bioRxivNeurosciencePreprint
CUBIC-Cloud: An Integrative Computational Framework Towards Community-Driven Whole-Mouse-Brain Mapping
Tomoyuki ManoiD, Ken Murata, Kazuhiro KoniD, Chika Shimizu, Hiroaki Ono, Shoi ShiiD, Rikuhiro G. YamadaiD, Kazunari MiyamichiiD, Etsuo A. SusakiiD, Kazushige TouharaiD, Hiroki R. UedaiD
Abstract
Recent advancements in tissue clearing technologies have offered unparalleled opportunities for researchers to explore the whole mouse brain at cellular resolution. With the expansion of this experimental technique, however, a scalable and easy-to-use computational tool is in demand to effectively analyze and integrate whole-brain mapping datasets. To that end, here we present CUBIC-Cloud, a cloud-based framework to quantify, visualize and integrate whole mouse brain data. CUBIC-Cloud is a fully automated system where users can upload their whole-brain data, run analysis and publish the results. We demonstrate the generality of CUBIC-Cloud by a variety of applications. First, we investigated brain-wide distribution of PV, Sst, ChAT, Th and Iba1 expressing cells. Second, A{beta} plaque deposition in AD model mouse brains were quantified. Third, we reconstructed neuronal activity profile under LPS-induced inflammation by c-Fos immunostaining. Last, we show brain-wide connectivity mapping by pseudo-typed Rabies virus. Together, CUBIC-Cloud provides an integrative platform to advance scalable and collaborative whole-brain mapping.
- organism: mouse
- assay: spatial transcriptomics
- research focus: clustering
- research focus: cell type annotation
- research focus: spatial domain detection
- research focus: database / resource
- approach: experimental assay
- Citations
- 7
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