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| Date | Name | Thumbnail | Size | User | Description | Versions |
|---|---|---|---|---|---|---|
| 10:48, 1 December 2025 | Dendro colorbars.png (file) | 11 KB | Brb (talk | contribs) | <syntaxhighlight lang='r'> library(ComplexHeatmap) library(circlize) library(RColorBrewer) set.seed(123) # --- Example data (10 samples) --- mat <- matrix(rnorm(30), nrow = 10) rownames(mat) <- paste0("Sample", 1:10) mat[1:5, ] <- mat[1:5, ] mat[6:10, ] <- mat[6:10, ] + 2 # Cluster on samples (rows) hc <- hclust(dist(mat)) # Annotations in ORIGINAL sample order groups <- rep(c("A", "B"), each = 5) score <- seq(0, 1, length = 10) cl2 <- cutree(hc, 2) cl3 <- cutree(hc, 3) cl4 <- cutree(hc,... | 1 | |
| 17:16, 10 November 2025 | Umap-iris.png (file) | 25 KB | Brb (talk | contribs) | <syntaxhighlight lang='r'> library(umap) # Load the built-in Iris dataset data(iris) # Separate the features (variables) from the species labels iris_features <- iris[, 1:4] iris_species <- iris[, 5] # Run UMAP, reducing the 4 dimensions down to 2 # n_neighbors: Controls how UMAP balances local vs. global structure. # min_dist: Controls how tightly points are packed together. iris_umap_results <- umap(iris_features, random_state = 42) # The result is a list. The actual 2D coordinates are... | 1 | |
| 19:07, 28 October 2025 | Paletteer d.png (file) | 39 KB | Brb (talk | contribs) | <syntaxhighlight lang='r'> paletteer_d("RColorBrewer::RdBu") #<colors> #67001FFF #B2182BFF #D6604DFF #F4A582FF #FDDBC7FF #F7F7F7FF #D1E5F0FF #92C5DEFF #4393C3FF #2166ACFF #053061FF paletteer_d("ggsci::uniform_startrek") # <colors> #CC0C00FF #5C88DAFF #84BD00FF #FFCD00FF #7C878EFF #00B5E2FF #00AF66FF </syntaxhighlight> | 1 | |
| 15:12, 4 October 2025 | Massage.png (file) | 1.55 MB | Brb (talk | contribs) | 1 | ||
| 14:57, 8 September 2025 | MacSettingKeyboardShortcut.png (file) | 274 KB | Brb (talk | contribs) | 1 | ||
| 14:56, 8 September 2025 | MacSettingLiveCaption.png (file) | 271 KB | Brb (talk | contribs) | 1 | ||
| 09:17, 7 August 2025 | Heatmap-gaps.png (file) | 4 KB | Brb (talk | contribs) | <syntaxhighlight lang='r'> # 1. Prepare the data set.seed(42) mat = matrix(rnorm(30, mean = 0, sd = 1.2), nrow = 5, ncol = 6) mat[2, 1] = -2.5 mat[2, 6] = 2.5 mat[1, 2] = -1.8 mat[4, 4] = 1.8 # 2. Define the color palette library(circlize) col_fun = colorRamp2(c(-2.5, 0, 2.5), c("steelblue", "white", "darkred")) # 3. Create the heatmap object library(ComplexHeatmap) ht = Heatmap( mat, col = col_fun, cluster_rows = FALSE, cluster_columns = FALSE, show_row_names = FALSE, show_colu... | 1 | |
| 14:18, 29 July 2025 | Inkscape-heatmap.svg (file) | 7 KB | Brb (talk | contribs) | 1 | ||
| 08:16, 19 July 2025 | NemoCaja.png (file) | 182 KB | Brb (talk | contribs) | 1 | ||
| 16:25, 5 July 2025 | Cinnamon.png (file) | 290 KB | Brb (talk | contribs) | 1 | ||
| 16:18, 5 July 2025 | MATE.png (file) | 296 KB | Brb (talk | contribs) | 1 | ||
| 16:13, 5 July 2025 | GNOME.png (file) | 273 KB | Brb (talk | contribs) | 1 | ||
