Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics

Kelly Street, Davide Risso, Russell B. Fletcher, Diya Das, John Ngai, Nir Yosef, Elizabeth Purdom and Sandrine Dudoit

BMC Genomics
June 18, 2018

Single-cell transcriptomics allows researchers to investigate complex communities of heterogeneouscells. It can be applied to stem cells and their descendants in order to chart the progression from multipotentprogenitors to fully differentiated cells. While a variety of statistical and computational methods have been proposedfor inferring cell lineages, the problem of accurately characterizing multiple branching lineages remains difficultto solve.

We introduce Slingshot, a novel method for inferring cell lineages and pseudotimes from single-cell geneexpression data. In previously published datasets, Slingshot correctly identifies the biological signal for one to threebranching trajectories. Additionally, our simulation study shows that Slingshot infers more accurate pseudotimes thanother leading methods.

Slingshot is a uniquely robust and flexible tool which combines the highly stable techniques necessaryfor noisy single-cell data with the ability to identify multiple trajectories. Accurate lineage inference is a critical step inthe identification of dynamic temporal gene expression.

Featured Fellows

Diya Das

Molecular & Cell Biology

Sandrine Dudoit

Statistics, Epidemiology and Biostatistics, School of Public Health, UC Berkeley
BIDS Faculty Council