Quentin PETITJEAN, Silene LARTIGUE, Melina COINTE, Nicolas RIS, vincent calcagno
{"title":"MoveR: an R package for easy processing and analysis of animal video-tracking data","authors":"Quentin PETITJEAN, Silene LARTIGUE, Melina COINTE, Nicolas RIS, vincent calcagno","doi":"10.1101/2023.11.08.566216","DOIUrl":null,"url":null,"abstract":"Animal movement and behavior are critical to understanding ecological and evolutionary processes. Recent years have witnessed an increase in methodological and technological innovations in video-tracking solutions for phenotyping animal behavior. Although these advances enable the collection of high-resolution data describing the movement of multiple individuals, analyzing and interpreting them remains challenging due to their complexity, heterogeneity, and noisiness. Here, we introduce MoveR, an R package for importing, filtering, visualizing, and analyzing data from common video-tracking solutions. MoveR includes flexible tools for polishing data, removing tracking artifacts, subsetting and plotting individual paths, and computing different movement and behavior metrics.","PeriodicalId":486943,"journal":{"name":"bioRxiv (Cold Spring Harbor Laboratory)","volume":"39 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv (Cold Spring Harbor Laboratory)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2023.11.08.566216","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Animal movement and behavior are critical to understanding ecological and evolutionary processes. Recent years have witnessed an increase in methodological and technological innovations in video-tracking solutions for phenotyping animal behavior. Although these advances enable the collection of high-resolution data describing the movement of multiple individuals, analyzing and interpreting them remains challenging due to their complexity, heterogeneity, and noisiness. Here, we introduce MoveR, an R package for importing, filtering, visualizing, and analyzing data from common video-tracking solutions. MoveR includes flexible tools for polishing data, removing tracking artifacts, subsetting and plotting individual paths, and computing different movement and behavior metrics.