Package: AnaCoDa 0.1.4.4

Cedric Landerer

AnaCoDa: Analysis of Codon Data under Stationarity using a Bayesian Framework

Is a collection of models to analyze genome scale codon data using a Bayesian framework. Provides visualization routines and checkpointing for model fittings. Currently published models to analyze gene data for selection on codon usage based on Ribosome Overhead Cost (ROC) are: ROC (Gilchrist et al. (2015) <doi:10.1093/gbe/evv087>), and ROC with phi (Wallace & Drummond (2013) <doi:10.1093/molbev/mst051>). In addition 'AnaCoDa' contains three currently unpublished models. The FONSE (First order approximation On NonSense Error) model analyzes gene data for selection on codon usage against of nonsense error rates. The PA (PAusing time) and PANSE (PAusing time + NonSense Error) models use ribosome footprinting data to analyze estimate ribosome pausing times with and without nonsense error rate from ribosome footprinting data.

Authors:Authors@R

AnaCoDa_0.1.4.4.tar.gz
AnaCoDa_0.1.4.4.zip(r-4.5)AnaCoDa_0.1.4.4.zip(r-4.4)AnaCoDa_0.1.4.4.zip(r-4.3)
AnaCoDa_0.1.4.4.tgz(r-4.4-x86_64)AnaCoDa_0.1.4.4.tgz(r-4.4-arm64)AnaCoDa_0.1.4.4.tgz(r-4.3-x86_64)AnaCoDa_0.1.4.4.tgz(r-4.3-arm64)
AnaCoDa_0.1.4.4.tar.gz(r-4.5-noble)AnaCoDa_0.1.4.4.tar.gz(r-4.4-noble)
AnaCoDa_0.1.4.4.tgz(r-4.4-emscripten)AnaCoDa_0.1.4.4.tgz(r-4.3-emscripten)
AnaCoDa.pdf |AnaCoDa.html✨
AnaCoDa/json (API)

# Install 'AnaCoDa' in R:
install.packages('AnaCoDa', repos = c('https://clandere.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/clandere/anacoda/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

4.00 score 1 stars 100 scripts 332 downloads 1 mentions 35 exports 3 dependencies

Last updated 4 years agofrom:6fc68a8050. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 06 2024
R-4.5-win-x86_64NOTENov 06 2024
R-4.5-linux-x86_64NOTENov 06 2024
R-4.4-win-x86_64NOTENov 06 2024
R-4.4-mac-x86_64NOTENov 06 2024
R-4.4-mac-aarch64NOTENov 06 2024
R-4.3-win-x86_64NOTENov 06 2024
R-4.3-mac-x86_64NOTENov 06 2024
R-4.3-mac-aarch64NOTENov 06 2024

Exports:AAToCodonacfCSPacfMCMCaddObservedSynthesisRateSetaminoAcidscalculateMarginalLogLikelihoodcalculateSCUOcodonscodonToAAconvergence.testfindOptimalCodongeomMeangetCAIgetCAIweightsgetCodonCountsgetCodonCountsForAAgetCSPEstimatesgetExpressionEstimatesgetMixtureAssignmentEstimategetNamesgetNcgetNcAAgetObservedSynthesisRateSetgetSelectionCoefficientsgetTraceinitializeGenomeObjectinitializeMCMCObjectinitializeModelObjectinitializeParameterObjectloadMCMCObjectloadParameterObjectrunMCMCsetRestartSettingswriteMCMCObjectwriteParameterObject

Dependencies:mvtnormRcppVGAM

AnaCoDa: Analyzing Codon Data

Cedric Landerer & Alexander L. Cope

Rendered fromanacoda.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2020-09-11
Started: 2018-01-02

