Jan Broder Engler
LightNews LightNews
banner
jbengler.de
Jan Broder Engler
@jbengler.de
1.4K followers 660 following 460 posts
Scientist and software developer. Creator of tidyplots.org. Website jbengler.de.
Posts Replies Media Videos
Pinned
jbengler.de
Jan Broder Engler @jbengler.de · Dec 6
Hey educators, tidyplots.org is great for teaching students data visualization because it is

🕊️ Free and open-source
🚀 Easy, intuitive and fast
💾 Loaded with demo datasets
🏆 Embracing best practices
🌈 Beautiful

#rstats #phd #dataviz #education
jbengler.de
This is how you can visualize gene expression data in #tidyheatmaps 🤩

jbengler.github.io/tidyheatmaps/

#rstats #dataviz #phd
library(tidyheatmaps) tidyheatmap(df = data_exprs, rows = external_gene_name, columns = sample, values = expression, scale = "row", annotation_col = c(sample_type, condition, group), annotation_row = c(is_immune_gene, direction), gaps_row = direction, gaps_col = group )
November 21, 2025 at 5:16 PM
jbengler.de
This is how you can change the color scheme in #tidyplots 🌈

#rstats #dataviz #phd
library(tidyplots) spendings |> tidyplot(x = category, y = amount, color = category) |> add_sum_bar() |> adjust_x_axis(rotate_labels = TRUE) |> sort_x_axis_levels() |> adjust_colors(new_colors = colors_discrete_candy)
November 20, 2025 at 5:25 PM
jbengler.de
This is how you can guide attention in #tidyplots 🎯

#rstats #dataviz #phd
library(tidyplots) spendings |> tidyplot(x = category, y = amount, color = category) |> add_sum_bar() |> adjust_x_axis(rotate_labels = TRUE) |> sort_x_axis_levels() |> adjust_colors(new_colors = c("Health" = "#ff3b30"), na.value = "lightgrey")
November 19, 2025 at 2:49 PM
jbengler.de
This is how you can add data values in #tidyplots 🏆

#rstats #dataviz #phd
library(tidyplots) spendings |> tidyplot(x = category, y = amount, color = category) |> add_sum_bar(alpha = 0.2) |> add_sum_dash() |> add_sum_value(accuracy = 1, color = "black") |> adjust_x_axis(rotate_labels = TRUE) |> sort_x_axis_levels()
November 18, 2025 at 7:45 PM
jbengler.de
This is how you can sort axis levels in #tidyplots 🤩

#rstats #dataviz #phd
library(tidyplots) spendings |> tidyplot(x = category, y = amount, color = category) |> add_sum_bar() |> adjust_x_axis(rotate_labels = TRUE) |> sort_x_axis_levels()
November 17, 2025 at 6:17 PM
jbengler.de
This is how you can rename axis levels in #tidyplots 🎉

#rstats #dataviz #phd
library(tidyplots) study |> tidyplot(x = treatment, y = score, color = treatment) |> add_violin() |> add_data_points_beeswarm(white_border = TRUE) |> rename_x_axis_levels(new_names = c( "A" = "Dog", "B" = "Cat", "C" = "Hamster", "D" = "Dinosaur"))
November 14, 2025 at 5:11 PM
jbengler.de
This is how you can reorder axis levels in #tidyplots 🚀

#rstats #dataviz #phd
library(tidyplots) study |> tidyplot(x = treatment, y = score, color = treatment) |> add_violin() |> add_data_points_beeswarm(white_border = TRUE) |> reorder_x_axis_levels("C", "D", "A", "B")
November 13, 2025 at 11:12 PM
jbengler.de
In its first year tidyplots.org has become the go-to data viz for many life science researchers, got 620+ stars on Github, ~30K CRAN downloads, and 11 citations. Thank you for using, sharing, citing, and feedback! There is more to come 🤩

#rstats #dataviz #phd
November 8, 2025 at 9:24 AM
jbengler.de
This is how you can add data and summary statistics to #tidyplots 🤩

#rstats #dataviz #phd
October 21, 2025 at 4:11 PM
jbengler.de
This is how you can save intermediate stages of #tidyplots 🦊

#rstats #dataviz #phd
library(tidyplots) study |> tidyplot(x = treatment, y = score, color = treatment) |> add_mean_dash() |> save_plot("stage_1.pdf") |> add_sem_errorbar() |> save_plot("stage_2.pdf") |> add_data_points_beeswarm() |> save_plot("stage_3.pdf")
October 16, 2025 at 4:45 PM
jbengler.de
This is how you can visualize time course data in #tidyplots ⏱️

#rstats #dataviz #phd
library(tidyplots) time_course |> tidyplot(x = day, y = score, color = treatment) |> add_mean_line() |> add_mean_dot() |> add_sem_ribbon()
October 14, 2025 at 3:58 PM
jbengler.de
Thank you for citing #tidyplots 🙏

Marcel S Woo et al. Glia inflammation and cell death pathways drive disease progression in preclinical and early AD. EMBO Molecular Medicine (2025).

doi.org/10.1038/s443...

