QC_checks: Check data quality and make suggestions to user about what...

In bakR: Analyze and Compare Nucleotide Recoding RNA Sequencing Datasets

Check data quality and make suggestions to user about what analyses to run.

Description

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.

Usage

QC_checks(obj)

Arguments

obj	bakRFit object

Value

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.

Examples

# 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)

bakR documentation built on June 22, 2024, 6:55 p.m.