Man pages for kgellatl/SignallingSingleCell
Network Analysis for single cell RNA sequencing Data (sc-RNASeq)

calc_agg_bulkCalculate mean expression values across pData values
calc_libsizeCalculate Library Size
calc_rl_networkIdentifies all R / L interactions
check_packagecheck_package
cluster_scCluster Single Cell
construct_ex_scConstruct Expression Set Class
dim_reduceDimension Reduction
edgeRDEThis will run edgeR to find differentially expressed genes....
filter_rl_networkIdentifies all R / L interactions
findDEgenesThis will perform differential expression using edgeR for...
findDEmarkersThis will perform differential expression using edgeR to find...
flow_filterConstruct Expression Set Class
flow_svmFlow Support Vector Machine
id_markersID markers
id_rlidentify receptors and ligands
merge_ex_scThis will merge pData and fData
norm_scNormalization
plot_densityPlot Density
plot_density_ridgePlot Density
plot_gene_dotsPlot of genes by pData variable
plot_heatmapPlots a heatmap
plot_rl_networkIdentifies all R / L interactions
plot_rl_summaryIdentifies all R / L interactions
plot_scatterCreate a Scatter Plot
plot_tsne_genetSNE Plot on a gene or genes
plot_tsne_metadatatSNE Plot on metadata
plot_violinThis will create a violin plot
plotViolinThis will create a violin plot
pre_filterFilter Data
Receptor_Ligand_DataReceptor Ligand Data
return_markersReturn markers
save_ggplotSave plot
search_geneSearch Gene
subset_ex_scThis will setset your expression set by some variable in...
subset_genesSubset Genes
kgellatl/SignallingSingleCell documentation built on July 15, 2018, 1:43 p.m.