bakRData

This function creates an object of class bakRData

Several implementations of a novel Bayesian hierarchical statistical model of nucleotide
recoding RNA-seq experiments (NR-seq; TimeLapse-seq, SLAM-seq, TUC-seq, etc.)
for analyzing and comparing NR-seq datasets (see 'Vock and Simon' (2023) <doi:10.1261/rna.079451.122>).
NR-seq is a powerful extension of RNA-seq that provides information about the kinetics
of RNA metabolism (e.g., RNA degradation rate constants), which is notably lacking
in standard RNA-seq data. The statistical model makes maximal use of these high-throughput
datasets by sharing information across transcripts to significantly improve
uncertainty quantification and increase statistical power. 'bakR' includes a maximally
efficient implementation of this model for conservative initial investigations of datasets. 'bakR'
also provides more highly powered implementations using the probabilistic programming language
'Stan' to sample from the full posterior distribution. 'bakR' performs multiple-test
adjusted statistical inference with the output of these model implementations to
help biologists separate signal from background. Methods to automatically visualize key
results and detect batch effects are also provided.

Isaac Vock

bakR

Analyze and Compare Nucleotide Recoding RNA Sequencing Datasets

bakRData function

<dl><dt>cB</dt>
<dd>Dataframe with columns corresponding to feature ID, number of Ts, number of mutations, sample ID, and number of identical observations</dd>
<dt>metadf</dt>
<dd>Dataframe detailing s4U label time and experimental ID of each sample</dd></dl>

Arguments

bakR Data object helper function for users — bakRData

<dl>

<dt>cB</dt>
<dd>Dataframe with columns corresponding to feature ID, number of Ts, number of mutations, sample ID, and number of identical observations</dd>


<dt>metadf</dt>
<dd>Dataframe detailing s4U label time and experimental ID of each sample</dd>

</dl>

bakRData: bakR Data object helper function for users

Description

Usage

Value

Arguments

Examples