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RaceID (version 0.2.3)

Identification of Cell Types and Inference of Lineage Trees from Single-Cell RNA-Seq Data

Description

Application of 'RaceID' allows inference of cell types and prediction of lineage trees by he StemID2 algorithm. Herman, J.S., Sagar, Grün D. (2018) .

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Version

Install

install.packages('RaceID')

Monthly Downloads

427

Version

0.2.3

License

GPL-3

Maintainer

Dominic Grc3<bc>n

Last Published

April 8th, 2021

Functions in RaceID (0.2.3)

The Ltree Class

Extract Cells on Differentiation Trajectory

Dimensional Reduction by PCA or ICA

Cell cycle markers for Mus Muscuus

Baseline gene expression variability

Gene Expression Barplot

The SCseq Class

Differential Gene Expression between Links

Inference of differentially expressed genes in a cluster

A short title line describing what the package does

Computing P-values for Link Significance

Inference of outlier cells and final clustering

Plotting a Heatmap of the Distance Matrix

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

Clustering of single-cell transcriptome data

Function for extracting genes maximal variability

Computes Medoids from a Clustering Partition

Computation of a two dimensional Fruchterman-Rheingold representation

Function for computing local gene expression averages

Function for computing local gene expression variability

createKnnMatrix

Function to create a knn matrix

Compute Expression Differences between Clusters

Function for differential expression analysis

Function for computing a background model of gene expression variability

Inference of a Lineage Graph

Function for extracting genes with elevated variability in a cluster

Plotting a dimensional reduction representation

intestinalDataSmall

Single-cell transcriptome data of intestinal epithelial cells

Compute transcriptome entropy of each cell

Computing a distance matrix for cell type inference

plotmarkergenes

Plotting a Heatmap of Marker Gene Expression

Extract Projections of all Cells from a Cluster

Dotplot of gene expression across clusters or samples

Barplot of differentially expressed genes

plotdistanceratio

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

Computation of a two dimensional t-SNE representation

Compute StemID2 score

Imputed expression matrix

Plotting the Saturation of Explained Variance

Function for infering Louvain clustering of the pruned k nearest neighbour graph

Single-cell transcriptome data of intestinal epithelial cells

Computation of a two dimensional umap representation

Function for plotting the variance of Pearson residuals

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

Function for plottinhg the background model of gene expression variability

plotsensitivity

Plot Sensitivity

Plot Cluster Silhouette

plotdiffgenesnb

Function for plotting differentially expressed genes

Heatmap of Link P-values

Function for plotting negative binomial regression

rcpp_hello_world

Simple function using Rcpp

transitionProbs

Function for the computation of transition probabilities between clusters

Random Forests-based Reclassification

Heatmap of Link Scores

Extracting filtered expression data

Function for updating a RaceID SCseq object with VarID results

Highlighting gene expression in a dimensional reduction representation

Function for plotting the baseline model of gene expression variability

StemID2 Lineage Graph

Plot Background Model

Plot Jaccard Similarities

Function for plotting transition probabilities between clusters

Plot Saturation of Within-Cluster Dispersion

Minimum Spanning Tree of RaceID3 clusters

plotoutlierprobs

Plot Outlier Probabilities

Enrichment of cells on inter-cluster links

Plot labels in a dimensional reduction representation

Function inferring a pruned knn matrix

Plotting groups as different symbols in a dimensional reduction representation

Compute Cell Projections for Randomized Background Distribution

Linear Regression of Sources of Variability

Compute transcriptome entropy of each cell