Package: colocalization 1.0.2

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.

Authors:Jiahui Xu, Xueyan Liu, Lin Li, Cheng Cheng, Hui Zhang

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colocalization.pdf |colocalization.html
colocalization/json (API)

# Install 'colocalization' in R:
install.packages('colocalization', repos = c('https://hughzhangcn.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • twolines - A simulated 2-lines test data in 3D

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 stars 6 scripts 243 downloads 1 mentions 4 exports 17 dependencies

Last updated from:cb3caed802. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK133
source / vignettesOK125
linux-release-x86_64OK123
macos-release-arm64OK140
macos-oldrel-arm64OK150
windows-develOK103
windows-releaseOK90
windows-oldrelOK118
wasm-releaseOK115

Exports:nsinc.dnsinc.zplot.colocalsummary.colocal

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecycleR6RColorBrewerrlangS7scalesvctrsviridisLitewithr