BioinformaticsBioinformaticsPeer-reviewed journal article
hoodscanR: profiling single-cell neighborhoods in spatial transcriptomics data
Ning LiuiD, Jarryd Martin, Dharmesh Dinesh BhuvaiD, Jinjin CheniD, Mengbo LiiD, Sam LeeiD, Malvika KharbandaiD, Jinming ChengiD, Ahmed MohamediD, Arutha KulasingheiD, Yunshun CheniD, Chin Wee TaniD, Fuyi LiiD, Jose Maria PoloiD, Melissa J. DavisiD
Abstract
Understanding complex cellular niches and neighborhoods have provided new insights into tissue biology. Thus, accurate neighborhood identification is crucial, yet existing methodologies often struggle to detect informative neighborhoods and generate cell-specific neighborhood profiles. To address these limitations, we developed hoodscanR, a Bioconductor package designed for neighborhood identification and downstream analyses using spatial data. Applying hoodscanR to breast and lung cancer datasets, we showcase its efficacy in conducting detailed neighborhood analyses and identify subtle transcriptional changes in tumor cells from different neighborhoods. Such analyses can help researchers gain valuable insights into disease mechanisms and potential therapeutic targets.
- organism: human
- assay: spatial transcriptomics
- research focus: cell-cell communication
- research focus: clustering
- research focus: spatial domain detection
- approach: statistical model
- Citations
- 10
- FWCI
- 14.36
- Field percentile
- top 1%
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