qfa: Tools for modelling the growth dynamics of arrays of large
numbers of colonies and performing quantitative fitness
analysis (QFA)
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.
Version: |
0.0-10 |
Depends: |
R (≥ 2.10.1), sp, DEoptim |
Published: |
2013-06-21 |
Author: |
Conor Lawless, with contributions
from Alexander Young and Darren
Wilkinson |
Maintainer: |
Conor Lawless <conor.lawless at ncl.ac.uk> |
BugReports: |
conor.lawless@ncl.ac.uk |
License: |
Artistic-2.0 |
URL: |
http://qfa.r-forge.r-project.org/ |
NeedsCompilation: |
no |
CRAN checks: |
qfa results |
Downloads: