Reversed graph embedding resolves complex single-cell developmental trajectories

By Xiaojie Qiu, Qi Mao, Ying Tang, Li Wang, Raghav Chawla, Hannah A. Pliner, Cole Trapnell. 2017

87 citations recorded by the source corpus.

Organizing single cells along a developmental trajectory has emerged as a powerful tool for understanding how gene regulation governs cell fate decisions. However, learning the structure of complex single-cell trajectories with two or more branches remains a challenging computational problem. We present Monocle 2, which uses reversed graph embedding to reconstruct single-cell trajectories in a fully unsupervised manner. Monocle 2 learns an explicit principal graph to describe the data, greatly improving the robustness and accuracy of its trajectories compared to other algorithms. Monocle 2 uncovered a new, alternative cell fate in what we previously reported to be a linear trajectory for differentiating myoblasts. We also reconstruct branched trajectories for two studies of blood development, and show that loss of function mutations in key lineage transcription factors diverts cells to alternative branches on the a trajectory. Monocle 2 is thus a powerful tool for analyzing cell fate decisions with single-cell genomics.

Subfields: Molecular Biology

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Citations in the corpus

Opportunities and obstacles for deep learning in biology and medicine (2017, background): “In the future, lineage tracing could be revolutionized by using autoencoders to reduce the feature space of transcriptomic or variant data followed by algorithms to learn optimal cell differentiation trajectories [222] or by feeding cell morphology and movement into neural networks [204].”
Tumor cell biodiversity drives microenvironmental reprogramming in liver cancer (2019, methodology): “Reversed graph embedding technique was applied in this process, by projecting cells to a low dimensional space while simultaneously learning smooth tree-like manifold as well as assigning cells onto the manifold (Mao et al., 2017; Qiu et al., 2017).”
The single cell transcriptional landscape of mammalian organogenesis (2019, unknown): “Briefly, differentially expressed genes across five development stages were identified with the differentialGeneTest function of Monocle 2 57 .”