VANESSA—Shiny Apps for Accelerated Time-series Analysis and Visualization of <i>Drosophila</i> Circadian Rhythm and Sleep Data
Arijit Ghosh, Vasu Sheeba
Abstract
Chronobiologists and sleep researchers often need to estimate various rhythm and sleep parameters from locomotor activity data from different organisms. The available open-source or expensive paid tools do not offer consolidated analysis and visualization options in one bundle, are often cumbersome for users unfamiliar with coding, offer very low customization options, introduce sources of human errors by requiring users to manually pick period and power values from periodogram plots, and do not generate reproducible reports. We present VANESSA, a family of cross-platform apps written in R, which, in our opinion, have several advantages compared with available tools—(a) open-source; (b) automatic period-power detection; (c) time-series filtering and smoothing; (d) high-resolution publication-quality figures with dynamic coloring, resizing, and light/dark shading; (e) reproducible code-report generation; (f) analysis and visualization of multiple monitor files, defining genotypes and replicates separately; and (g) sleep profile analysis, various sleep parameter estimations, quantification, bout analysis, and latency analysis. The current version of the app is for data acquired through Drosophila Activity Monitors (DAM, TriKinetics) but can be easily extended to that from other data acquisition systems and from other organisms. We will continue to develop VANESSA with more useful features and version control will be done via archiving versions with significant changes on GitHub ( https://github.com/orijitghosh/VANESSA-DAM ) and Zenodo.