Package: TOAST 1.25.0

Ziyi Li

TOAST: Tools for the analysis of heterogeneous tissues

This package is devoted to analyzing high-throughput data (e.g. gene expression microarray, DNA methylation microarray, RNA-seq) from complex tissues. Current functionalities include 1. detect cell-type specific or cross-cell type differential signals 2. tree-based differential analysis 3. improve variable selection in reference-free deconvolution 4. partial reference-free deconvolution with prior knowledge.

Authors:Ziyi Li and Weiwei Zhang and Luxiao Chen and Hao Wu

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TOAST/json (API)
NEWS

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

Bug tracker:https://github.com/ziyili20/toast/issues

Datasets:
  • beta_emp - Simulated methylation 450K array data with related
  • CBS_PBMC_array - An example dataset for partial reference-free cell composition estimation from tissue gene expression
  • RA_100samples - An example dataset for cellular proportion estimation and multiple factor design

On BioConductor:TOAST-1.25.0(bioc 3.23)TOAST-1.24.0(bioc 3.22)

dnamethylationgeneexpressiondifferentialexpressiondifferentialmethylationmicroarraygenetargetepigeneticsmethylationarray

8.30 score 14 stars 4 packages 120 scripts 996 downloads 174 mentions 16 exports 92 dependencies

Last updated from:dab62cfc0c. Checks:1 ERROR, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksERROR190
linux-devel-x86_64OK407
source / vignettesOK314
linux-release-x86_64OK423
macos-release-arm64OK229
macos-oldrel-arm64OK213
windows-develOK312
windows-releaseOK318
windows-oldrelOK326
wasm-releaseOK154

Exports:assignCellTypecedarChooseMarkercsDeconvcsTestDEVarSelectfindRefinxfitModelGetPriormakeDesignMDeconvmyprojectMixmyRefFreeCellMixmyRefFreeCellMixInitializeplotCorrTsisal

Dependencies:abindannotateAnnotationDbiaskpassBiobaseBiocGenericsBiostringsbitbit64blobcachemclassclicodetoolscorpcorcpp11crayoncurlDBIDelayedArraydoParalleldplyre1071EpiDISHfarverfastmapforcatsforeachgenefiltergenericsGenomicRangesGGallyggplot2ggstatsgluegtablehmshttrIRangesisobanditeratorsjsonliteKEGGRESTlabelinglatticelifecyclelimmalocfdrmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemimennlsopensslpatchworkpillarpkgconfigpngprettyunitsprogressproxypurrrquadprogR6RColorBrewerrlangRSQLiteS4ArraysS4VectorsS7scalesSeqinfoSparseArraystatmodstringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselectutf8vctrsviridisLitewithrXMLxtableXVector

Analyses of high-throughput data from heterogeneous samples with TOAST

Rendered fromTOAST.Rmdusingknitr::rmarkdownon Apr 05 2026.

Last update: 2022-08-14
Started: 2019-05-21

Readme and manuals

Help Manual

Help pageTopics
Align cell types when reference proportions are knownassignCellType
Simulated methylation 450K array data with relatedbeta_emp
An example dataset for partial reference-free cell composition estimation from tissue gene expressionCBS_PBMC_array
Testing cell type specific differential signals for specified phenotype by considering DE/DM state corrleation between cell types.cedar
Choose cell type-specific markers from pure cell type profiles or single cell dataChooseMarker
Improve reference-free deconvolution using cross-cell type differential analysiscsDeconv
Testing differential signals for specified phenotype and cell type(s).csTest
Feature selection for reference-free deconvolution using cross-cell type differential analysisDEVarSelect
findRefinxfindRefinx
Fit model with proportions and phenotypes.fitModel
Get prior knowledge for supported tissue typesGetPrior
Generate design matrix from input phenotypes and proportions.makeDesign
Estimate cell compoisitons via partial reference-free deconvolution.MDeconv
Replicate the function myprojectMix() from RefFreeEWAS packagemyprojectMix
Replicate the function RefFreeCellMix() from RefFreeEWAS packagemyRefFreeCellMix
Replicate the function RefFreeCellMixInitialize() from RefFreeEWAS packagemyRefFreeCellMixInitialize
Show DE/DM state correlation between cell typesplotCorr
An example dataset for cellular proportion estimation and multiple factor designRA_100samples
Complete Deconvolution of DNA methylation data based on TOAST and SISALTsisal