Readme and manuals

Help Manual

Help pageTopics
Amino Acid to codon setAAToCodon
Plots ACF for codon specific parameter tracesacfCSP
Autocorrelation function for the likelihood or posterior traceacfMCMC
Add gene observed synthesis ratesaddObservedSynthesisRateSet
Amino acidsaminoAcids
Calculates the marginal log-likelihood for a set of parameterscalculateMarginalLogLikelihood
calculates the synonymous codon usage order (SCUO)calculateSCUO
Codonscodons
translates codon to amino acidcodonToAA
Convergence Testconvergence.test
Find and return list of optimal codonsfindOptimalCodon
fixDEtafixDEta
fixDMfixDM
fixSphifixSphi
Take the geometric mean of a vectorgeomMean
getAdaptiveWidthgetAdaptiveWidth
Calculate the Codon Adaptation IndexgetCAI
Calculate the CAI codon weigths for a reference genomegetCAIweights
Get Codon Counts For all Amino AcidsgetCodonCounts
Get Codon Counts For a specific Amino AcidgetCodonCountsForAA
getCodonSpecificPosteriorMeanForCodongetCodonSpecificPosteriorMeanForCodon
getCodonSpecificPosteriorVarianceForCodongetCodonSpecificPosteriorVarianceForCodon
getCodonSpecificQuantilesForCodongetCodonSpecificQuantilesForCodon
Return Codon Specific Paramters (or write to csv) estimates as data.framegetCSPEstimates
getEstimatedMixtureAssignmentForGenegetEstimatedMixtureAssignmentForGene
getEstimatedMixtureAssignmentProbabilitiesForGenegetEstimatedMixtureAssignmentProbabilitiesForGene
Returns the estimated phi posterior for a genegetExpressionEstimates
getGroupListgetGroupList
getLogLikelihoodTracegetLogLikelihoodTrace
getLogPosteriorMeangetLogPosteriorMean
getLogPosteriorTracegetLogPosteriorTrace
Returns mixture assignment estimates for each genegetMixtureAssignmentEstimate
Gene Names of GenomegetNames
Calculate the Effective Number of CodonsgetNc
Calculate the Effective Number of Codons for each Amino AcidgetNcAA
getNoiseOffsetPosteriorMeangetNoiseOffsetPosteriorMean
getNoiseOffsetVariancegetNoiseOffsetVariance
Get gene observed synthesis ratesgetObservedSynthesisRateSet
getSamplesgetSamples
Calculate Selection coefficientsgetSelectionCoefficients
getStdDevSynthesisRatePosteriorMeangetStdDevSynthesisRatePosteriorMean
getStdDevSynthesisRateVariancegetStdDevSynthesisRateVariance
getStepsToAdaptgetStepsToAdapt
getSynthesisRategetSynthesisRate
getSynthesisRatePosteriorMeanForGenegetSynthesisRatePosteriorMeanForGene
getSynthesisRatePosteriorVarianceForGenegetSynthesisRatePosteriorVarianceForGene
getThinninggetThinning
extracts an object of traces from a parameter object.getTrace
getTraceObjectgetTraceObject
Initialize Covariance MatricesinitializeCovarianceMatrices
Genome InitializationinitializeGenomeObject
Initialize MCMCinitializeMCMCObject
Model InitializationinitializeModelObject
Initialize ParameterinitializeParameterObject
initializeSynthesisRateByGenomeinitializeSynthesisRateByGenome
initializeSynthesisRateByListinitializeSynthesisRateByList
initializeSynthesisRateByRandominitializeSynthesisRateByRandom
initMutationCategoriesinitMutationCategories
initSelectionCategoriesinitSelectionCategories
Length of Genomelength.Rcpp_Genome
Load MCMC ObjectloadMCMCObject
Load Parameter ObjectloadParameterObject
Plot Model Objectplot.Rcpp_FONSEModel
Plot Parameterplot.Rcpp_FONSEParameter
Plot MCMC algorithmplot.Rcpp_MCMCAlgorithm
Plot Model Objectplot.Rcpp_ROCModel
Plot Parameterplot.Rcpp_ROCParameter
Plot Trace Objectplot.Rcpp_Trace
Plot Acceptance ratiosplotAcceptanceRatios
Plot Codon Specific ParameterplotCodonSpecificParameters
readPhiValuereadPhiValue
Run MCMCrunMCMC
setAdaptiveWidthsetAdaptiveWidth
setGroupListsetGroupList
setRestartFileSettingssetRestartFileSettings
Set Restart SettingssetRestartSettings
setSamplessetSamples
setStepsToAdaptsetStepsToAdapt
setThinningsetThinning
simulateGenomesimulateGenome
Summary of Genomesummary.Rcpp_Genome
Write MCMC ObjectwriteMCMCObject
Write Parameter Object to a FilewriteParameterObject