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RaceID (version 0.2.6)

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

0.2.6

License

GPL-3

Maintainer

Dominic Grc3<bc>n

Last Published

August 19th, 2022

Functions in RaceID (0.2.6)

The Ltree Class

Function for computing local gene expression variability

Function for computing local gene expression averages

Cell cycle markers for Mus Muscuus

Extract Cells on Differentiation Trajectory

Plotting a Heatmap of the Distance 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.

Computation of a two dimensional umap representation

Clustering of single-cell transcriptome data

Function for computing a background model of gene expression variability

Compute transcriptome entropy of each cell

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

Computation of a two dimensional Fruchterman-Rheingold representation

Function for differential expression analysis

diffNoisyGenesTB

Function for extracting genes with differential biological variability in a cluster

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

Extracting filtered expression data

Compute StemID2 score

Computing a distance matrix for cell type inference

Inference of outlier cells and final clustering

Computation of a two dimensional t-SNE representation

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

Computing P-values for Link Significance

Computes Medoids from a Clustering Partition

createKnnMatrix

Function to create a knn matrix

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

Extract Projections of all Cells from a Cluster

Function for filtering count data

Compute Expression Differences between Clusters

Function for infering clustering of the pruned k nearest neighbour graph

Function for extracting genes with elevated variability in a cluster

Noise-expression scatter plot

Function for inspecting pruned k-nearest neighbourhoods

Function for plotting differentially variable genes

Plotting the Saturation of Explained Variance

Imputed expression matrix

Inference of a Lineage Graph

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.

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

getFilteredCounts

Function for filtering count data

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

Plotting function for posterior checks

maxNoisyGenesTB

Function for extracting genes maximal variability

Function to plot the selected number of principal components

Function for plotting negative binomial regression

Function for extracting genes maximal variability

Prior function for maximum a posterior inference

Plot Background Model

Plotting noise dependence on total UMI count

Heatmap of Link Scores

plotdistanceratio

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

Plotting groups as different symbols in a dimensional reduction representation

Linear Regression of Sources of Variability

Function for plotting transition probabilities between clusters

Highlighting gene expression in a dimensional reduction representation

plotdiffgenesnb

Function for plotting differentially expressed genes

Plotting a dimensional reduction representation

violinMarkerPlot

Violin plot of marker gene expression or noise

Inference of differentially expressed genes in a cluster

Compute Cell Projections for Randomized Background Distribution

Posterior probability

Function for pruning k-nearest neighborhoods based on neighborhood overlap

Highlighting feature values in a dimensional reduction representation

Plot Cluster Silhouette

Compute transcriptome entropy of each cell

Minimum Spanning Tree of RaceID3 clusters

Boxplots for features across clusters

Plot of Mean-Variance dependence and various fits

Function for plottinhg the background model of gene expression variability

Plot Jaccard Similarities

Function for plotting the baseline model of gene expression variability

plotsensitivity

Plot Sensitivity

rcpp_hello_world

Simple function using Rcpp

StemID2 Lineage Graph

Plot Saturation of Within-Cluster Dispersion

Noise-related quantaties of local pruned k-nearest neighbourhoods

Enrichment of cells on inter-cluster links

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

Dotplot of gene expression across clusters or samples

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

Heatmap of Link P-values

Plot labels in a dimensional reduction representation

Random Forests-based Reclassification

Posterior check of the model

Barplot of differentially expressed genes

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

intestinalDataSmall

Single-cell transcriptome data of intestinal epithelial cells

Plotting pseudo-time in dimensional reduction representation

Single-cell transcriptome data of intestinal epithelial cells

plotoutlierprobs

Plot Outlier Probabilities

plotmarkergenes

Plotting a Heatmap of Marker Gene Expression

Function for updating a RaceID SCseq object with VarID results

Function for plotting the variance of Pearson residuals

Extract pseudo-time order of cells along a trajectory

transitionProbs

Function for the computation of transition probabilities between clusters

Function inferring a pruned knn matrix

Baseline gene expression variability

Gene Expression Barplot

A short title line describing what the package does

The SCseq Class

Dimensional Reduction by PCA or ICA

Function for calculating total variance from VarID fit

Function for calculating the total variance fit

Function for calculating an aggregated dispersion parameter

Differential Gene Expression between Links