colocalization: Normalized Spatial Intensity Correlation

Calculate the colocalization index, NSInC, in two different ways as described in the paper (Liu et al., 2019. Manuscript submitted for publication.) for multiple-species spatial data which contain the precise locations and membership of each spatial point. The two main functions are nsinc.d() and nsinc.z(). They provide the Pearson’s correlation coefficients of signal proportions in different memberships within a concerned proximity of every signal (or every base signal if single direction colocalization is considered) across all (base) signals using two different ways of normalization. The proximity sizes could be an individual value or a range of values, where the default ranges of values are different for the two functions.

Version:	1.0.2
Depends:	R (≥ 2.10)
Imports:	utils, stats, ggplot2
Suggests:	testthat, rgl
Published:	2020-09-21
DOI:	10.32614/CRAN.package.colocalization
Author:	Jiahui Xu, Xueyan Liu, Lin Li, Cheng Cheng, Hui Zhang
Maintainer:	Hui Zhang <hzhang at northwestern.edu>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	colocalization results

Documentation:

Reference manual:

colocalization.pdf

Downloads:

Package source:	colocalization_1.0.2.tar.gz
Windows binaries:	r-devel: colocalization_1.0.2.zip, r-release: colocalization_1.0.2.zip, r-oldrel: colocalization_1.0.2.zip
macOS binaries:	r-release (arm64): colocalization_1.0.2.tgz, r-oldrel (arm64): colocalization_1.0.2.tgz, r-release (x86_64): colocalization_1.0.2.tgz, r-oldrel (x86_64): colocalization_1.0.2.tgz
Old sources:	colocalization archive

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