Package: DeMixT 1.21.0

Shuai Guo

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 <[email protected]>, Shaolong Cao<[email protected]>, Wenyi Wang <wwang7@@mdanderson.org>

# Install 'DeMixT' in R:

install.packages('DeMixT', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

Datasets:

On BioConductor:DeMixT-1.21.0(bioc 3.20)DeMixT-1.20.0(bioc 3.19)

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

Last updated 2 months agofrom:7df08b0259

Last update: 2022-10-06
Started: 2019-02-21

Help page	Topics
batch_correction	batch_correction
Deconvolution of heterogeneous tumor samples with two or three components using expression data from RNAseq or microarray platforms	DeMixT
Estimates the proportions of mixed samples for each mixing component	DeMixT_DE
Estimates the proportions of mixed samples for each mixing component using profile likelihood gene selection	DeMixT_GS
DeMixT_preprocessing	DeMixT_preprocessing
Deconvolves expressions of each individual sample for unknown component	DeMixT_S2
detect_suspicious_sample_by_hierarchical_clustering_2comp	detect_suspicious_sample_by_hierarchical_clustering_2comp plot_dim plot_sd
Kernel function for optimizing parameters and hidden variables in DeMixT	Optimum_KernelC
scale_normalization_75th_percentile	scale_normalization_75th_percentile
Function to simulate two-component test data	simulate_2comp
Function to simulate three-component mixed cell line test data	simulate_3comp
subset_sd	subset_sd
subset_sd_gene_remaining	subset_sd_gene_remaining
Simulated two-component test data	test.data.2comp
Simulated three-component mixed cell line test data	test.data.3comp