Package: CBASSED50 0.2.0

Luigi Colin

CBASSED50: Process CBASS-Derived PAM Data

Tools to process CBASS-derived PAM data efficiently. Minimal requirements are PAM-based photosynthetic efficiency data (or data from any other continuous variable that changes with temperature, e.g. relative bleaching scores) from 4 coral samples (nubbins) subjected to 4 temperature profiles of at least 2 colonies from 1 coral species from 1 site. Please refer to the following CBASS (Coral Bleaching Automated Stress System) papers for in-depth information regarding CBASS acute thermal stress assays, experimental design considerations, and ED5/ED50/ED95 thermal parameters: Nicolas R. Evensen et al. (2023) <doi:10.1002/lom3.10555> Christian R. Voolstra et al. (2020) <doi:10.1111/gcb.15148> Christian R. Voolstra et al. (2025) <doi:10.1146/annurev-marine-032223-024511>.

Authors:Yulia Iakovleva [aut], Luigi Colin [aut, cre], Christian Robert Voolstra [aut]

CBASSED50_0.2.0.tar.gz
CBASSED50_0.2.0.zip(r-4.7-any)CBASSED50_0.2.0.zip(r-4.6-any)
CBASSED50_0.2.0.tar.gz(r-4.7-any)CBASSED50_0.2.0.tar.gz(r-4.6-any)
CBASSED50_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
CBASSED50/json (API)

# Install 'CBASSED50' in R:

install.packages('CBASSED50', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

cbass_dataset - CBASS Dataset

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 3 scripts 360 downloads 20 exports 84 dependencies

Last updated from:f659cbd53d. Checks:6 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	174
source / vignettes	OK	213
linux-release	OK	162
windows-devel	OK	131
windows-release	OK	124
wasm-release	OK	125

Exports:calculate_eds check_enough_unique_temperatures_values convert_columns dataset_has_mandatory_columns define_grouping_property define_temperature_ranges exploratory_tr_curve fit_curve_eds fit_drms get_all_eds_by_grouping_property get_ed50_by_grouping_property get_predicted_pam_values mandatory_columns plot_ED50_box plot_model_curve predict_temperature_values preprocess_dataset process_dataset read_data validate_cbass_dataset

Dependencies:abind backports boot broom car carData cellranger cli codetools colorspace cowplot cpp11 crayon Deriv doBy dplyr drc farver forecast Formula fracdiff generics ggplot2 glue gtable gtools hms isoband labeling lattice lifecycle lme4 lmtest magrittr MASS Matrix MatrixModels mgcv minqa modelr multcomp mvtnorm nlme nloptr nnet numDeriv pbkrtest pillar pkgconfig plotrix prettyunits progress purrr quantreg R6 rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen Rdpack readxl reformulas rematch rlang rlog S7 sandwich scales SparseM stringi stringr survival TH.data tibble tidyr tidyselect timeDate urca utf8 vctrs viridisLite withr zoo

Help page	Topics
Calculate ED5, ED50, and ED95 values for all samples in the dataset.	calculate_eds
CBASS Dataset	cbass_dataset
Check if the dataset contains enough unique temperature values	check_enough_unique_temperatures_values
Check and Convert Columns in Dataset	convert_columns
Check if the dataset has all mandatory columns	dataset_has_mandatory_columns
Define Grouping Property Column	define_grouping_property
Define Temperature Ranges	define_temperature_ranges
Plot an exploratory temperature response curve.	exploratory_tr_curve
Fit dose-response models and calculate summary statistics for ED5, ED50, and ED95 values.	fit_curve_eds
Fit Dynamic Regression Models (DRMs)	fit_drms
Get ED5s, ED50s and ED95s by Grouping Property	get_all_eds_by_grouping_property
Get ED50 by Grouping Property	get_ed50_by_grouping_property
Get Predicted PAM Values	get_predicted_pam_values
Get the names of mandatory columns for the dataset.	mandatory_columns
Plot a boxplot of ED50 values for different species and conditions.	plot_ED50_box
Plot the model curve with predicted PAM values and confidence intervals.	plot_model_curve
Predict the temperature values	predict_temperature_values
Preprocesses the data by converting and checking column data types.	preprocess_dataset
Experimental Features for CBASS Dataset Analysis	process_dataset
Read Data Function	read_data
Transform Predictions to a Long-Format DataFrame	transform_predictions_to_long_dataframe
Validate CBASS Dataset	validate_cbass_dataset

Package: CBASSED50 0.2.0

CBASSED50: Process CBASS-Derived PAM Data

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Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)