Package: bakR 1.0.1

Isaac Vock

bakR: Analyze and Compare Nucleotide Recoding RNA Sequencing Datasets

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.

Authors:Isaac Vock [aut, cre]

bakR_1.0.1.tar.gz
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bakR.pdf |bakR.html
bakR/json (API)
NEWS

# Install 'bakR' in R:
install.packages('bakR', repos = c('https://simonlabcode.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/simonlabcode/bakr/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • GS_table - Example cB data frame
  • cB_small - Example cB data frame
  • fns - Example fraction news (fns) data frame
  • metadf - Example meatdf data frame

On CRAN:

6.25 score 6 stars 21 scripts 333 downloads 21 exports 92 dependencies

Last updated 3 days agofrom:77950c1070. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-win-x86_64NOTENov 20 2024
R-4.5-linux-x86_64NOTENov 20 2024
R-4.4-win-x86_64NOTENov 20 2024
R-4.4-mac-x86_64NOTENov 20 2024
R-4.4-mac-aarch64NOTENov 20 2024
R-4.3-win-x86_64NOTENov 20 2024
R-4.3-mac-x86_64NOTENov 20 2024
R-4.3-mac-aarch64NOTENov 20 2024

Exports:bakRDatabakRFitbakRFnDatacBprocessCorrectDropoutDissectMechanismfast_analysisfn_processFnPCAFnPCA2GSprocessingHeatmap_kdegNSSHeatplotMAplotVolcanoQC_checksQuantifyDropoutreliableFeaturesSimulate_bakRDataSimulate_relative_bakRDataVisualizeDropout

Dependencies:abindbackportsbase64encBHbslibcachemcallrcheckmatecliclustercolorspacecpp11data.tabledescdigestdistributionaldplyrevaluatefansifarverfastmapfontawesomeforeignFormulafsgenericsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsinlineisobandjquerylibjsonliteknitrlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmemoisemgcvmimemunsellnlmennetnumDerivpillarpkgbuildpkgconfigposteriorprocessxpspurrrQuickJSRR6rappdirsRColorBrewerRcppRcppEigenRcppParallelrlangrmarkdownrpartrstanrstantoolsrstudioapisassscalesStanHeadersstringistringrtensorAtibbletidyrtidyselecttinytexutf8vctrsviridisviridisLitewithrxfunyaml

GRAND-SLAM output/fn estimates as bakR input

Rendered frombakR-Fn.Rmdusingknitr::rmarkdownon Nov 20 2024.

Last update: 2023-06-27
Started: 2023-06-27

bakR for people in a hurry

Rendered frombakR-Quickstart.Rmdusingknitr::rmarkdownon Nov 20 2024.

Last update: 2023-06-27
Started: 2023-06-27

Differential synthesis analysis with bakR and DESeq2

Rendered fromDifferential-Synth.Rmdusingknitr::rmarkdownon Nov 20 2024.

Last update: 2024-01-13
Started: 2023-06-27

Correcting for dropout

Rendered fromDropout.Rmdusingknitr::rmarkdownon Nov 20 2024.

Last update: 2024-06-25
Started: 2023-06-27

Differential kinetic analysis with bakR

Rendered fromGetting-Started.Rmdusingknitr::rmarkdownon Nov 20 2024.

Last update: 2023-06-29
Started: 2021-10-07

Steady-state quasi-independent mechanistic investigations

Rendered fromNSS.Rmdusingknitr::rmarkdownon Nov 20 2024.

Last update: 2023-06-29
Started: 2023-06-27

Troubleshooting analyses of NR-seq data with bakR

Rendered fromTroubleshooting.Rmdusingknitr::rmarkdownon Nov 20 2024.

Last update: 2023-06-27
Started: 2023-06-27

Readme and manuals

Help Manual

Help pageTopics
The 'bakR' package.bakR-package bakR
Efficiently average replicates of nucleotide recoding data and regularizeavg_and_regularize
bakR Data object helper function for usersbakRData
Estimating kinetic parameters from nucleotide recoding RNA-seq databakRFit
bakRFnData object helper function for usersbakRFnData
Example cB data framecB_small
Curate data in bakRData object for statistical modelingcBprocess
Correcting for metabolic labeling induced RNA dropoutCorrectDropout
Construct heatmap for non-steady state (NSS) analysis with improved mechanism scoreDissectMechanism
Efficiently analyze nucleotide recoding datafast_analysis
Curate data in bakRFnData object for statistical modelingfn_process
Creating PCA plots with logit(fn) estimatesFnPCA
Creating PCA plots with logit(fn) estimatesFnPCA2
Example fraction news (fns) data framefns
Example cB data frameGS_table
Prep GRAND-SLAM output for 'bakRFnData'GSprocessing
Creating a L2FC(kdeg) matrix that can be passed to heatmap functionsHeatmap_kdeg
Example meatdf data framemetadf
bakRData object constructor for internal usenew_bakRData
bakRFnData object constructor for internal usenew_bakRFnData
Construct heatmap for non-steady state (NSS) analysisNSSHeat
Creating L2FC(kdeg) MA plot from fit objectsplotMA
Creating L2FC(kdeg) volcano plot from fit objectsplotVolcano
Check data quality and make suggestions to user about what analyses to run.QC_checks
Fit dropout model to quantify dropout frequencyQuantifyDropout
Identify features (e.g., transcripts) with high quality datareliableFeatures
Simulating nucleotide recoding dataSimulate_bakRData
Simulating nucleotide recoding data with relative count dataSimulate_relative_bakRData
Fit 'Stan' models to nucleotide recoding RNA-seq data analysisTL_stan
bakR Data object validatorvalidate_bakRData
bakRFnData object validatorvalidate_bakRFnData
Visualize dropoutVisualizeDropout