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.
Last updated 4 months ago
dnamethylationgeneexpressiondifferentialexpressiondifferentialmethylationmicroarraygenetargetepigeneticsmethylationarray
8.01 score 11 stars 3 dependents 104 scripts 784 downloadsRegionalST - Investigating regions of interest and performing regional cell type-specific analysis with spatial transcriptomics data
This package analyze spatial transcriptomics data through cross-regional cell type-specific analysis. It selects regions of interest (ROIs) and identifys cross-regional cell type-specific differential signals. The ROIs can be selected using automatic algorithm or through manual selection. It facilitates manual selection of ROIs using a shiny application.
Last updated 3 months ago
spatialtranscriptomicsreactomekegg
4.30 score 8 scripts 146 downloadspartCNV - Infer locally aneuploid cells using single cell RNA-seq data
This package uses a statistical framework for rapid and accurate detection of aneuploid cells with local copy number deletion or amplification. Our method uses an EM algorithm with mixtures of Poisson distributions while incorporating cytogenetics information (e.g., regional deletion or amplification) to guide the classification (partCNV). When applicable, we further improve the accuracy by integrating a Hidden Markov Model for feature selection (partCNVH).
Last updated 4 months ago
softwarecopynumbervariationhiddenmarkovmodelsinglecellclassification
4.18 score 4 scripts 136 downloads