NBLAST: Rapid, Sensitive Comparison of Neuronal Structure and Construction of Neuron Family Databases

被引:153
作者
Costa, Marta [1 ,2 ]
Manton, James D. [1 ,5 ]
Ostrovsky, Aaron D. [1 ,6 ]
Prohaska, Steffen [1 ,3 ]
Jefferis, Gregory S. X. E. [1 ,4 ]
机构
[1] MRC, Div Neurobiol, Mol Biol Lab, Cambridge CB2 0QH, England
[2] Univ Cambridge, Dept Genet, Downing St, Cambridge CB2 3EH, England
[3] ZIB, D-14195 Berlin, Germany
[4] Univ Cambridge, Dept Zool, Downing St, Cambridge CB2 3EJ, England
[5] Univ Cambridge, Dept Chem Engn & Biotechnol, Cambridge CB2 3RA, England
[6] Heidelberg Univ, Ctr Organismal Studies, D-69120 Heidelberg, Germany
基金
欧洲研究理事会; 英国医学研究理事会;
关键词
FLY DROSOPHILA-MELANOGASTER; MUSHROOM BODY; PROJECTION NEURONS; GANGLION-CELLS; IMAGE-ANALYSIS; OLFACTORY MAP; MOUSE RETINA; BRAIN; CLASSIFICATION; REPRESENTATION;
D O I
10.1016/j.neuron.2016.06.012
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Neural circuit mapping is generating datasets of tens of thousands of labeled neurons. New computational tools are needed to search and organize these data. We present NBLAST, a sensitive and rapid algorithm, for measuring pairwise neuronal similarity. NBLAST considers both position and local geometry, decomposing neurons into short segments; matched segments are scored using a probabilistic scoring matrix defined by statistics of matches and non-matches. We validated NBLAST on a published dataset of 16,129 single Drosophila neurons. NBLAST can distinguish neuronal types down to the finest level (single identified neurons) without a priori information. Cluster analysis of extensively studied neuronal classes identified new types and unreported topographical features. Fully automated clustering organized the validation dataset into 1,052 clusters, many of which map onto previously described neuronal types. NBLAST supports additional query types, including searching neurons against transgene expression patterns. Finally, we show that NBLAST is effective with data from other invertebrates and zebrafish.
引用
收藏
页码:293 / 311
页数:19
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