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RaceID (version 0.4.2)

Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data

Description

Application of 'RaceID' allows inference of cell types and prediction of lineage trees by the 'StemID2' algorithm (Herman, J.S., Sagar, Grun D. (2018) ). 'VarID2' is part of this package and allows quantification of biological gene expression noise at single-cell resolution (Rosales-Alvarez, R.E., Rettkowski, J., Herman, J.S., Dumbovic, G., Cabezas-Wallscheid, N., Grun, D. (2023) ).

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Install

install.packages('RaceID')

Monthly Downloads

374

Version

0.4.2

License

GPL-3

Maintainer

Dominic Grc3<bc>n

Last Published

June 16th, 2026

Functions in RaceID (0.4.2)

Function for computing local gene expression averages

Computation of a two dimensional Fruchterman-Rheingold representation

Computes Medoids from a Clustering Partition

Computation of a two dimensional umap representation

Computation of a two dimensional t-SNE representation

Compute transcriptome entropy of each cell

Function for differential expression analysis

Compute Expression Differences between Clusters

Computing a distance matrix for cell type inference

Function for filtering count data

diffNoisyGenesTB

Function for extracting genes with differential biological variability in a cluster

Function for infering clustering of the pruned k nearest neighbour graph

Function for extracting genes with elevated variability in a cluster

Imputed expression matrix

Extract all genes for a module in a FateID self-orgaizing map

Fitting a Gamma distribution to global cell-to-cell variability

fitLogVarLogMean

Second order polynomial fit of mean-variance dependence This function corrects for the systematic dependence of the variance on the mean by a local regression.

getFilteredCounts

Function for filtering count data

intestinalDataSmall

Single-cell transcriptome data of intestinal epithelial cells

Extract Projections of all Cells from a Cluster

createKnnMatrix

Function to create a knn matrix

Function for regressing out the mean-variance dependence. This function corrects for the systematic dependence of the variance on the mean by a local regression.

Computing P-values for Link Significance

Inference of a Lineage Graph

Extracting filtered expression data

Compute StemID2 score

Function for plottinhg the background model of gene expression variability

Plotting noise-related quantaties of local pruned k-nearest neighbourhoods

Function for plotting differentially variable genes

Single-cell transcriptome data of intestinal epithelial cells

Function for inspecting pruned k-nearest neighbourhoods

Highlighting feature values in a dimensional reduction representation

Noise-expression scatter plot

Plot of Mean-Variance dependence and various fits

StemID2 Lineage Graph

Function for plotting transition probabilities between clusters

Plotting noise dependence on total UMI count

Plot Saturation of Within-Cluster Dispersion

plotoutlierprobs

Plot Outlier Probabilities

Plot Cluster Silhouette

Function for extracting a filtered expression matrix from a RaceID SCseq object

Boxplots for features across clusters

Dotplot of gene expression across clusters or samples

Function for computing a fit to the baseline of gene expression variability

plotdistanceratio

Histogram of Cell-to-Cell Distances in Real versus Embedded Space

Plotting function for posterior checks

Plot Jaccard Similarities

Compute Cell Projections for Randomized Background Distribution

Compute transcriptome entropy of each cell

plotsensitivity

Plot Sensitivity

Highlighting gene expression in a dimensional reduction representation

Function for plotting negative binomial regression

Plotting pseudo-time in dimensional reduction representation

Enrichment of cells on inter-cluster links

Function inferring a pruned knn matrix

Extract pseudo-time order of cells along a trajectory

Plot labels in a dimensional reduction representation

Function for plotting the variance of Pearson residuals

Scatter plot of two noise-related quantaties of local pruned k-nearest neighbourhoods

violinMarkerPlot

Violin plot of marker gene expression or noise

transitionProbs

Function for the computation of transition probabilities between clusters

Noise-related quantaties of local pruned k-nearest neighbourhoods

Posterior check of the model

plotmarkergenes

Plotting a Heatmap of Marker Gene Expression

Plotting a dimensional reduction representation

Plotting the Saturation of Explained Variance

plotdiffgenesnb

Function for plotting differentially expressed genes

Function for fitting a negative binomial noise model of technical and biological variability

Inference of outlier cells and final clustering

Function for extracting genes maximal variability

Function for computing a background model of gene expression variability

Function for fitting a negative binomial noise model of technical and biological variability

Random Forests-based Reclassification

rcpp_hello_world

Simple function using Rcpp

Minimum Spanning Tree of RaceID3 clusters

Plotting groups as different symbols in a dimensional reduction representation

maxNoisyGenesTB

Function for extracting genes maximal variability

Function for plotting the baseline model of gene expression variability

Function to plot the selected number of principal components

Plot Background Model

Heatmap of Link Scores

Heatmap of Link P-values

Barplot of differentially expressed genes

Prior function for maximum a posterior inference

Posterior probability

Linear Regression of Sources of Variability

Function for updating a RaceID SCseq object with VarID results

The Ltree Class

Differential Gene Expression between Links

Baseline gene expression variability

Function for calculating an aggregated dispersion parameter

Gene Expression Barplot

Dimensional Reduction by PCA or ICA

The SCseq Class

Converting a Seurat object to a RaceID/VarID object

Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data

Function for calculating total variance from VarID fit

Clustering of single-cell transcriptome data

Inference of differentially expressed genes in a cluster

Extract Cells on Differentiation Trajectory

Function for pruning k-nearest neighborhoods based on neighborhood overlap

Function for fitting a negative binomial noise model of technical and biological variability across cells in pruned k-nearest neighbourhoods.

Function for calculating the total variance fit

Plotting a Heatmap of the Distance Matrix

Function for computing local gene expression variability

Cell cycle markers for Mus Muscuus