Command lines 1: wget http://chibba.pgml.uga.edu/mcscan2/MCScanX.zip unzip MCScanX.zip Command lines 2: cd MCScanX make Command lines 3: sed -i '1s/^/#include \n/' msa.h sed -i '1s/^/#include \n/' dissect_multiple_alignment.h sed -i '1s/^/#include \n/' detect_collinear_tandem_arrays.h Command lines 4: wget http://genomes.cribi.unipd.it/DATA/V1/FASTA/V1_prot.fa wget http://genomes.cribi.unipd.it/DATA/GFF/V1.tar.gz Command lines 5: tar -zxvf V1.tar.gz cat ./V1/*.gff3 >v1.gff Command lines 6: makeblastdb -in V1_prot.fa -dbtype prot Command lines 7: blastall –i fasta_file –d fasta_file –p blastp –e1e-10 –b 5 –v 5 –m 8 –o vitis.blast Command lines 8: wget "https://sourceforge.net/projects/jove-ariani-etal/files/parseMSCanXgff.pl" Command lines 9: perl parseMSCanXgff.pl v1.gff vitis.gff Command lines 10: ./MCScanX vitis ./mcscaxOutput Command lines 11: ./duplicate_gene_classifier vitis Command lines 12: perl origin_enrichment_analysis.pl –I gene_family_file –d vitis.gene_type –o outputFile.txt Command lines 13: >design <- matrix(c(1,0,1,0,1,0,0,1,0,1,0,1), nrow=6, ncol=2, byrow = TRUE) >dimnames(design) <- list(c("GSM1272068", "GSM1272069", "GSM1272070", "GSM1272071", "GSM1272072", "GSM1272073"), c("Con", "Inf")) >design ## Con Infected ##GSM1272068 1 0 ##GSM1272069 1 0 ##GSM1272070 1 0 ##GSM1272071 0 1 ##GSM1272072 0 1 ##GSM1272073 0 1 Command lines 14: > design <- data.frame(row.names= c("SRX966735", "SRX966740", "SRX966742", "SRX1008217", "SRX1010114", "SRX1010115"), condition= as.factor(c(rep("Con",3), rep("Shade",3)))) >design ## condition ##SRX966735 Con ##SRX966740 Con ##SRX966742 Con ##SRX1008217 Shade ##SRX1010114 Shade ##SRX1010115 Shade Command lines 15: >eset <- read.table("expr.mat.txt",sep="\t",header=TRUE,row.names=1) ##From section 7.1 >fit <- lmFit(eset, design) >cont.matrix <- makeContrasts(InfvsCon=Infected-Con, levels=design) >fit <- contrasts.fit(fit, cont.matrix) >fit <- eBayes(fit) >res=topTable(fit, adjust="BH", number=Inf) >write.table(res, "DE.results.txt", sep="\t") Command lines 16: >eset <- read.table(f, sep="\t", header=TRUE, row.names=1) >dds$condition <- factor(dds$condition,levels=c("Con","Shade")) >dds1 <- DESeq(dds) >res <- results(dds1, addMLE=T) >write.table(res, "DE.results.txt", sep= "\t") Command lines 17: comp <- read.table("biotic.compedia.txt",sep="\t",header=TRUE,row.names=1) cn <- read.table("biotic.compedia.notes.txt",sep="\t",header=TRUE) d_comp <- dist(comp) hc_comp <- hclust(d_comp, method = "complete") dend <- as.dendrogram(hc_comp) breaks <- c(seq(-4,-0.51,length=20),seq(-0.5,0.5,length=10),seq(0.51,4,length=20)) my_palette <- colorRampPalette(c("lightskyblue","white", "red"))(n=49) gplots::heatmap.2(as.matrix(comp), srtCol = 90, dendrogram = "row", Rowv = dend, Colv = "NA", trace="none", col = my_palette, sepwidth=c(0.01,0.01), sepcolor="black", colsep=1:ncol(comp), rowsep=1:nrow(comp), breaks=breaks, cellnote=cn) Command lines 18: wget "https://sourceforge.net/projects/jove-ariani-etal/files/Exp_ATL.txt" Command lines 19: wget "https://sourceforge.net/projects/jove-ariani-etal/files/PC_Coexpression.pl" Command lines 20: perl PC_Coexpression.pl Exp_ATL.txt Command lines 21: similarityTable <- read.table("similarityTable.txt", header = F) coexpressionTable <- read.table("coexpressionTable.txt", header = F) similarityDist <- as.dist(similarityTable) coexpressionDist <- as.dist(coexpressionTable) mantel.rtest(m1 = similarityDist, m2 = coexpressionDist, nrepet = 1000) Example output 1 ## Alignment 0: score=1069.0 e_value=8.2e-78 N=25 vv1&vv14 plus 0- 0: VIT_01s0026g01080.t01 VIT_14s0066g02240.t01 0 0- 1: VIT_01s0026g01290.t01 VIT_14s0066g02440.t01 0 0- 2: VIT_01s0026g01430.t01 VIT_14s0066g02470.t01 8e-65 0- 3: VIT_01s0026g01460.t01 VIT_14s0066g02560.t01 3e-49 0- 4: VIT_01s0026g01490.t01 VIT_14s0066g02590.t01 0 0- 5: VIT_01s0026g01650.t01 VIT_14s0108g00010.t01 3e-166