Package: tTEscanR 0.99.1

Ana Varas-Sánchez

tTEscanR: A user-friendly integrative R package for quantifying and visualizing translation efficiency from sequencing data in diverse biological systems

Translation elongation is dependent on codon-anticodon interactions, with suitable nucleotide pairing being essential for efficient translation. To quantify this relationship, we previously developed a computational pipeline (GitHub - wgao688/sc_tRNA_mRNA) that uses mRNA codon usage relative to tRNA anticodon availability as a proxy for theoretical translation efficiency (tTE). Here, we introduce tTEscanR, a powerful and user-friendly R-based package that extends this approach to quantify translation efficiency from both bulk and single-cell sequencing data. tTEscanR is a versatile tool for exploring translation efficiency in diverse cellular processes, disease mechanisms, and therapeutic development. It also features an advanced visualization module to generate high-quality plots, enhancing result interpretation and communication.

Authors:Ana Varas-Sánchez [aut, cre], Carlos Gallardo-Dodd [aut], William Gao [aut], Claudia Kutter [ths], Karolinska Institutet [fnd], Swedish Research Council [fnd], Cancerfonden [fnd]

tTEscanR_0.99.1.tar.gz
tTEscanR_0.99.1.zip(r-4.7-any)tTEscanR_0.99.1.zip(r-4.6-any)tTEscanR_0.99.1.zip(r-4.5-any)
tTEscanR_0.99.1.tgz(r-4.6-any)tTEscanR_0.99.1.tgz(r-4.5-any)
tTEscanR_0.99.1.tar.gz(r-4.7-any)tTEscanR_0.99.1.tar.gz(r-4.6-any)
tTEscanR_0.99.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tTEscanR/json (API)

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

Bug tracker:https://github.com/avarassanchez/ttescanr/issues

Datasets:

On CRAN:

Conda:

softwareepitranscriptomicstranscriptomicsgeneexpressiongeneregulationsequencingsinglecellcellbasedassays

4.15 score 6 scripts 32 exports 188 dependencies

Last updated from:bf75b1ff98. Checks:1 NOTE, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE249
linux-develOK495
source / vignettesOK406
linux-releaseOK490
macos-releaseOK379
macos-oldrelOK318
windows-develOK447
windows-releaseOK417
windows-oldrelOK354
wasm-releaseOK211

Exports:computeAAUsagecomputeAnticodonUsagecomputeCodonUsagecomputeCorrelationBackgroundcomputeDEResultscomputeExonicBackgroundcomputeMeanUsagecomputeTheoreticalTEcreateObjectextractCodonsfeaturesToAAgetCodonFreqgetPermutationDistgroupConditionsmergeMatricesobtainSignificanceplotCorrelationplotDEResultsplotDistributionplotPermutationplotProportionplotTargetComparisonplotTEscorerunDEAnalysisrunPipelineshowPoolContributiontransformFormattRNAFilterCutstRNAGetMatrixtRNASetCutofftRNASetGenesupdateObject

Dependencies:abindAnnotationDbiaskpassbackportsBHBiobaseBiocBaseUtilsBiocFileCacheBiocGenericsBiocIOBiocParallelbiomaRtBiostringsbitbit64bitopsblobbootbroomBSgenomecachemcarcarDatacigarillocirclizecliclueclustercodetoolscolorspaceComplexHeatmapcorrplotcowplotcpp11crayoncurldata.tableDBIdbplyrDelayedArraydendsortDerivDESeq2digestdoBydoParalleldotCall64dplyrdqrngfarverfastmapfastmatchfilelockFNNforeachforecastformatRFormulafracdifffutile.loggerfutile.optionsfuturefuture.applygenericsGenomeInfoDbGenomicAlignmentsGenomicRangesGetoptLongggplot2ggpubrggrepelggsciggsignifGlobalOptionsglobalsgluegridExtragtablehmshttrhttr2IRangesirlbaisobanditeratorsjsonliteKEGGRESTlabelinglambda.rlatticelifecyclelistenvlme4lmtestlocfitmagrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmemoisemgcvmimeminqamodelrModstringsMultiAssayExperimentnlmenloptrnnetnumDerivopensslparallellypatchworkpbapplypbkrtestpillarpkgconfigpngpolynomprettyunitsprogressprogressrpurrrquantregR6rbibutilsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppProgressRcppRollRCurlRdpackreformulasrestfulrRhtslibrjsonrlangRsamtoolsRSpectraRSQLiterstatixrtracklayerRtsneS4ArraysS4VectorsS7scalesSeqinfoSeuratObjectshapeSignacsitmosnowspspamSparseArraySparseMsparseMatrixStatsstringistringrStructstringsSummarizedExperimentsurvivalsystibbletidyrtidyselecttimeDatetRNAtRNAscanImportUCSC.utilsurcautf8uwotvctrsviridisviridisLitewithrXMLxml2XVectoryamlzoo

