PT  - JOURNAL ARTICLE
AU  - Manu Setty
AU  - Vaidotas Kiseliovas
AU  - Jacob Levine
AU  - Adam Gayoso
AU  - Linas Mazutis
AU  - Dana Pe’er
TI  - Palantir characterizes cell fate continuities in human hematopoiesis
AID  - 10.1101/385328
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 385328
4099  - http://biorxiv.org/content/early/2018/08/05/385328.short
4100  - http://biorxiv.org/content/early/2018/08/05/385328.full
AB  - Recent studies using single cell RNA-seq (scRNA-seq) data derived from differentiating systems have raised fundamental questions regarding the discrete vs continuous nature of both differentiation and cell fate. Here we present Palantir, an algorithm that models trajectories of differentiating cells, which treats cell-fate as a probabilistic process, and leverages entropy to measure the changing nature of cell plasticity along the differentiation trajectory. Palantir generates a high resolution pseudotime ordering of cells, and assigns each cell state with its probability to differentiate into each terminal state. We apply Palantir to human bone marrow scRNA-seq data and detect key landmarks of hematopoietic differentiation. Palantir’s resolution enables identification of key transcription factors driving lineage fate choices, as these TFs closely track when cells lose plasticity. We demonstrate that Palantir is generalizable to diverse tissue types and well-suited to resolve less studied differentiating systems.