Model Gene Expression Dynamics with Spline-Based NB GLMs, GEEs, & GLMMs

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Documentation for package ‘scLANE’ version 1.0.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

backward_sel_WIC	Backward selection function for MARGE - uses the Wald information criterion (WIC).
biasCorrectGEE	Bias-correct the GEE sandwich variance-covariance matrix.
bootstrapRandomEffects	Generate bootstrapped confidence intervals for random effects.
chooseCandidateGenes	Choose candidate genes for trajectory DE analysis.
clusterGenes	Cluster the fitted values from a set of 'scLANE' models.
createCellOffset	Create an offset vector before modeling.
createSlopeTestData	A helper function to create a dataframe of breakpoints and associated _p_-values from a 'marge' model.
embedGenes	Generate PCA & UMAP embeddings of fitted gene dynamics.
enrichDynamicGenes	Perform GSEA on dynamic genes identified by 'scLANE'.
extractBreakpoints	Identify breakpoints in a 'marge' model.
fitGLMM	Build an NB GLMM using truncated power basis functions.
geneProgramDrivers	Identify driver genes for a given gene program.
geneProgramScoring	Add per-cell module scores for gene programs.
geneProgramSignificance	Test significance of gene program enrichment across a trajectory.
getFittedValues	Generate a table of fitted values and celltype metadata for genes of interest.
getKnotDist	Pull the set of knots for dynamic genes across each lineage.
getResultsDE	Tidy the results of 'testDynamic'.
marge2	Fit 'MARGE' models of single cell counts.
max_span	Truncates the predictor variable value to exclude extreme values in knots selection.
min_span	A truncation function applied on the predictor variable for knot selection.
modelLRT	Perform a likelihood ratio test for one model against another.
nbGAM	Fit a negative-binomial GAM.
npConvolve	Convolution that matches 'np.convolve'.
plotClusteredGenes	Generate tidy results from 'clusterGenes' to use in plotting.
plotModelCoefs	Plot gene dynamics with estimated coefficients.
plotModels	Plot results of 'marge' and other models using 'ggplot2'.
print.summary.scLANE	Print method for summary.scLANE objects.
pullMARGESummary	Generate a summary of the MARGE model.
pullNullSummary	Generate a summary of the null model.
scLANE_models	An object of class 'scLANE'.
scoreTestGEE	Use a Lagrange multiplier (score) test to compare nested GEE models.
score_fun_gee	Given estimates from the null model fit and the design matrix for alternative model, find the score statistic (this is used for GEEs only).
score_fun_glm	Given estimates from the null model fit and the design matrix for alternative model, find the score statistic (this is used for GLMs only).
sim_counts	A 'SingleCellExperiment' object containing simulated counts.
sim_pseudotime	A data.frame containing ground-truth pseudotime.
smoothedCountsMatrix	Generate a smoothed matrix of gene expression using 'scLANE' models.
sortGenesHeatmap	Sort genes by where their peak expression occurs across pseudotime.
sortObservations	Sort observations by sample ID and pseudotime.
stat_out	Fits a linear regression model and calculates RSS/GCV measures (used for MARS linear models).
stat_out_score_gee_null	Calculate part of the score statistic for a GEE.
stat_out_score_glm_null	Calculate part of the score statistic for a GLM.
stripGLM	Make GLM objects much smaller.
summarizeModel	Represent a 'marge' model as a series of piecewise equations.
summary.scLANE	Summary method for scLANE objects.
testDynamic	Test whether a gene is dynamic over pseudotime.
testSlope	Test whether a gene is dynamic over a pseudotime interval.
theme_scLANE	A 'ggplot2' theme for 'scLANE'.
tp1	Truncated p-th power function (positive part).
tp2	Truncated p-th power function (negative part).
waldTestGEE	Use a Wald test to compare nested GEE models.