bioRxivAnimal Behavior & Cognition
TManual: Assistant for manually measuring length development in structures built by animals
Abstract
O_LIStructures built by animals are extended phenotypes, and animal behavior can be better understood by recording the temporal development of structure construction. For most subterranean and wood-boring animals, these structures consist of gallery systems, such as burrows made by mice, tunnel foraging by termites, and nest excavation in ants. Measurement of the length development of such structures is often performed manually. However, it is time-consuming and cognitively costly to track length development in nested branching structures, hindering the quantitative determination of temporal development. C_LIO_LIHere, I introduce TManual, which aids the manual measurement of structure length development using a number of images. TManual provides a user interface to draw gallery structures and take over all other processes handling input datasets (e.g., zero-adjustment, scaling the units, measuring the length, assigning gallery identities, and extracting network structures). Thus, users can focus on the measuring process without interruptions. C_LIO_LIAs examples, I provide the results of the analysis of a dataset of tunnel construction by three termite species after successfully processing 1,125 images in [~]3 h. The output datasets clearly visualized the interspecific variation in tunneling speed and branching structures. Furthermore, I applied TManual to a complex gallery system by another termite species and extracted network structures. C_LIO_LIMeasuring the lengths of objects from images is an essential task in biological observation. TManual helps users handle many images in a realistic time scale, enabling a comparative analysis across a wide array of species. TManual does not require programming skills and outputs a tidy data frame in CSV format. Therefore, it is suitable for any user who wants to perform image analysis for length measurements. C_LI
- assay: imaging
- research focus: cell type annotation
- research focus: clustering
- research focus: spatial domain detection
- approach: experimental assay
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- A new pipeline to automatically segment and semi-automatically measure bone length on 3D models obtained by Computed Tomography
Santiago Beltran Diaz, Xinli Qu, … Alberto Roselló‐Díez·Frontiers in Cell and Developmental BiologyPeer-reviewed·Aug 26, 2021
- ML-morph: A fast, accurate and general approach for automated detection and landmarking of biological structures in images
A. Porto, K. L. Voje·bioRxiv·Sep 14, 2019
- InsectMorphoAI: A Deep Learning-Based Software for Automated Estimation of Insect Length, Volume, and Biomass
Hossein Shirali, Aleida Ascenzi, … Christian Pylatiuk·Ecological InformaticsPeer-reviewed·May 25, 2026
- Cellects, a software to quantify cell expansion and motion
Aurèle Boussard, Manuel Petit, … Alfonso Pérez‐Escudero·bioRxiv·Mar 26, 2024
- DSeg: A dynamic image segmentation program to extract backbone patterns for filamentous bacteria and hyphae structures
Hanqing Zhang, Niklas Söderholm, … Magnus J. Andersson·Microscopy and MicroanalysisPeer-reviewed·Mar 21, 2019
- Multiscale learning and topological analysis across complex postures enable robust nematode size quantification in pharmacological assays
Zihao Li, Amanda O. Shaver, … Erik C. Andersen·bioRxiv·Jul 17, 2026