Runway: A novel, forward-screen method of analyzing catwalk gait analysis data

Area of Science:

• Neuroscience
• Biomechanical Engineering
• Computational Biology

Background:

• Locomotor behavior assessment is vital in neurotrauma research.
• Gait analysis using tools like the CatWalk apparatus generates high-dimensional data.
• Interpreting this complex data for locomotor outcomes poses a significant challenge.

Purpose of the Study:

• To develop an accessible R package for processing, analyzing, and visualizing CatWalk kinematic data.
• To introduce a novel forward-screen analysis method for identifying treatment-affected gait variables.
• To facilitate the interpretation of animal locomotion data in neurotrauma studies.

Main Methods:

• Development of the "runway" R package.
• Implementation of a novel forward-screen analysis pipeline.
• Systematic identification and analysis of gait variables affected by experimental interventions.

Main Results:

• The "runway" package effectively processes and analyzes high-dimensional CatWalk data.
• The forward-screen method successfully isolates and analyzes key gait variables.
• Demonstrated utility through use case examples for interpreting animal gait.

Conclusions:

• "runway" offers a powerful and systematic approach to interpreting CatWalk gait analysis data.
• This R package aids researchers in understanding treatment effects on animal locomotion.
• Facilitates robust gait analysis in neurotrauma and related research fields.