Quantitative Fitness Analysis (QFA) is a complementary series of experimental and computational methods for estimating the fitness of thousands of microbial cultures in parallel. QFA is suitable for focussed, high-quality studies of the effect of genetic mutations or drug interventions on growth in model microbial organisms such as brewer's yeast. Culture growth is observed by time-lapse photography of solid agar plates inoculated with cultures in rectangular arrays. Growth curves are constructed by analysing image series using Colonyzer image analysis software (http://research.ncl.ac.uk/colonyzer) which converts images to arrays of cell density estimates. This R package is for a) fitting the generalised logistic model to potentially thousands of parallel growth curves, b) using inferred parameter values to calculate fitnesses for each culture and c) comparing fitnesses between QFA experiments with different genetic backgrounds or treatments to deduce interaction strengths. This package facilitates quantifying the fitness of thousands of independent microbial strains and tracking them throughout growth curve experiments. With appropriately designed experiments, qfa can also estimate genetic interaction strengths and produce epistasis plots.
|Author||Conor Lawless <email@example.com>, with contributions from Alexander Young <firstname.lastname@example.org> and Darren Wilkinson <email@example.com>|
|Date of publication||2016-12-01 17:32:23|
|Maintainer||Conor Lawless <firstname.lastname@example.org>|
colonyzer.read: Reads raw cell density timecourse data from Colonyzer output...
correlationReport: Correlation Report
datafit: Fitting generalised logistic model to growth data by least...
dtl: Culture Doubling Time for Generalised Logistic Function (as a...
fitnessReport: Fitness Report
getDeadLocations: Find dead cultures in SGA plates (1536 format), and report...
Glogist: Generalised Logistic growth curve model
growthcurve: Wrapper function for generating QFA generalised logistic...
iRVisDemo: Interactive fitness plots from Addinal et al. 2011 PLoS...
loapproxfun: Model free growth curve approximation
logist: Logistic growth curve model
makeBoundsQFA: Generate generalised logistic parameter bounds for QFA
makeFitness: Generate QFA fitnesses
mdp: Maximum Doubling Potential (MDP) for Generalised Logistic...
mdr: Maximum Doubling Rate (MDR) for Generalised Logistic Function
mdrmdp: Fitness value for Generalised Logistic Function
normalisePlates: Normalising culture fitness by plate
numericalfitness: Numerical fitness estimates from timecourse data
numerical_r: Generates numerical fitnesses from experimental growth curve...
pgis: Calculate strength and significance of genetic interaction.
plateBoxplots: Plate Boxplots
qfa.epi: Finds genetic interaction strengths and p-values
qfa.epiplot: Makes an epistasis plot from the full results of qfa.epi
qfa.fit: Growth curve modelling
qfa-Internal: Internal qfa Functions
qfa.plot: Plots fitted model and data for all the colonies in results...
report.epi: Normalising culture fitness by plate
rod.read: Reading of ROD raw timecourse data. Deprecated.
rod.write: Writes a synthetic ROD-like output file to hard-drive....
showDemo: Show Demo
visTool: Making the visualisation tool