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spots (version 0.1.0)

Spatial Component Analysis

Description

The spots package is designed for spatial omics (10x Visium, etc.) data analysis. It performs various statistical analyses and tests, including spatial component analysis (SCA), both global and local spatial statistics, such as univariate and bivariate Moran's I, Getis-Ord Gi* statistics, etc. See Integrated protein and transcriptome high-throughput spatial profiling (2022) for more details.

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Version

Install

install.packages('spots')

Monthly Downloads

2

Version

0.1.0

License

GPL-3

Maintainer

X. Steve Niu

Last Published

May 3rd, 2022

Functions in spots (0.1.0)

Local Moran's I

10x Genomics Visium hexagonal nearest neighbor

Bivariate Moran's I using Wartenberg's M matrix

LocalMoransIStats

Local Moran's I statistics

Spatial Component Analysis

PermutationMoransI

Permutation based Moran's I

PermutationLocalI

Permutation based local Moran's I

PermutationPval

Permutation based p-value

Load selected data

Spatial cross-correlation

Local Getis-Ord Gi or Gi* statistics for spatial hot spot analysis

Moran's I using ordinary least squares (OLS)

Hexagonal nearest neighbor based imputation

Permutation based p-value for spatial lag

P-value of Z scores

Permutation based Getis-Ord Gi or Gi* statistics for spatial hots pot analysis

spots: Spatial Component Analysis

PermutationCorr

Permutation based p-value for Pearson's correlation coefficient

UnivariateMoransI

Univariate Moran's I

BivariateMoransIStats

Bivariate Moran's I statistics

IrregularMoransI

Moran's I between two groups (irregular data shape)

HnnNeighborIndex

Hexagonal nearest neighbor index

Fitted values of Moran's I

Bivariate Moran's I using Lee's L measurement

Hexagonal nearest neighbor

BivariateMoransI

Bivariate Moran's I

Hexagonal nearest neighbor weight

Process irregular data shape (between two groups) for Moran's I