cell.emb=emb, cell.colors=cell.colors, cell.dist=cell.dist, show.gene=gene, old.fit = rvel.cd)

###Plot Average Spliced/Unspliced for particular genes par(mfrow=c(2,3)) for (gene in genes){ ymax = max(avgRatio[[gene]][is.finite(avgRatio[[gene]])]) if (is.infinite(ymax)) ymax = 1 barplot(avgRatio[[gene]], main=gene, xlab="Clusters", ylab="Ratio of Average Spliced/Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids, border=T) }

###Plot Average Spliced/Unspliced for particular genes par(mfrow=c(2,3)) for (gene in genes){ ymax = max(avgRatio[[gene]][is.finite(avgRatio[[gene]])]) if (is.infinite(ymax)) ymax = 1 barplot(avgRatio[[gene]], main=gene, xlab="Clusters", ylab="Ratio of Average Spliced/Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids, border=T) }

###Plot Average Spliced/Unspliced for particular genes par(mfrow=c(2,3)) for (gene in genes){ ymax = max(avgRatio[[gene]][is.finite(avgRatio[[gene]])]) if (is.infinite(ymax)) ymax = 1 barplot(avgRatio[[gene]], main=gene, xlab="Clusters", ylab="Ratio of Average Spliced/Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids, border=T) }

###Plot Average Spliced/Unspliced for particular genes par(mfrow=c(2,3)) for (gene in genes){ ymax = max(avgRatio[[gene]][is.finite(avgRatio[[gene]])]) if (is.infinite(ymax)) ymax = 1 barplot(avgRatio[[gene]], main=gene, xlab="Clusters", ylab="Ratio of Average Spliced/Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids, border=T) }

###Plot Average Spliced/Unspliced for particular genes par(mfrow=c(2,3)) for (gene in genes){ ymax = max(avgRatio[[gene]][is.finite(avgRatio[[gene]])]) if (is.infinite(ymax)) ymax = 1 barplot(avgRatio[[gene]], main=gene, xlab="Clusters", ylab="Ratio of Average Spliced/Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids, border=T) }

###Plot Average Spliced/Unspliced for particular genes par(mfrow=c(2,3)) for (gene in genes){ ymax = max(avgRatio[[gene]][is.finite(avgRatio[[gene]])]) if (is.infinite(ymax)) ymax = 1 barplot(avgRatio[[gene]], main=gene, xlab="Clusters", ylab="Ratio of Average Spliced/Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids, border=T) }

###Plot Average Spliced/Unspliced for each cluster par(mfrow = c(1,1)) ymax = max(avgRatio$Total[is.finite(avgRatio$Total)]) if (is.infinite(ymax)) ymax = 1 barplot(avgRatio$Total, main="Average Spliced/Unspliced for each cluster", xlab="Clusters", ylab="Ratio of Average Spliced/Unspliced", col = "Wheat", ylim=c(0,ymax), names.arg = new.cluster.ids)

###Plot normalized Unspliced and Spliced for particular genes genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) if (is.infinite(ymax)) ymax = 1 barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) if (is.infinite(ymax)) ymax = 1 barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

###Plot normalized Unspliced and Spliced for particular genes genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) if (is.infinite(ymax)) ymax = 1 barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) if (is.infinite(ymax)) ymax = 1 barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

###Plot normalized Unspliced and Spliced for particular genes genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) if (is.infinite(ymax)) ymax = 1 barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) if (is.infinite(ymax)) ymax = 1 barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

###Plot normalized Unspliced and Spliced for particular genes genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) if (is.infinite(ymax)) ymax = 1 barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) if (is.infinite(ymax)) ymax = 1 barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

###Plot normalized Unspliced and Spliced for particular genes genes <- list(Ar = c("Bmx", "Gja5", "Acvrl1"), Lv = c("Ackr1", "Sele", "Selp", "Vwf"), HEV = c("Ackr1", "Fut7", "Chst4", "Gcnt1"), CapEC1 = c("Nfkbia", "Dusp1", "Cxcl1", "Cxcl12"), CapEC2 = c("Id1", "Id3", "Cdkn1a", "Cdkn2a"), CapEC3 = c("Irf7", "Cxcl9", "Cxcl10"), #Cxcl11 CapEC4 = c("Enpp2"), CapRC = c("Nes", "Cxcr4", "Vim", "Cd34", "Apln", "Dll4", "Esm1", "Mcam")) allGenes <- as.character(unlist(genes)) genes <-allGenes par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) if (is.infinite(ymax)) ymax = 1 barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) if (is.infinite(ymax)) ymax = 1 barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

par(mfrow=c(2,2)) for (gene in genes){ ymax = max(avgUnSplNorm[[gene]][is.finite(avgUnSplNorm[[gene]])]) #new.cluster.ids <- is.infinite(avgUnSplNorm[[gene]]) barplot(avgUnSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) ymax = max(avgSplNorm[[gene]][is.finite(avgSplNorm[[gene]])]) barplot(avgSplNorm[[gene]], main=gene, xlab="Clusters", ylab="Normalized Spliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids) }

avgRatio$Total <- NA sumsSpl <- rowSums(avgSpl) sumsUnSpl <- rowSums(avgUnSpl) avgRatio$Total<- sumsSpl/sumsUnSpl # Plot Average Spliced/Unspliced by each cluster ymax = max(avgRatio$Total[is.finite(avgRatio$Total)]) barplot(avgRatio$Total, main="Average Spliced/Unspliced for each cluster", xlab="Clusters", ylab="Ratio of Average Spliced/Unspliced", col = "wheat", ylim=c(0,ymax), names.arg = new.cluster.ids)

