README.md

Aodav

Advanced Omics Data Analysis and Visualization (Aodav). Highly adaptable to Seurat objects for single-cell RNA-seq data.

Functions

Gene selection

pcaGenes: find top gene list associted most with the first three dimensions using PCA analysis.

pwDEG: thoroughly find differentially expressed genes (DEGs) for any pairs of cell clusters.

conservedMarkers: find conserved marker genes for each cluster in two conditions.

markerSelect: select representative genes according to differential expression in each cluster, usefull for downstream visualization.

GO enrichment

DEGsEnrich: perfrom GO enrichment analysis for each cluster specifically expressed genes by batching enrichR.

viewGO: visualize GO enrichment results by UP, DOWN and Total genes for each cell cluster.

viewMergeGO: simultaneously dispaly the GO enrichments in all cell clusters by merging top representative terms.

ROC socre

addROC: calculate ROC score for each gene to estimate the capability for separating cell clusters.

Celluar composition (Ro/e)

Roe: evaluate the cellular composition among samples as compared to controls by adopting Chi-square test.

Projection of single cells

cellMap: map single cells to each cell clusters using scRNA-seq data. This function embeds 'scmap' tool and improves to enable multiple rounds of projection to increase the mapping accuracy of cells with similar experssion patterns.

Visualization

geneHeatmap: combined heatmap and clustering for customized display of gene expression dynamics through cell types, given selected gene list.

volcanoPlot: volcano plot of differentially expressed genes between two groups of cells. It supports displaying gene symbols on the plot.

barPlot: bar plot shows gene expression of individual cells in each cell group.

boxPlot: box plot shows gene expression of cell groups for a gene set or individual genes.

Install

devtools::install_github("zhupinglab/Aodav")



zhupinglab/Aodav documentation built on June 10, 2019, 2:31 a.m.