LoadSpatial

A function to load and filter data from a Seurat object or a data frame.

Identifying spatially variable genes is critical in linking molecular cell functions with tissue phenotypes. This package implemented a granularity-based dimension-agnostic tool for the identification of spatially variable genes. The detailed description of this method is available at Wang, J. and Li, J. et al. 2023 (Wang, J. and Li, J. (2023), <doi:10.1038/s41467-023-43256-5>).

Jinpu Li

GrabSVG

Granularity-Based Spatially Variable Genes Identifications

LoadSpatial function

<dl><dt>InputData</dt>
<dd>A Seurat spatial object or a M x (D + N) data matrix representing the D-dimensional coordinates and expressions of N genes on M spots. The coordinates should be placed at the first D columns</dd>
<dt>Dimension</dt>
<dd>The dimension of coordinates</dd></dl>

Arguments

Loading data from a Seurat object or a data frame. — LoadSpatial

<dl>

<dt>InputData</dt>
<dd>A Seurat spatial object or a M x (D + N) data matrix representing the D-dimensional coordinates and expressions of N genes on M spots. The coordinates should be placed at the first D columns</dd>


<dt>Dimension</dt>
<dd>The dimension of coordinates</dd>

</dl>

LoadSpatial: Loading data from a Seurat object or a data frame.

Description

Usage

Value

Arguments