Package: DeMixT 2.1.0

Ruonan Li

DeMixT: Cell type-specific deconvolution of heterogeneous tumor samples with two or three components using expression data from RNAseq or microarray platforms

DeMixT is a software package that performs deconvolution on transcriptome data from a mixture of two or three components.

Authors:Zeya Wang [aut], Shaolong Cao [aut], Liyang Xie [aut], Ruonan Li [cre], Wenyi Wang [aut]

DeMixT_2.1.0.tar.gz
DeMixT_2.1.0.zip(r-4.7-x86_64)DeMixT_2.1.0.zip(r-4.7-arm64)DeMixT_2.1.0.zip(r-4.6-x86_64)DeMixT_2.1.0.zip(r-4.6-arm64)DeMixT_2.1.0.zip(r-4.5-x86_64)
DeMixT_2.1.0.tgz(r-4.6-x86_64)DeMixT_2.1.0.tgz(r-4.6-arm64)DeMixT_2.1.0.tgz(r-4.5-x86_64)DeMixT_2.1.0.tgz(r-4.5-arm64)
DeMixT_2.1.0.tar.gz(r-4.7-arm64)DeMixT_2.1.0.tar.gz(r-4.7-x86_64)DeMixT_2.1.0.tar.gz(r-4.6-arm64)DeMixT_2.1.0.tar.gz(r-4.6-x86_64)
DeMixT_2.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
DeMixT/json (API)

# Install 'DeMixT' in R:
install.packages('DeMixT', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On BioConductor:DeMixT-2.1.0(bioc 3.24)DeMixT-2.0.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

softwarestatisticalmethodclassificationgeneexpressionsequencingmicroarraytissuemicroarraycoveragecppopenmp

5.82 score 33 scripts 523 downloads 5 mentions 18 exports 92 dependencies

Last updated from:7874c43e7a. Checks:1 ERROR, 13 NOTE, 2 OK. Indexed: yes.

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bioc-checksERROR192
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linux-devel-x86_64NOTE371
source / vignettesOK301
linux-release-arm64NOTE309
linux-release-x86_64NOTE423
macos-release-arm64NOTE323
macos-release-x86_64NOTE598
macos-oldrel-arm64NOTE256
macos-oldrel-x86_64NOTE545
windows-devel-arm64NOTE384
windows-devel-x86_64NOTE531
windows-release-arm64NOTE573
windows-release-x86_64NOTE437
windows-oldrel-x86_64NOTE359
wasm-releaseOK155

Exports:batch_correctionDeMixNBDeMixNB_preprocessingDeMixTDeMixT_DEDeMixT_GSDeMixT_preprocessingDeMixT_S2detect_suspicious_sample_by_hierarchical_clustering_2compgene_selection_DEOptimum_KernelCplot_dimplot_sdscale_normalization_75th_percentilesimulate_2compsimulate_3compsubset_sdsubset_sd_gene_remaining

Dependencies:abindannotateAnnotationDbiaskpassbase64encBHBiobaseBiocBaseUtilsBiocGenericsBiocParallelBiostringsbitbit64blobcachemclicodetoolscpp11crayoncurlDBIDelayedArraydendextendedgeRevdfarverfastmapfitdistrplusformatRfutile.loggerfutile.optionsgenefiltergenericsGenomicRangesggplot2glueGPArotationgridExtragtablehttrIRangesisobandjsonliteKEGGRESTKernSmoothlabelinglambda.rlatticelifecyclelimmalocfitmagrittrMASSMatrixmatrixcalcMatrixGenericsmatrixStatsmemoisemgcvmimemnormtnlmeopensslpbapplypkgconfigpngpsychR6RColorBrewerRcpprlangRSQLiteS4ArraysS4VectorsS7scalesSeqinfosnowSparseArraystatmodSummarizedExperimentsurvivalsvasystruncdistvctrsviridisviridisLitewithrXMLxtableXVector

A Vignette for DeMixT
Introduction | Feature Description | Installation | Functions | Methods | Model | The DeMixT algorithm for deconvolution | Examples | Simulated two-component data | Simulated three-component data | Real data: PRAD in TCGA dataset | Obtain raw read counts for the tumor and normal RNAseq data | Data preprocessing | Deconvolution using DeMixT | Deconvolution using normal reference samples from GTEx | Reference | Session Info

Last update: 2026-03-26
Started: 2026-03-26

DeMixNB: Deconvolution for Sparse Count Data
Introduction | Feature Description | Functions | Methods | Model | The DeMixNB Algorithm for Deconvolution | Real data Example | Spatially Resolved Transcriptomics | Results | Session Information

Last update: 2026-03-26
Started: 2026-03-26