Package: sicegar 0.2.4
Claus O. Wilke
sicegar: Analysis of Single-Cell Viral Growth Curves
Aims to quantify time intensity data by using sigmoidal and double sigmoidal curves. It fits straight lines, sigmoidal, and double sigmoidal curves on to time vs intensity data. Then all the fits are used to make decision on which model best describes the data. This method was first developed in the context of single-cell viral growth analysis (for details, see Caglar et al. (2018) <doi:10.7717/peerj.4251>), and the package name stands for "SIngle CEll Growth Analysis in R".
Authors:
sicegar_0.2.4.tar.gz
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sicegar_0.2.4.tgz(r-4.4-any)sicegar_0.2.4.tgz(r-4.3-any)
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sicegar.pdf |sicegar.html✨
sicegar/json (API)
| # Install 'sicegar' in R: |
| install.packages('sicegar', repos = c('https://wilkelab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/wilkelab/sicegar/issues
Last updated 4 years agofrom:08bf9c45d2. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 01 2024 |
| R-4.5-win | NOTE | Nov 01 2024 |
| R-4.5-linux | NOTE | Nov 01 2024 |
| R-4.4-win | NOTE | Nov 01 2024 |
| R-4.4-mac | NOTE | Nov 01 2024 |
| R-4.3-win | NOTE | Nov 01 2024 |
| R-4.3-mac | NOTE | Nov 01 2024 |
Exports:categorizedataCheckdoublesigmoidalFitFormuladoublesigmoidalFitFunctionfigureModelCurvesfitAndCategorizemultipleFitFunctionnormalizeDataparameterCalculationpreCategorizesameSourceDataChecksigmoidalFitFormulasigmoidalFitFunctionunnormalizeData
Dependencies:clicolorspacedplyrfansifarverfBasicsgenericsggplot2gluegssgtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvminpack.lmmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalesspatialstabledisttibbletidyselecttimeDatetimeSeriesutf8vctrsviridisLitewithr
Calculation of additional parameters of interest
Rendered fromadditional_parameters.Rmdusingknitr::rmarkdownon Nov 01 2024.Last update: 2017-07-11
Started: 2017-06-22
Fitting individual models
Rendered fromfitting_individual_models.Rmdusingknitr::rmarkdownon Nov 01 2024.Last update: 2017-07-11
Started: 2017-06-23
Identifying the best-fitting model category
Rendered fromcategorizing_fits.Rmdusingknitr::rmarkdownon Nov 01 2024.Last update: 2017-07-28
Started: 2017-06-23
Introduction
Rendered fromintroduction.Rmdusingknitr::rmarkdownon Nov 01 2024.Last update: 2019-08-22
Started: 2017-06-21
Plotting the fitted models
Rendered fromplotting_fitted_models.Rmdusingknitr::rmarkdownon Nov 01 2024.Last update: 2017-07-11
Started: 2017-06-23
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Categorize input data by comparing the AIC values of the three fitted models. | categorize |
| Checks if data is in correct format. | dataCheck |
| Double Sigmoidal Formula | doublesigmoidalFitFormula |
| Double sigmoidal fit function. | doublesigmoidalFitFunction |
| Generate model associated figures. | figureModelCurves |
| Fit and categorize. | fitAndCategorize |
| multiple fit function. | multipleFitFunction |
| Normalization of given data | normalizeData |
| useful paramter calculation with help of fits | parameterCalculation |
| Checks for signal in the data. | preCategorize |
| Check is data came from the same source. | sameSourceDataCheck |
| sigmoidalFitFormula | sigmoidalFitFormula |
| Sigmoidal fit function | sigmoidalFitFunction |
| Unnormalization of given data | unnormalizeData |
