Package: NOVA 0.1.5

Alex Tudoras

NOVA: Neural Output Visualization and Analysis

A comprehensive toolkit for analyzing and visualizing neural data outputs, including Principal Component Analysis (PCA) trajectory plotting, Multi-Electrode Array (MEA) heatmap generation, and variable importance analysis. Provides publication-ready visualizations with flexible customization options for neuroscience research applications.

Authors:Alex Tudoras [aut, cre]

NOVA_0.1.5.tar.gz
NOVA_0.1.5.zip(r-4.7)NOVA_0.1.5.zip(r-4.6)NOVA_0.1.5.zip(r-4.5)
NOVA_0.1.5.tgz(r-4.6-any)NOVA_0.1.5.tgz(r-4.5-any)
NOVA_0.1.5.tar.gz(r-4.7-any)NOVA_0.1.5.tar.gz(r-4.6-any)
NOVA_0.1.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
NOVA/json (API)
NEWS

# Install 'NOVA' in R:

install.packages('NOVA', repos = c('https://atudoras.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/atudoras/nova/issues

On CRAN:

3.56 score 18 scripts 458 downloads 19 exports 76 dependencies

Last updated from:0be3f5ffbe. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	197
source / vignettes	OK	176
linux-release-x86_64	NOTE	212
macos-release-arm64	NOTE	179
macos-oldrel-arm64	NOTE	172
windows-devel	NOTE	125
windows-release	NOTE	98
windows-oldrel	NOTE	122
wasm-release	OK	167

Exports:aggregate_data analyze_pca_variable_importance_general apply_scaling_enhanced clean_heatmap_matrix create_annotations_enhanced create_color_palette_enhanced create_mea_heatmaps_enhanced discover_mea_structure handle_missing_values null_coalesce pca_analysis_enhanced pca_plots_enhanced perform_mea_pca plot_mea_metric plot_pca_trajectories_general print_detailed_summary process_mea_flexible quality_filter setup_color_scheme

Dependencies:base64enc bit bit64 bslib cachem cellranger cli clipr cpp11 crayon crosstalk digest dplyr DT evaluate farver fastmap fontawesome fs generics ggplot2 ggrepel glue gridExtra gtable highr hms htmltools htmlwidgets isoband jquerylib jsonlite knitr labeling later lazyeval lifecycle magrittr memoise mime otel pheatmap pillar pkgconfig prettyunits progress promises purrr R6 rappdirs RColorBrewer Rcpp readr readxl rematch rlang rmarkdown S7 sass scales stringi stringr tibble tidyr tidyselect tinytex tzdb utf8 vctrs viridis viridisLite vroom withr writexl xfun yaml

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Aggregate Data by Groups	aggregate_data
Analyze and Visualize PCA Variable Importance	analyze_pca_variable_importance_general
Apply Enhanced Scaling Methods	apply_scaling_enhanced
Clean Heatmap Matrix	clean_heatmap_matrix
Create Enhanced Annotations for Heatmaps	create_annotations_enhanced
Create Enhanced Color Palettes	create_color_palette_enhanced
Create Enhanced Heatmaps for Multi-Electrode Array (MEA) Data Analysis	create_mea_heatmaps_enhanced
Discover MEA Data Structure	discover_mea_structure
Handle Missing Values in MEA Data	handle_missing_values
Null Coalescing Operator	null_coalesce
Enhanced PCA Analysis for MEA Data	pca_analysis_enhanced
Enhanced PCA Plotting for Neural and Omics Data	pca_plots_enhanced
Perform MEA PCA Analysis	perform_mea_pca
Plot a Single MEA Metric Across Conditions	plot_mea_metric
Plot PCA Trajectories for Time Series Data	plot_pca_trajectories_general
Print Detailed PCA Variable Summary	print_detailed_summary
Process MEA Data Flexibly	process_mea_flexible
Filter Data by Quality Metrics	quality_filter
Setup Color Scheme	setup_color_scheme