From fungal confrontation photographs to matched-control results.
FunMel measures the colour, shape and image-darkness profiles of approximately round Zymoseptoria tritici colonies around another fungus. It separates target colonies from central fungal tissue and connected hyphal growth, preserves image provenance and custom metadata, and compares treatments with their own set controls.
Get started · Real 14-day tutorial · All function examples
Install
install.packages("remotes")
remotes::install_github("mghotbi/FunMel")Restart R before loading an updated package. R >= 4.1 and source-compilation tools are required: Xcode Command Line Tools on macOS, matching Rtools on Windows, or R development tools and ImageMagick development libraries on Linux. For installed tutorials, use build_vignettes=TRUE during installation.
Quick start with your photographs
The ZIP is an input file; the project is a separate output folder. Replace these paths with your own. This block reopens a recognized project and reads saved measurements; otherwise it prepares and measures a new project.
library(FunMel)
photo_zip <- path.expand("~/Desktop/photos_14_days.zip")
project_dir <- path.expand("~/Desktop/My_FunMel_project")
if (file.exists(file.path(project_dir, "project.rds"))) {
project <- load_experiment(project_dir)
} else {
project <- prepare_experiment(input=photo_zip, project_dir=project_dir)
}
if (file.exists(project$result_file) || file.exists(project$reviewed_file)) {
result <- read_experiment(project)
} else {
result <- run_experiment(
project, dish_diameter_mm=90, # Replace with the verified outer dish diameter.
n_spots=5, spot_radius_mm=0.4
)
}
result$failed
head(result$colonies)
project$qc_dir # Inspect the saved QC images and resolve failures first.
reviewed <- finish_experiment(project)
comparison <- plot_treatment_comparison(reviewed)
if (!is.null(comparison)) print(comparison)
project$project_dir # Saved tables and any eligible comparison figures.A new project needs a new or empty output folder. Reopening retains that project’s photographs; choose another folder for a different archive. To change analysis settings, rerun run_experiment() explicitly. The default layout is four target colonies around a central fungus. Control-only images need default_centre="none"; mixed collections need correct per-image layouts.
Measurement needs no treatment names or approval-flag edits. A treatment comparison still requires real treatment/control assignments within each set_id. Otherwise FunMel saves measurements, reports awaiting_design and explains why no comparison figure is produced. The real-data tutorial also shows a descriptive set plot that needs no treatment names.
The output folder also contains run_summary.csv, metadata_issues.csv, measurement_issues.csv and layout_assignments.csv. These distinguish missing experimental assignments from incomplete colony/spot measurements. See the real-data troubleshooting guide.
Tutorials
| Task | Guide |
|---|---|
| Own photographs, layouts, metadata and saved work | Get started |
| Eight original photographs, complete walkthrough and set-only summaries | Real 14-day data |
| Every exported function, including specialist tools | Function examples |
| Algorithms and use alongside ImageJ/Fiji | Package overview |
Interpretation
Melanization index is MI = 100 - CIELAB L*: an image-darkness proxy, not a direct measurement of melanin concentration. Central hyphal growth is not an inhibition zone. Inspect masks, calibration and lighting before interpreting results.
Independent plates are the experimental units; colonies and spots are subsamples. Matched coefficients divide treatment plate means by their own set’s control mean. One control per set supports descriptive ratios, not replicated-control significance tests. The tutorials explain statistical requirements, figure contents and limitations in detail.