Upload log

Below is a list of the most recent file uploads. See the gallery of new files for a more visual overview.

• 10:10, 11 February 2023 Brb talk contribs uploaded File:ClassPredictionOptions.PNG
• 10:08, 11 February 2023 Brb talk contribs uploaded File:ClassPrediction.PNG
• 20:01, 28 January 2023 Brb talk contribs uploaded File:Pca factoextra.png
• 19:34, 28 January 2023 Brb talk contribs uploaded File:Pca autoplot.png
• 19:34, 28 January 2023 Brb talk contribs uploaded File:Pca directly.png
• 09:21, 25 January 2023 Brb talk contribs uploaded File:VscodeEnergy.png
• 21:26, 14 January 2023 Brb talk contribs uploaded File:RbdGeom.png (<pre> require(ggplot2) aggregate( .~ treatment +block,FUN=median, data = data) |> ggplot(aes(treatment, yield)) + geom_line(aes(group = block, color = block), linewidth = 1.2) + geom_point(aes(color = block), shape = 15, size=2.6) </pre>)
• 20:51, 14 January 2023 Brb talk contribs uploaded File:RbdBlock.png (<pre> set.seed(1234) block <- as.factor(rep(1:5, each=6)) treatment <- rep(c("A","B","C"),5) block_shift <- rnorm(5, mean = 0, sd = 2) treatment_shift <- c(A=0, B=4, C=2) random_effect <- rnorm(30, mean = 0, sd = 1) yield <- rnorm(30, mean = 10, sd = 2) + treatment_shift[as.integer(factor(treatment))] + block_shift[as.numeric(block)] + random_effect data <- data.frame(block, treatment, yield) summary(fm1 <- aov(yield ~ treatment + block, data = data)) # Df Sum Sq Mean Sq...)
• 20:50, 14 January 2023 Brb talk contribs uploaded File:RbdTreat.png (<pre> set.seed(1234) block <- as.factor(rep(1:5, each=6)) treatment <- rep(c("A","B","C"),5) block_shift <- rnorm(5, mean = 0, sd = 2) treatment_shift <- c(A=0, B=4, C=2) random_effect <- rnorm(30, mean = 0, sd = 1) yield <- rnorm(30, mean = 10, sd = 2) + treatment_shift[as.integer(factor(treatment))] + block_shift[as.numeric(block)] + random_effect data <- data.frame(block, treatment, yield) summary(fm1 <- aov(yield ~ treatment + block, data = data)) # Df Sum Sq Mean Sq...)
• 11:18, 12 January 2023 Brb talk contribs uploaded File:GseaTable2.png (An example of a plot from 10 non-enriched pathways. <pre> data(examplePathways) data(exampleRanks) fgseaRes <- fgsea(examplePathways, exampleRanks, nperm=1000, minSize=15, maxSize=100) fgseaRes[order(pval, decreasing = T),][1:10, c('NES', 'pval')] # NES pval # 1: -0.4050950 1.0000000 # 2: -0.4050950 1.0000000 # 3: -0.4966664 0.9932584 # 4: 0.4804114 0.9870610 # 5: 0.4804114 0.9870610 # 6: 0.4804114 0.9870610 # 7: 0.4804114 0.9870610 # 8: 0.4955139 0.9854...)
• 11:01, 12 January 2023 Brb talk contribs uploaded File:GseaTable.png (<pre> data(examplePathways) data(exampleRanks) fgseaRes <- fgsea(examplePathways, exampleRanks, nperm=1000, minSize=15, maxSize=100) # I pick 5 pathways with + NES and 5 pathways with - NES. fgseaRes[order(pval), ][62:71, c('pathway', 'NES')] # pathway NES # 1: 5992282_ECM_proteoglycans 1.984081 # 2: 5992219_Regulation_of_cholesterol_biosynthesis_by_SREBP_SREBF_ 1.95...)
