Tree-ensemble analysis assesses presence of multifurcations in single cell data.

Will Macnair,Laura De Vargas Roditi,Stefan Ganscha,Manfred Claassen

doi:10.15252/msb.20188552

Abstract

We introduce TreeTop, an algorithm for single cell data analysis to identify and assign a branching score to branch points in biological processes which may have multi‐level branching hierarchies. We demonstrate branch point identification for processes with varying topologies, including T‐cell maturation, B‐cell differentiation and hematopoiesis. Our analyses are consistent with recent experimental studies suggesting a shallower hierarchy of differentiation events in hematopoiesis, rather than the classical multi‐level hierarchy.

Highlights

Many important biological processes, such as differentiation in developmental and immune biology, and clonal evolution in cancer, can be conceived of as bi- or multi-furcated cellular state trajectories
High-dimensional single cell technologies, such as single cell RNA sequencing (Tang et al, 2009) and mass cytometry (Bendall et al, 2014), constitute widely used tools to investigate such opposing models of differentiation, and other branching processes. These technologies allow the evaluation of the state of single cells, i.e. the transcriptional or proteomic abundance profile in the case of single cell RNA sequencing or mass cytometry, respectively
Biological processes can be conceived of as trajectories through state space: ordered sequences of cellular states that can either be derived from time series or reconstructed from non-time series single cell data (Stegle et al, 2015)

Summary

Introduction

Many important biological processes, such as differentiation in developmental and immune biology, and clonal evolution in cancer, can be conceived of as bi- or multi-furcated cellular state trajectories. Monocle fits smoothed trees to a low-dimensional representation of single cell data, where branch points in the tree are assumed to correspond to branch points in the data (Trapnell et al, 2014; Qiu et al, 2017). P-Creode fits multiple trees to the data, uses the data to smooth them, identifies the tree which is most central within these (Herring et al, 2017) These algorithms can all (with the exception of SCUBA, which requires time annotations) return branch points regardless of the actual evidence in the data, and any decision on the presence or absence of a branch point must be made by the user

Results and Discussion

Materials and Methods

Methods and Protocols