Showing 4 of total 4 results (show query)
bioc
lemur:Latent Embedding Multivariate Regression
Fit a latent embedding multivariate regression (LEMUR) model to multi-condition single-cell data. The model provides a parametric description of single-cell data measured with treatment vs. control or more complex experimental designs. The parametric model is used to (1) align conditions, (2) predict log fold changes between conditions for all cells, and (3) identify cell neighborhoods with consistent log fold changes. For those neighborhoods, a pseudobulked differential expression test is conducted to assess which genes are significantly changed.
Maintained by Constantin Ahlmann-Eltze. Last updated 5 months ago.
transcriptomicsdifferentialexpressionsinglecelldimensionreductionregressionopenblascpp
87 stars 7.69 score 81 scriptsbioc
transformGamPoi:Variance Stabilizing Transformation for Gamma-Poisson Models
Variance-stabilizing transformations help with the analysis of heteroskedastic data (i.e., data where the variance is not constant, like count data). This package provide two types of variance stabilizing transformations: (1) methods based on the delta method (e.g., 'acosh', 'log(x+1)'), (2) model residual based (Pearson and randomized quantile residuals).
Maintained by Constantin Ahlmann-Eltze. Last updated 5 months ago.
singlecellnormalizationpreprocessingregressioncpp
21 stars 5.95 score 21 scriptsbioc
BASiCStan:Stan implementation of BASiCS
Provides an interface to infer the parameters of BASiCS using the variational inference (ADVI), Markov chain Monte Carlo (NUTS), and maximum a posteriori (BFGS) inference engines in the Stan programming language. BASiCS is a Bayesian hierarchical model that uses an adaptive Metropolis within Gibbs sampling scheme. Alternative inference methods provided by Stan may be preferable in some situations, for example for particularly large data or posterior distributions with difficult geometries.
Maintained by Alan OCallaghan. Last updated 5 months ago.
immunooncologynormalizationsequencingrnaseqsoftwaregeneexpressiontranscriptomicssinglecelldifferentialexpressionbayesiancellbiologysingle-cell-rna-seqcpp
3.78 score 1 scripts
liuy12
SCdeconR:Deconvolution of Bulk RNA-Seq Data using Single-Cell RNA-Seq Data as Reference
Streamlined workflow from deconvolution of bulk RNA-seq data to downstream differential expression and gene-set enrichment analysis. Provide various visualization functions.
Maintained by Yuanhang Liu. Last updated 10 months ago.
bulk-rna-seq-deconvolutiondeconvolutiondifferential-expressionffpegeneset-enrichment-analysisscdeconrsingle-cell
4 stars 3.60 score 4 scripts