PuSH - Publication Server of Helmholtz Zentrum München: Model-based branching point detection in single-cell data by K-Branches clustering.

Navigation

Home

Deutsch

Research

Advanced Search

Browse by ...

... Journal

... Publication Type

... Research Data

... Publication Year

Publication overview

Support & Contact

Contact persons

Help

Data protection

Chlis, N.-K. ; Wolf, F.A. ; Theis, F.J.

Model-based branching point detection in single-cell data by K-Branches clustering.

Bioinformatics 33, 3211-3219 (2017)

Publ. Version/Full Text

Research data

DOI

PMC

	Open Access Gold (Paid Option)

Abstract
Metrics
Extra information

Motivation: The identification of heterogeneities in cell populations by utilizing single-cell technologies such as single-cell RNA-Seq, enables inference of cellular development and lineage trees. Several methods have been proposed for such inference from high-dimensional single-cell data. They typically assign each cell to a branch in a differentiation trajectory. However, they commonly assume specific geometries such as tree-like developmental hierarchies and lack statistically sound methods to decide on the number of branching events. Results: We present K-Branches, a solution to the above problem by locally fitting half-lines to single-cell data, introducing a clustering algorithm similar to K-Means. These halflines are proxies for branches in the differentiation trajectory of cells. We propose a modified version of the GAP statistic for model selection, in order to decide on the number of lines that best describe the data locally. In this manner, we identify the location and number of subgroups of cells that are associated with branching events and full differentiation, respectively. We evaluate the performance of our method on single-cell RNA-Seq data describing the differentiation of myeloid progenitors during hematopoiesis, single-cell qPCR data of mouse blastocyst development, single-cell qPCR data of human myeloid monocytic leukemia and artificial data. Availability: An R implementation of K-Branches is freely available at https://github.com/theislab/kbranches.

Altmetric

Additional Metrics?

[➜Log in]