### R code from vignette source 'GOsummaries-basics.Rnw' ################################################### ### code chunk number 1: style-Sweave ################################################### BiocStyle::latex() ################################################### ### code chunk number 2: myCodeBlock ################################################### library(GOsummaries, quietly=TRUE) library(vegan, quietly=TRUE) library(ggplot2, quietly=TRUE) ################################################### ### code chunk number 3: example1 ################################################### # Define gene lists genes1 = c("203485_at", "209469_at", "209470_s_at", "203999_at", "205358_at", "203130_s_at", "210222_s_at", "202508_s_at", "203001_s_at", "207957_s_at", "203540_at", "203000_at", "219619_at","221805_at", "214046_at", "213135_at", "203889_at", "209990_s_at", "210016_at", "202507_s_at","209839_at", "204953_at", "209167_at", "209685_s_at", "211276_at", "202391_at", "205591_at","201313_at") genes2 = c("201890_at", "202503_s_at", "204170_s_at", "201291_s_at", "202589_at", "218499_at", "209773_s_at", "204026_s_at", "216237_s_at", "202546_at", "218883_s_at", "204285_s_at", "208659_at", "201292_at", "201664_at") gl = list(List = list(genes1, genes2)) # Two lists per component # Construct gosummaries objects gs = gosummaries(gl) plot(gs, fontsize = 8, filename = "figure2.pdf") ################################################### ### code chunk number 4: Example2 ################################################### data(tissue_example) # Filter genes and perform k-means sd = apply(tissue_example$exp, 1, sd) exp2 = tissue_example$exp[sd > 0.75,] exp2 = exp2 - apply(exp2, 1, mean) kmr = kmeans(exp2, centers = 6, iter.max = 100) # Create gosummaries object exp2[1:6, 1:5] head(tissue_example$annot) gs_kmeans = gosummaries(kmr, components = 1:2, exp = exp2, annotation = tissue_example$annot) plot(gs_kmeans, fontsize = 8, classes = "Tissue", filename = "figure3.pdf") ################################################### ### code chunk number 5: Example3 ################################################### cust = function(p, par){ p = p + scale_fill_brewer(par$classes, type = "qual", palette = 2) return(p) } plot(gs_kmeans, panel_plot = panel_violin, panel_customize = cust, classes = "Tissue", components = 1:2, filename = "ex3.pdf") ################################################### ### code chunk number 6: ExampleUserSupplied ################################################### wcd1 = data.frame(Term = c("KLF1", "KLF2", "POU5F1"), Score = c(0.05, 0.001, 0.0001)) wcd2 = data.frame(Term = c("CD8", "CD248", "CCL5"), Score = c(0.02, 0.005, 0.00001)) ################################################### ### code chunk number 7: ExampleUserSupplied2 ################################################### gs = gosummaries(wc_data = list(Results1 = wcd1, Results2 = wcd2)) plot(gs, filename = "figure5.pdf") ################################################### ### code chunk number 8: ExampleUserSupplied3 ################################################### # To get two word clouds per block use neted lists gs = gosummaries(wc_data = list(Results = list(wcd1, wcd2))) plot(gs, filename = "figure6.pdf") ################################################### ### code chunk number 9: ExampleMetagenomic ################################################### data(metagenomic_example) # Run Principal Coordinate Analysis on Bray-Curtis dissimilarity matrix pcoa = cmdscale(vegdist(t(metagenomic_example$otu), "bray"), k = 3) # By turning off the GO analysis we can show the names of taxa gs = gosummaries(pcoa, metagenomic_example$otu, metagenomic_example$annot, show_genes = T, gconvert_target = NULL, n_genes = 30) plot(gs, class = "BodySite", fontsize = 8, file = "figure7.pdf") ################################################### ### code chunk number 10: SessionInfo ################################################### sessionInfo()