#rstats #dataviz #phd
Glia inflammation and cell death pathways drive disease progression in preclinical and early AD | EMBO Molecular Medicine
imageimageGlia activation, inflammation, cell death pathways and neuronal pathologies are associated with disease progression in preclinical AD. Activation of glia cells and cell death pathways maintain a vicious cycle of neuroinflammation that ...
doi.org
October 14, 2025 at 3:03 PM
jbengler.de
This is how to get started with #tidyplots 🚀

tidyplots.org/getstarted

#rstats #dataviz #phd
October 10, 2025 at 4:24 PM
jbengler.de
This is how you can generate lollipop charts in #tidyplots 🍭

#rstats #dataviz #phd
library(tidyplots) spendings |> tidyplot(x = amount, y = category, color = category) |> add_sum_bar(width = 0.05) |> add_sum_dot()
October 10, 2025 at 4:21 PM
jbengler.de
This is how you can set a default style in #tidyplots 🎨

jbengler.github.io/tidyplots/re...

#rstats #dataviz #phd
library(tidyplots) # Define style my_style <- function(x) x |> adjust_colors(colors_discrete_candy) |> adjust_font(family = "mono") |> adjust_size(height = 30) # Set global options tidyplots_options(my_style = my_style) study |> tidyplot(x = group, y = score, color = dose) |> add_mean_bar() # Reset global options tidyplots_options()
October 9, 2025 at 3:48 PM
jbengler.de
This is how you can add normal data ellipses in #tidyplots 🐣

#rstats #dataviz #phd
library(tidyplots) pca |> tidyplot(x = pc1, y = pc2, color = group) |> add_data_points() |> add_ellipse()
October 7, 2025 at 2:37 PM
jbengler.de
Being free and open-source, this is how you can support #tidyplots ❤️

tidyplots.org
github.com/jbengler/tid...

#rstats #dataviz #phd
October 7, 2025 at 2:34 PM
jbengler.de
This is how you can preview a subset of the dataset in #tidyplots 🔎

#rstats #dataviz #phd
library(tidyplots) gene_expression |> tidyplot(x = group, y = expression, color = group) |> add_violin() |> add_data_points_beeswarm(white_border = TRUE) |> view_plot(data = filter_rows(external_gene_name == "Apol6"), title = "Apol6")
October 6, 2025 at 6:12 PM
jbengler.de
This is how you can test selected comparisons in #tidyplots ✅

#rstats #dataviz #phd
library(tidyplots) study |> tidyplot(x = treatment, y = score, color = treatment) |> add_mean_dash() |> add_sem_errorbar() |> add_data_points() |> add_test_pvalue(comparisons = list(c(1,3),c(2,4)))
October 3, 2025 at 6:22 PM
jbengler.de
This is how you can do paired testing in #tidyplots 🍒

#rstats #dataviz #phd
library(tidyplots) x <- c(2.3, 4.5, 6.3, 3.4, 7.8, 6.7) df <- data.frame( x = c(x, x + c(0.8, 0.75)), group = paste0("g", rep(c(1, 2), each = 6)), batch = paste0("b", c(1:6, 1:6)), shuffle = paste0("c", c(1:6, 6:1)) ) df |> tidyplot(group, x, color = group) |> add_boxplot() |> add_data_points() |> add_test_pvalue(paired_by = batch) |> add_line(group = batch, color = "black")
October 2, 2025 at 6:54 PM
jbengler.de
Thank you for citing #tidyplots 🙏

Marcel S. Woo et al. The immunoproteasome disturbs neuronal metabolism and drives neurodegeneration in multiple sclerosis. Cell (2025).

www.cell.com/cell/fulltex...

#rstats #dataviz #phd
The immunoproteasome disturbs neuronal metabolism and drives neurodegeneration in multiple sclerosis
Neuronal proteasomal dysfunction is a hallmark of neuroinflammatory and neurodegenerative diseases. This study reveals that the interferon-induced immunoproteasome drastically decreases proteasomal ac...
www.cell.com
October 2, 2025 at 6:49 PM
jbengler.de
This is how you can adjust the plot size in #tidyplots 🔥

All measures are in mm.

#rstats #dataviz #phd
library(tidyplots) study |> tidyplot(x = group, y = score, color = group) |> add_median_bar(alpha = 0.3) |> add_median_dash() |> add_data_points_beeswarm(white_border = TRUE) |> remove_x_axis_labels() |> adjust_size(width = 20, height = 50)
October 1, 2025 at 4:05 PM
jbengler.de
Thank you for citing #tidyplots 🙏

Jakub Idkowiak et al. Best practices and tools in R and Python for statistical processing and visualization of lipidomics and metabolomics data. Nature Communications (2025).

doi.org/10.1038/s414...

#rstats #dataviz #phd
Best practices and tools in R and Python for statistical processing and visualization of lipidomics and metabolomics data - Nature Communications
Mass spectrometry-based lipidomics and metabolomics generate large, complex datasets requiring effective analysis. Here, authors review key statistical and visualization methods alongside widely used R and Python tools, and provide a GitBook with step-by-step code for accessible, reproducible data analysis.
doi.org
October 1, 2025 at 3:05 PM
jbengler.de
This is how you can adjust colors in #tidyplots 🌈

#rstats #dataviz #phd
library(tidyplots) library(patchwork) p1 <- energy |> tidyplot(x = year, y = energy, color = energy_type) |> add_barstack_absolute() |> adjust_colors(colors_discrete_apple) p2 <- p1 |> adjust_colors(colors_discrete_metro) wrap_plots(p1, p2, ncol = 1)
September 30, 2025 at 3:49 PM
jbengler.de
This is how you can do stacked bar charts in #tidyplots 🐝

#rstats #dataviz #phd
library(tidyplots) energy |> tidyplot(x = year, y = energy, color = energy_type) |> add_barstack_absolute()
September 29, 2025 at 5:34 PM