DENDRO, stands for Dna based EvolutioNary tree preDiction by scRna-seq technOlogy, is an R package, which takes scRNA-seq data for a tumor (or related somatic tissues) and accurately reconstructs its phylogeny, assigning each single cell from the single cell RNA sequencing (scRNA-seq) data to a subclone. Currently there is no phylogenetic reconstruction framework specifically designs for scRNA-seq dataset due to biological dropout (i.e. burstness), sequencing error, and technical dropout. DENDRO perfectly tackles this problem with a Bayesian framework (Beta-Binomial), and achieves high clustering accuracy .
In addition, before conducting a single cell RNA-seq experiment on a tumor sample, it is important to project how subclone detection power depends on the number of cells sequenced and the coverage per cell. To facilitate experiment design, we developed a tool, DENDROplan, that predicts the expected clustering accuracy by DENDRO given sequencing parameters. As a result, researchers can design experiment parameters, such as sequencing depth and number of cells, based on DENDROplan's prediction.