ggplot() + geom_point(data = as.data.frame(rvel.cd.exp), mapping = aes(x = Irf7_conv.nmat.norm, y = Irf7_conv.emat.norm, color = as.factor(og_expDat$og_sClustsPCA_t2X0.3_3_Y0.25_10_R0.3))) + scale_fill_brewer(palette = "Set1") + theme(legend.title = element_blank())

toBeP <- pcaVelP genes2plot <- c("Chst4", "Apln", "Nes", "Ly6c1", "Pdgfra", "Pdpn", "Adm", "Pgf", "Sox17") plist <- list() genes2plot2 <- genes2plot[genes2plot %in% colnames(og_expDat)] for (i in genes2plot2) { p <- eval(substitute(ggplot() + geom_point(data = as.data.frame(toBeP$epc@scores), mapping = aes(x = PC1, y = PC2, color = og_expDat[[i]])) + viridis::scale_color_viridis() + geom_segment(data = as.data.frame(toBeP$garrows), aes(x = x0, y = y0, xend = x1, yend = y1), arrow = arrow(length = unit(0.2, "cm"))) + ggtitle(i) )) plist[[i]] <- print(p) }

toBeP <- pcaVelP genes2plot <- c("Chst4", "Apln", "Nes", "Ly6c1", "Pdgfra", "Pdpn", "Adm", "Pgf", "Sox17") plist <- list() genes2plot2 <- genes2plot[genes2plot %in% colnames(og_expDat)] for (i in genes2plot2) { p <- eval(substitute(ggplot() + geom_point(data = as.data.frame(toBeP$epc@scores), mapping = aes(x = PC1, y = PC2, color = og_expDat[[i]])) + viridis::scale_color_viridis() + geom_segment(data = as.data.frame(toBeP$garrows), aes(x = x0, y = y0, xend = x1, yend = y1), arrow = arrow(length = unit(0.2, "cm"))) + ggtitle(i) )) plist[[i]] <- print(p) }

toBeP <- pcaVelP genes2plot <- c("Chst4", "Apln", "Nes", "Ly6c1", "Pdgfra", "Pdpn", "Adm", "Pgf", "Sox17") plist <- list() genes2plot2 <- genes2plot[genes2plot %in% colnames(og_expDat)] for (i in genes2plot2) { p <- eval(substitute(ggplot() + geom_point(data = as.data.frame(toBeP$epc@scores), mapping = aes(x = PC1, y = PC2, color = og_expDat[[i]])) + viridis::scale_color_viridis() + geom_segment(data = as.data.frame(toBeP$garrows), aes(x = x0, y = y0, xend = x1, yend = y1), arrow = arrow(length = unit(0.2, "cm"))) + ggtitle(i) )) plist[[i]] <- print(p) }

toBeP <- pcaVelP genes2plot <- c("Chst4", "Apln", "Nes", "Ly6c1", "Pdgfra", "Pdpn", "Adm", "Pgf", "Sox17") plist <- list() genes2plot2 <- genes2plot[genes2plot %in% colnames(og_expDat)] for (i in genes2plot2) { p <- eval(substitute(ggplot() + geom_point(data = as.data.frame(toBeP$epc@scores), mapping = aes(x = PC1, y = PC2, color = og_expDat[[i]])) + viridis::scale_color_viridis() + geom_segment(data = as.data.frame(toBeP$garrows), aes(x = x0, y = y0, xend = x1, yend = y1), arrow = arrow(length = unit(0.2, "cm"))) + ggtitle(i) )) plist[[i]] <- print(p) }

toBeP <- pcaVelP genes2plot <- c("Chst4", "Apln", "Nes", "Ly6c1", "Pdgfra", "Pdpn", "Adm", "Pgf", "Sox17") plist <- list() genes2plot2 <- genes2plot[genes2plot %in% colnames(og_expDat)] for (i in genes2plot2) { p <- eval(substitute(ggplot() + geom_point(data = as.data.frame(toBeP$epc@scores), mapping = aes(x = PC1, y = PC2, color = og_expDat[[i]])) + viridis::scale_color_viridis() + geom_segment(data = as.data.frame(toBeP$garrows), aes(x = x0, y = y0, xend = x1, yend = y1), arrow = arrow(length = unit(0.2, "cm"))) + ggtitle(i) )) plist[[i]] <- print(p) }

toBeP <- pcaVelP genes2plot <- c("Chst4", "Apln", "Nes", "Ly6c1", "Pdgfra", "Pdpn", "Adm", "Pgf", "Sox17") plist <- list() genes2plot2 <- genes2plot[genes2plot %in% colnames(og_expDat)] for (i in genes2plot2) { p <- eval(substitute(ggplot() + geom_point(data = as.data.frame(toBeP$epc@scores), mapping = aes(x = PC1, y = PC2, color = og_expDat[[i]])) + viridis::scale_color_viridis() + geom_segment(data = as.data.frame(toBeP$garrows), aes(x = x0, y = y0, xend = x1, yend = y1), arrow = arrow(length = unit(0.2, "cm"))) + ggtitle(i) )) plist[[i]] <- print(p) }

ggplot() + geom_point(data = as.data.frame(rvel.cd.exp), mapping = aes(x = Chst4_conv.nmat.norm, y = Chst4_conv.emat.norm, color = as.factor(og_expDat$og_sClustsPCA_t2X0.3_3_Y0.25_10_R0.3))) + scale_fill_brewer(palette = "Set1") + theme(legend.title = element_blank())