Package: TOAST 1.27.0

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

TOAST_1.27.0.tar.gz
TOAST_1.27.0.zip(r-4.7)TOAST_1.27.0.zip(r-4.6)TOAST_1.27.0.zip(r-4.5)
TOAST_1.27.0.tgz(r-4.6-any)TOAST_1.27.0.tgz(r-4.5-any)
TOAST_1.27.0.tar.gz(r-4.7-any)TOAST_1.27.0.tar.gz(r-4.6-any)
TOAST_1.27.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
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-1.27.0(bioc 3.24)TOAST-1.26.0(bioc 3.23)

dnamethylation geneexpression differentialexpression differentialmethylation microarray genetarget epigenetics methylationarray

8.34 score 14 stars 4 packages 120 scripts 1.1k downloads 174 mentions 16 exports 92 dependencies

Last updated from:a6f2209974. Checks:1 ERROR, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	183
linux-devel-x86_64	OK	422
source / vignettes	OK	341
linux-release-x86_64	OK	402
macos-release-arm64	OK	215
macos-oldrel-arm64	OK	248
windows-devel	OK	264
windows-release	OK	356
windows-oldrel	OK	270
wasm-release	OK	140

Exports:assignCellType cedar ChooseMarker csDeconv csTest DEVarSelect findRefinx fitModel GetPrior makeDesign MDeconv myprojectMix myRefFreeCellMix myRefFreeCellMixInitialize plotCorr Tsisal

Dependencies:abind annotate AnnotationDbi askpass Biobase BiocGenerics Biostrings bit bit64 blob cachem class cli codetools corpcor cpp11 crayon curl DBI DelayedArray doParallel dplyr e1071 EpiDISH farver fastmap forcats foreach genefilter generics GenomicRanges GGally ggplot2 ggstats glue gtable hms httr IRanges isoband iterators jsonlite KEGGREST labeling lattice lifecycle limma locfdr magrittr MASS Matrix MatrixGenerics matrixStats memoise mime nnls openssl patchwork pillar pkgconfig png prettyunits progress proxy purrr quadprog R6 RColorBrewer rlang RSQLite S4Arrays S4Vectors S7 scales Seqinfo SparseArray statmod stringi stringr SummarizedExperiment survival sys tibble tidyr tidyselect utf8 vctrs viridisLite withr XML xtable XVector

Analyses of high-throughput data from heterogeneous samples with TOAST

Ziyi Li, Hao Wu

Rendered fromTOAST.Rmdusingknitr::rmarkdownon May 30 2026.

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

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Align cell types when reference proportions are known	assignCellType
Simulated methylation 450K array data with related	beta_emp
An example dataset for partial reference-free cell composition estimation from tissue gene expression	CBS_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 data	ChooseMarker
Improve reference-free deconvolution using cross-cell type differential analysis	csDeconv
Testing differential signals for specified phenotype and cell type(s).	csTest
Feature selection for reference-free deconvolution using cross-cell type differential analysis	DEVarSelect
findRefinx	findRefinx
Fit model with proportions and phenotypes.	fitModel
Get prior knowledge for supported tissue types	GetPrior
Generate design matrix from input phenotypes and proportions.	makeDesign
Estimate cell compoisitons via partial reference-free deconvolution.	MDeconv
Replicate the function myprojectMix() from RefFreeEWAS package	myprojectMix
Replicate the function RefFreeCellMix() from RefFreeEWAS package	myRefFreeCellMix
Replicate the function RefFreeCellMixInitialize() from RefFreeEWAS package	myRefFreeCellMixInitialize
Show DE/DM state correlation between cell types	plotCorr
An example dataset for cellular proportion estimation and multiple factor design	RA_100samples
Complete Deconvolution of DNA methylation data based on TOAST and SISAL	Tsisal