| QC_checks {bakR} | R Documentation |
QC_checks takes as input a bakRFit or bakRFnFit object and uses the Fast_Fit object to assess
data quality and make suggestions about which implementation to run next. QC_checks
takes into account the mutation rates in all samples, the fraction new distributions, the reproducibility
of fraction new estimates, and the read lengths. It then outputs a number of
diagnostic plots that might alert users to problems in their data. It also
outputs messages informing users what implementation is best used next.
QC_checks(obj)
obj |
bakRFit object |
A list with 3 components:
raw_mutrates. This is a plot of the raw T-to-C mutation rates in all samples analyzed by bakR. It includes horizontal lines as reference for what could be considered "too low" to be useful in s4U fed samples.
conversion_rates. This is a plot of the estimated T-to-C mutation rates in new and old reads. Thus, each bar represents the probability that a U in a new/old read is mutated. It includes horizontal lines as reference for what could be considered good mutation rates.
correlation_plots. This is a list of ggplot objects. Each is a scatter plot comparing estimates of the fraction new in one replicate to another replicate in the same experimental condition. A y=x guide line is included to reveal any estimation biases.
# Simulate data for 500 genes and 2 replicates
sim <- Simulate_bakRData(500, nreps = 2)
# Fit data with fast implementation
Fit <- bakRFit(sim$bakRData)
# Run QC
QC <- QC_checks(Fit)