• 11:15, 8 January 2023 Brb talk contribs uploaded File:Reorder.dendrogram.png (<pre> set.seed(123) x <- rnorm(20) hc <- hclust(dist(x)) dd <- as.dendrogram(hc) par(mfrow=c(3, 1)) plot(dd, main = "random dendrogram 'dd'") # not the same as reorder(dd, 1:20) plot(reorder(dd, 20:1), main = 'reorder(dd, 20:1, sum)') plot(reorder(dd, 20:1, mean), main = 'reorder(dd, 20:1, mean)') </pre>)
• 20:37, 7 January 2023 Brb talk contribs uploaded File:ComplexHeatmap2.png (<syntaxhighlight lang="rsplus"> # Simulate data library(ComplexHeatmap) ng <- 30; ns <- 20 set.seed(1) mat <- matrix(rnorm(ng*ns), nr=ng, nc=ns) colnames(mat) <- 1:ns rownames(mat) <- 1:ng # color bar on RHS ind_e <- 1:round(ng/3) ind_m <- (1+round(ng/3)):ng epimes <- rep(c("epi", "mes"), c(length(ind_e), length(ind_m))) row_ha <- rowAnnotation(epimes = epimes, col = list(epimes = c("epi" = "orange", "mes" = "darkgreen"))) # color bar on Top tumortype <- rep(c("carcinoma", "sarcoma"...)
• 11:37, 6 January 2023 Brb talk contribs uploaded File:Fgsea3plots.png (<pre> par(mfrow=c(1,3)) with(fgseaRes, plot(abs(ES), pval)) with(fgseaRes, plot(abs(NES), pval)) with(fgseaRes, plot(ES, NES)) </pre>)
• 13:58, 31 December 2022 Brb talk contribs uploaded File:Filebrowser.png
• 19:07, 25 December 2022 Brb talk contribs uploaded File:DisableDropbox4pm.png
• 14:40, 15 December 2022 Brb talk contribs uploaded File:Geom smooth ex.png (<pre> library(dplyr) #group the data by cyl and create the plots mpg %>% group_by(cyl) %>% ggplot(aes(x=displ, y=hwy, color=factor(cyl))) + geom_point() + geom_smooth(method = "lm", se = FALSE) + theme(legend.position="none") </pre>)
• 14:14, 15 December 2022 Brb talk contribs uploaded File:Geom bar4.png (<pre> ggplot(mpg, aes(x = class)) + geom_vline(xintercept = mpg$class, color = "grey", linetype = "dashed", size = 1) + geom_bar() + theme_classic() + coord_flip() </pre>)
• 14:08, 15 December 2022 Brb talk contribs uploaded File:Geom bar3.png (<pre> ggplot(mpg, aes(x=manufacturer)) + geom_bar() + theme(panel.grid.major.x = element_blank(), panel.grid.minor = element_blank()) </pre>)
• 13:41, 15 December 2022 Brb talk contribs uploaded File:Geom bar2.png (<pre> library(ggplot2) library(scales) library(patchwork) dtf <- data.frame(x = c("ETB", "PMA", "PER", "KON", "TRA", "DDR", "BUM", "MAT", "HED", "EXP"), y = c(.02, .11, -.01, -.03, -.03, .02, .1, -.01, -.02, 0.06)) set.seed(1) dtf2 <- data.frame(x = dtf[, 1], y = sample(dtf[, 2])) g1 <- ggplot(dtf, aes(x, y)) + geom_bar(stat = "identity", fill = "#F8767D") + geom_text(aes(label = paste0(y * 100, "%"), hjust = ifelse(y >= 0, 0, 1))) +...)
• 13:39, 15 December 2022 Brb talk contribs uploaded File:Geom bar1.png (<pre> library(ggplot2) library(scales) library(patchwork) dtf <- data.frame(x = c("ETB", "PMA", "PER", "KON", "TRA", "DDR", "BUM", "MAT", "HED", "EXP"), y = c(.02, .11, -.01, -.03, -.03, .02, .1, -.01, -.02, 0.06)) set.seed(1) dtf2 <- data.frame(x = dtf[, 1], y = sample(dtf[, 2])) g1 <- ggplot(dtf, aes(x, y)) + geom_bar(stat = "identity", aes(fill = x)) + geom_text(aes(label = paste0(y * 100, "%"), hjust = ifelse(y >= 0,...)
• 17:00, 5 December 2022 Brb talk contribs uploaded File:GpartedinfoSanDisk.png
• 14:55, 29 October 2022 Brb talk contribs uploaded File:ExampleRanks.png (<pre> plot(exampleRanks) </pre>)
• 14:39, 29 October 2022 Brb talk contribs uploaded File:FgseaPlotSmallm.png
• 14:15, 27 October 2022 Brb talk contribs uploaded File:DHdialog2.png
• 14:15, 27 October 2022 Brb talk contribs uploaded File:DHdialog1.png
• 08:46, 27 October 2022 Brb talk contribs uploaded File:HC single.png
• 09:48, 20 October 2022 Brb talk contribs uploaded File:1NN better NC.png
• 16:26, 19 October 2022 Brb talk contribs uploaded File:NC better kNN.png (The green color is a new observation (Sensitive). By using the kNN method, it will be assigned to Resistant b/c it is closer to the Resistant group. However, using the NC, the distance of it to the Resistant group centroid is 8.42 which is larger than the distance of it to the Sensitive groups centroid 7.31. So NC classified it to Sensitive. Color annotation: green=LOO obs, black=centroid in each class.)
• 10:03, 12 October 2022 Brb talk contribs uploaded File:Foldchangefilter.png (<pre> LFC <- log2(1.5) x <- c(0, 0, 0, 0, 0, 0, 0, 0, 3.22, 0, 0, 0, 8.09, 0, 0.65, 0, 0, 0, 0, 0, 3.38, 0, 5.63, 7.46, 0, 0, 4.38, 0) plot(x, y = 1:28, xlab="log2 intensity", ylab="samples") abline(v=LFC, lty="dashed") axis(side=3,at=LFC, labels="LFC", tick=FALSE, line=0) </pre>)
• 15:39, 11 October 2022 Brb talk contribs uploaded File:Cvglmnetplot.png (<pre> n <- 100 set.seed(1) x1 <- rnorm(n) e <- rnorm(n)*.01 y <- x1 + e x4 <- x fit <- cv.glmnet(x=cbind(x1, x4, matrix(rnorm(n*10), nr=n)), y=y) plot (fit) </pre>)
• 13:12, 6 October 2022 Brb talk contribs uploaded File:Greedypairs.png
• 10:11, 6 October 2022 Brb talk contribs uploaded a new version of File:Barplot base.png
• 10:06, 6 October 2022 Brb talk contribs uploaded File:Barplot ggplot2.png
• 10:06, 6 October 2022 Brb talk contribs uploaded File:Barplot base.png
• 10:50, 30 August 2022 Brb talk contribs uploaded File:Geomcolviridis.png (Modify the example from https://datavizpyr.com/re-ordering-bars-in-barplot-in-r/ to allow filled colors and facet. <pre> library(tidyverse) library(gapminder) library(viridis) theme_set(theme_bw(base_size=16)) pop_df <- gapminder %>% filter(year==2007)%>% group_by(continent) %>% summarize(pop_in_millions=sum(pop)/1e06) pop_df2 <- tibble(class=rbinom(nrow(pop_df), 1, .5), pop_df) pop_df2 <- pop_df2 |> mutate(pop_in_millions = pop_in_millions-1900) pop_df2 %>% ggplot(aes...)
