A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics

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Documentation for package ‘DIscBIO’ version 1.2.2

• DESCRIPTION file.
• Package NEWS.

Help Pages

as.DISCBIO	Convert Single Cell Data Objects to DISCBIO.
check.format	Check format
ClassVectoringDT	Generating a class vector to be used for the decision tree analysis.
ClassVectoringDT-method	Generating a class vector to be used for the decision tree analysis.
ClustDiffGenes	ClustDiffGenes
ClustDiffGenes-method	ClustDiffGenes
Clustexp	Clustering of single-cell transcriptome data
Clustexp-method	Clustering of single-cell transcriptome data
clustheatmap	Plotting clusters in a heatmap representation of the cell distances
clustheatmap-method	Plotting clusters in a heatmap representation of the cell distances
comptSNE	Computing tSNE
comptSNE-method	Computing tSNE
customConvertFeats	Automatic Feature Id Conversion.
DEGanalysis	Determining differentially expressed genes (DEGs) between all individual clusters.
DEGanalysis-method	Determining differentially expressed genes (DEGs) between all individual clusters.
DEGanalysis2clust	Determining differentially expressed genes (DEGs) between two particular clusters.
DEGanalysis2clust-method	Determining differentially expressed genes (DEGs) between two particular clusters.
DISCBIO	The DISCBIO Class
DISCBIO-class	The DISCBIO Class
DISCBIO-class,	The DISCBIO Class
DISCBIO2SingleCellExperiment	Convert a DISCBIO object to a SingleCellExperiment.
Exprmclust	Performing Model-based clustering on expression values
Exprmclust-method	Performing Model-based clustering on expression values
FinalPreprocessing	Final Preprocessing
FinalPreprocessing-method	Final Preprocessing
FindOutliers	Inference of outlier cells
FindOutliers-method	Inference of outlier cells
foldchange.seq.twoclass.unpaired	Foldchange of twoclass unpaired sequencing data
HumanMouseGeneIds	Human and Mouse Gene Identifiers.
J48DT	J48 Decision Tree
J48DTeval	Evaluating the performance of the J48 decision tree.
Jaccard	Jaccard’s similarity
KmeanOrder	Pseudo-time ordering based on k-means clusters
KmeanOrder-method	Pseudo-time ordering based on k-means clusters
NetAnalysis	Networking analysis.
Networking	Plotting the network.
NoiseFiltering	Noise Filtering
NoiseFiltering-method	Noise Filtering
Normalizedata	Normalizing and filtering
Normalizedata-method	Normalizing and filtering
PCAplotSymbols	Plot PCA symbols
PCAplotSymbols-method	Plot PCA symbols
plotExptSNE	Highlighting gene expression in the t-SNE map
plotExptSNE-method	Highlighting gene expression in the t-SNE map
plotGap	Plotting Gap Statistics
plotGap-method	Plotting Gap Statistics
plotLabelstSNE	tSNE map with labels
plotLabelstSNE-method	tSNE map with labels
PlotMBpca	Plotting pseudo-time ordering or gene expression in Model-based clustering in PCA
PlotmclustMB	Plotting the Model-based clusters in PCA.
PlotmclustMB-method	Plotting the Model-based clusters in PCA.
plotOrderTsne	Plotting the pseudo-time ordering in the t-SNE map
plotOrderTsne-method	Plotting the pseudo-time ordering in the t-SNE map
plotSilhouette	Silhouette Plot for K-means clustering
plotSilhouette-method	Silhouette Plot for K-means clustering
plotSymbolstSNE	tSNE map for K-means clustering with symbols
plotSymbolstSNE-method	tSNE map for K-means clustering with symbols
plottSNE	tSNE map
plottSNE-method	tSNE map
PPI	Defining protein-protein interactions (PPI) over a list of genes,
prepExampleDataset	Prepare Example Dataset
pseudoTimeOrdering	Pseudo-time ordering
pseudoTimeOrdering-method	Pseudo-time ordering
rankcols	Rank columns
reformatSiggenes	Reformat Siggenes Table
replaceDecimals	Replace Decimals
resa	Resampling
retrieveURL	Retries a URL
RpartDT	RPART Decision Tree
RpartEVAL	Evaluating the performance of the RPART Decision Tree.
sammy	Significance analysis of microarrays
samr.estimate.depth	Estimate sequencing depths
valuesG1msTest	Single-cells data from a myxoid liposarcoma cell line
VolcanoPlot	Volcano Plot
wilcoxon.unpaired.seq.func	Twoclass Wilcoxon statistics