tTEscanR User Guide
Overview | Workflow | 1. Loading the data | 2. Setup the tTEscanR object | 2.1 Pre-processing | 2.2. Defining the tTEscanR object | 3. Standard workflow | 3.1. Codon usage assessment | 3.2. Anticodon usage assessment | 3.3. Amino acid level assessment | 3.4. Theoretical Translation Efficiency (tTE) computation | 4. Differential expression analysis | 5. References
Rendered fromtTEscanR_general_use.Rmdusingknitr::rmarkdown

Last update: 2026-08-25
Started: 2025-08-27

tTEscanR tRNA-Specific Preprocessing Module
1. Overview | 2. Obtaining the tRNA matrix | 3. Identifying the optimal tRNA cutoff
Rendered fromtTEscanR_tRNA_preprocessing.Rmdusingknitr::rmarkdown

Last update: 2026-08-25
Started: 2026-06-12

tTEscanR Codon Frequency-per-Gene Matrix
Overview
Rendered fromtTEscanR_codonfreq_module.Rmdusingknitr::rmarkdown

Last update: 2026-08-25
Started: 2025-08-27

tTEscanR Visualization Module
1. Overview | 2. Configuration options | 2.1. Data transformation | 2.2. Parameters | 3. Visualization options | 4. References
Rendered fromtTEscanR_visualization_module.Rmdusingknitr::rmarkdown

Last update: 2026-08-25
Started: 2025-08-27

Readme and manuals

Help Manual

Help pageTopics
Compute Amino Acid (AA) Demand or SupplycomputeAAUsage
Compute Anticodon Usage from tRNA Gene Expression DatacomputeAnticodonUsage
Compute Codon Usage from mRNA Gene Expression DatacomputeCodonUsage
Compute the Correlation Between Mean Usage and Exonic BackgroundcomputeCorrelationBackground
Compute the DESeq2 AnalysiscomputeDEResults
Compute the Exonic Background of the Codon/Anticodon UsagecomputeExonicBackground
Compute Usage Across Conditions (Mean Usage)computeMeanUsage
Compute the Theoretical Translation Efficiency (tTE) scorecomputeTheoreticalTE
Create a tTEscanR object as a MultiAssayExperimentcreateObject
Metadata of mRNA and tRNA datadefault_tTEscanR_metadata
mRNA Expression Data Subsetdefault_tTEscanR_mRNA_data
tRNA Expression Data Subsetdefault_tTEscanR_tRNA_data
Extract Codon Composition of SequencesextractCodons
Relates Codons, Anticodons and their corresponding Amino AcidsfeaturesToAA
Compute Codon Frequency-per-Gene TablegetCodonFreq
Run Codon Usage Permutation Test (Background)getPermutationDist
Aggregates data by groupgroupConditions
Combine large matricesmergeMatrices
Assess Significance (P-value) & Corrects for Multiple Hypothesis TestingobtainSignificance
Correlation Plot: Exonic Codon Background - Mean Codon UsageplotCorrelation
Generates Visualizations from the DEA dataplotDEResults
Distribution Plot of Codon/Anticodon Usage or Amino Acid Demand/SupplyplotDistribution
Permutation PlotplotPermutation
Proportion Plot of Codon/Anticodon Usage or Amino Acid Demand/SupplyplotProportion
Distribution Plot of Codon/Anticodon Usage or Amino Acid Demand/Supply Compared to a TargetplotTargetComparison
Violin Plot Displaying tTE ScoresplotTEscore
Perform Differential Expression Analysis Using DESeq2runDEAnalysis
Runs the Theoretical Translation Efficiency (tTE) PipelinerunPipeline
Examine the Codon Pool ContributionshowPoolContribution
Transform the format of a tabletransformFormat
Filter Out Conditions With Low tRNA CutstRNAFilterCuts
Generate a tRNA expression matrixtRNAGetMatrix
Selection of the Optimal tRNA Cut CutofftRNASetCutoff
Annotate the tRNA genes from tRNA tagstRNASetGenes
Update Assay in a tTEscanR objectupdateObject