Wishbone identifies bifurcating developmental trajectories from single-cell data.
Wishbone identifies bifurcating developmental trajectories from single-cell data.
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DOI：
10.1038/nbt.3569
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发表时间：
2016-06
影响因子：
46.9
通讯作者：
Pe'er D
中科院分区：
文献类型：
--
作者：
Setty M;Tadmor MD;Reich-Zeliger S;Angel O;Salame TM;Kathail P;Choi K;Bendall S;Friedman N;Pe'er D
最近的单细胞分析技术为阐明发育途径提供了前所未有的机会。在这里，我们提出了Wishbone，定位单细胞沿着分叉的发展轨迹与高分辨率的算法。Wishbone使用多维单细胞数据（如质谱细胞术或RNA-seq数据）作为输入，并通过精确定位分叉点并将每个细胞标记为分叉前或两个分叉后细胞命运之一，根据细胞的发育进程对其进行排序。使用30通道质谱仪数据，我们表明Wishbone准确地恢复了小鼠胸腺中T细胞发育的已知阶段，包括分叉点。我们还将该算法应用于小鼠骨髓分化，并证明其推广到其他谱系。Wishbone与扩散图、SCUBA和Monocle的比较表明，它在细胞排序的准确性和分支点的正确识别方面都优于这些方法。
Recent single-cell analysis technologies offer an unprecedented opportunity to elucidate developmental pathways. Here we present Wishbone, an algorithm for positioning single cells along bifurcating developmental trajectories with high resolution. Wishbone uses multi-dimensional single-cell data, such as mass cytometry or RNA-seq data, as input and orders cells according to their developmental progression by pinpointing bifurcation points and labeling each cell as pre-bifurcation or as one of two post-bifurcation cell fates. Using 30-channel mass cytometry data, we show that Wishbone accurately recovers the known stages of T cell development in the mouse thymus, including the bifurcation point. We also apply the algorithm to mouse myeloid differentiation and demonstrate its generalization to additional lineages. A comparison of Wishbone to diffusion maps, SCUBA and Monocle shows that it outperforms these methods both in the accuracy of ordering cells and in the correct identification of branch points.