• 09:31, 30 August 2022 Brb talk contribs uploaded File:ViridisDefault.png (<pre> library(viridis) n = 200 image( 1:n, 1, as.matrix(1:n), col = viridis(n, option = "D"), xlab = "viridis n", ylab = "", xaxt = "n", yaxt = "n", bty = "n" ) </pre>)
• 09:08, 30 August 2022 Brb talk contribs uploaded File:ScaleFillViridisDiscrete.png (See https://r-graph-gallery.com/79-levelplot-with-ggplot2.html <pre> library(ggplot2) # library(hrbrthemes) # Dummy data x <- LETTERS[1:20] y <- paste0("var", seq(1,20)) data <- expand.grid(X=x, Y=y) data$Z <- runif(400, 0, 5) library(viridis) ggplot(data, aes(X, Y, fill= Z)) + geom_tile() + scale_fill_viridis(discrete=FALSE) </pre>)
• 13:19, 29 August 2022 Brb talk contribs uploaded File:Rbiomirgs barall.png
• 13:17, 29 August 2022 Brb talk contribs uploaded File:Rbiomirgs bar.png
• 13:17, 29 August 2022 Brb talk contribs uploaded File:Rbiomirgs volcano.png
• 06:08, 27 August 2022 Brb talk contribs uploaded File:FgseaPlotTop.png
• 05:34, 27 August 2022 Brb talk contribs uploaded File:FgseaPlotSmall2.png
• 05:34, 27 August 2022 Brb talk contribs uploaded File:FgseaPlotSmall.png
• 05:33, 27 August 2022 Brb talk contribs uploaded File:FgseaPlot.png
• 14:02, 23 August 2022 Brb talk contribs uploaded File:ComplexHeatmap1.png (<pre> library(ComplexHeatmap) set.seed(123) ng <- 10; n <- 10 mat = matrix(rnorm(ng * n), n) rownames(mat) = paste0("R", 1:ng) colnames(mat) = paste0("C", 1:n) bin <- sample(c("resistant", "sensitive"), n, replace = TRUE) tgi <- runif(n) # sort the columns by tgi ord <- order(tgi) col_fun = circlize::colorRamp2(range(tgi), c("#DEEBF7", "#084594")) column_ha = HeatmapAnnotation(tgi = tgi[ord], bin = bin[ord], col = list(tgi = col_fun,...)
• 13:19, 22 August 2022 Brb talk contribs uploaded File:Doubledip.png (<pre> ng <- 1000 # number of genes ns <- 100 # number of samples k <- 2 # number of groups alpha <- .001 # cutoff of selecting sig genes set.seed(1) x = matrix(rnorm(ng * ns), nr= ns) # samples x features hc = hclust(dist(x)) plot(hc) grp = cutree(hc, k=k) # vector of group membership ex <- t(x) r1 <- genefilter::rowttests(ex, factor(grp)) sum(r1$p.value < alpha) # 2 hist(r1$p.value) i <- which(r1$p.value < alpha) i1 <- i[1] ; i2 <- i[2] plot(x[, i1], x[, i2], col = grp, pch= 16, cex=1...)
• 09:21, 10 August 2022 Brb talk contribs uploaded File:Ruspini.png (library(cluster) # ruspini is 75 x 2 data(ruspini) hc <- hclust(dist(ruspini), "ave"); plot(hc) # si <- silhouette(groups, dist(ruspini)) # plot(si, main = paste("k = ", 4)) op <- par(mfrow= c(3,2), oma= c(0,0, 3, 0), mgp= c(1.6,.8,0), mar= .1+c(4,2,2,2)) plot(hc) for(k in 2:6) { groups<- cutree(hc, k=k) si <- silhouette(groups, dist(ruspini)) plot(si, main = paste("k = ", k)) } par(op))
• 18:55, 23 June 2022 Brb talk contribs uploaded File:Tidyheatmap.png
• 14:22, 21 June 2022 Brb talk contribs uploaded File:BatchqcPCA.png