| 16:06, 5 July 2025 | KDE.png (file) | 325 KB | Brb (talk | contribs) | 1 | ||
| 15:52, 5 July 2025 | LXDE.png (file) | 251 KB | Brb (talk | contribs) | 1 | ||
| 15:52, 5 July 2025 | Xfce.png (file) | 274 KB | Brb (talk | contribs) | 1 | ||
| 15:50, 5 July 2025 | LXQt.png (file) | 271 KB | Brb (talk | contribs) | 1 | ||
| 14:16, 2 July 2025 | Palbarplot.png (file) | 57 KB | Brb (talk | contribs) | 1 | ||
| 08:07, 13 June 2025 | Cauchyos install.png (file) | 579 KB | Brb (talk | contribs) | 1 | ||
| 12:44, 20 May 2025 | Combat DE mod.png (file) | 149 KB | Brb (talk | contribs) | Demonstrate the importance of the 'mod' parameter in sva::ComBat() <syntaxhighlight lang='r'> library(sva) library(limma) library(ggplot2) library(tidyr) set.seed(42) n_genes <- 100 n_samples <- 20 # Group: 10 Case and 10 Control — spread across batches group <- sample(rep(c("Control", "Case"), each=10)) # now randomized batch <- rep(c(1, 2), each=10) # Simulate expression data expr <- matrix(rnorm(n_genes * n_samples, mean=5, sd=1), nrow=n_genes) # Add true signal to 10 genes for Case... | 1 | |
| 20:47, 17 May 2025 | Twoway.png (file) | 76 KB | Brb (talk | contribs) | <syntaxhighlight lang='r'> png("~/Downloads/twoway.png", width=8, height=6, units="in",res=300) par(mar = c(8, 4, 4, 2)) boxplot(y ~ treatment * timepoint, data = df, col = c("skyblue", "lightgreen", "lightpink"), main = "Plant Growth by Treatment and Timepoint", xlab = "", ylab = "Plant Height", xaxt = "n") # Add rotated x-axis labels labels <- levels(interaction(df$treatment, df$timepoint)) axis(1, at = 1:length(labels), labels = FALSE) # Add ticks without labels... | 1 | |
| 12:33, 17 April 2025 | Groupjitterboxplot.png (file) | 247 KB | Brb (talk | contribs) | <syntaxhighlight lang='r'> library(ggplot2) library(dplyr) # Create a sample dataset with large sample size set.seed(42) n_per_group <- 500 # 500 samples per group and category combination (2000 total) data <- data.frame( A = rep(c("Group1", "Group2"), each = n_per_group * 2), B = c(rnorm(n_per_group, 10, 2), rnorm(n_per_group, 8, 1.5), # Group1: Category1, Category2 rnorm(n_per_group, 12, 2.5), rnorm(n_per_group, 14, 2)), # Group2: Category1, Category2 F = rep(rep(c("Categ... | 1 | |
| 16:37, 31 January 2025 | Heatmapcolparam.png (file) | 27 KB | Brb (talk | contribs) | <syntaxhighlight lang='r'> library(ComplexHeatmap) library(circlize) # Create a sample 5x5 matrix with values from -4 to 4 set.seed(123) # for reproducibility example_matrix <- matrix(runif(25, -4, 4), nrow = 5) colnames(example_matrix) <- paste0("Col", 1:5) rownames(example_matrix) <- paste0("Row", 1:5) # Define the color function that truncates at -2 and 2 col_fun <- colorRamp2(c(-2, 0, 2), c("blue", "white", "red")) # Plot the heatmap without truncating the data heatmap1 <- Heatmap(exa... | 1 | |
| 18:37, 11 January 2025 | Scale color identity.png (file) | 24 KB | Brb (talk | contribs) | 2 | ||
| 20:27, 26 December 2024 | Hmscaled.png (file) | 61 KB | Brb (talk | contribs) | 2 |