scDD - Mixture modeling of single-cell RNA-seq data to identify genes with differential distributions
This package implements a method to analyze single-cell RNA- seq Data utilizing flexible Dirichlet Process mixture models. Genes with differential distributions of expression are classified into several interesting patterns of differences between two conditions. The package also includes functions for simulating data with these patterns from negative binomial distributions.
Last updated
immunooncologybayesianclusteringrnaseqsinglecellmultiplecomparisonvisualizationdifferentialexpression
8.32 score 35 stars 79 scripts 702 downloadsdmrseq - Detection and inference of differentially methylated regions from Whole Genome Bisulfite Sequencing
This package implements an approach for scanning the genome to detect and perform accurate inference on differentially methylated regions from Whole Genome Bisulfite Sequencing data. The method is based on comparing detected regions to a pooled null distribution, that can be implemented even when as few as two samples per population are available. Region-level statistics are obtained by fitting a generalized least squares (GLS) regression model with a nested autoregressive correlated error structure for the effect of interest on transformed methylation proportions.
Last updated
immunooncologydnamethylationepigeneticsmultiplecomparisonsoftwaresequencingdifferentialmethylationwholegenomeregressionfunctionalgenomics
6.50 score 1 dependents 149 scripts 890 downloadsdecemedip - hierarchical Bayesian modeling for cell type deconvolution of immunoprecipitation-based DNA methylome
The R package decemedip is a novel computational paradigm developed for inferring the relative abundances of cell types and tissues measure by methylated DNA immunoprecipitation sequencing (MeDIP-Seq). This paradigm allows using reference data from other technologies such as microarray or WGBS.
Last updated
softwareimmunooncologydnamethylationepigeneticssequencingwholegenomebayesianbayesian-data-analysisbayesian-inferencebioinformaticsdna-methylationdna-methylation-dataepigenomicsgenerative-modelomicsrstanstanonetbbcpp
5.54 score 4 stars 43 scripts 226 downloads
vmrseq - Probabilistic Modeling of Single-cell Methylation Heterogeneity
High-throughput single-cell measurements of DNA methylation allows studying inter-cellular epigenetic heterogeneity, but this task faces the challenges of sparsity and noise. We present vmrseq, a statistical method that overcomes these challenges and identifies variably methylated regions accurately and robustly.
Last updated
softwareimmunooncologydnamethylationepigeneticssinglecellsequencingwholegenomecomputational-biologydimensionality-reductionepigenomics-workflowhidden-markov-modelprobabilistic-models
5.22 score 11 stars 7 scripts 265 downloads