基因表达
转录组
基因
计算生物学
生物
RNA序列
空间分析
核糖核酸
遗传学
鉴定(生物学)
基因表达谱
细胞
地理
植物
遥感
作者
Daniel Edsgärd,Per Johnsson,Rickard Sandberg
出处
期刊:Nature Methods
[Nature Portfolio]
日期:2018-03-19
卷期号:15 (5): 339-342
被引量:321
摘要
As methods for measuring spatial gene expression at single-cell resolution become available, there is a need for computational analysis strategies. We present trendsceek, a method based on marked point processes that identifies genes with statistically significant spatial expression trends. trendsceek finds these genes in spatial transcriptomic and sequential fluorescence in situ hybridization data, and also reveals significant gene expression gradients and hot spots in low-dimensional projections of dissociated single-cell RNA-seq data.
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