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Simulated Random Spatially Patterned Kidney Datasets

simRanPatternRasts.Rd

A list of 100 simulated SpatialExperiment objects representing kidney-shaped datasets, each containing one independently generated spatially patterned gene with no correlation between datasets. Each dataset consists of \(N = 5000\) simulated cells distributed within a kidney-shaped region, with spatial coordinates and expression values generated from Gaussian random fields.

Usage

simRanPatternRasts

Format

A list of length 100, where each element is a SpatialExperiment object containing:

assays

Matrix of simulated expression values named "pixelval".

colData

Data frame of per-cell metadata including coordinates and IDs.

spatialCoords

Matrix of spatial \((x, y)\) coordinates.

Source

Simulated by the STcompare development team.

Details

Each simulated dataset was generated as follows:

  • Cell coordinates \((x, y)\) were uniformly sampled within a bounding box from \(x, y \in [0,1]\).

  • A Matern covariance matrix \(Cov_{ij}\) of size \(N \times N\) was computed as: $$ Cov_{ij} = \frac{2^{1-\nu}}{\Gamma(\nu)} \left(\frac{h \sqrt{2\nu}}{\kappa}\right)^{\nu} K_\nu \left(\frac{h \sqrt{2\nu}}{\kappa}\right) $$ where \(h = \sqrt{(x_i - x_j)^2 + (y_i - y_j)^2}\), \(\nu = 0.5\), \(\kappa = 0.1\), \(\Gamma\) is the gamma function, and \(K_\nu\) is the modified Bessel function of the second kind. For diagonal elements (\(i = j\)), \(Cov_{ij} = 1\).

  • The covariance matrix was used to generate a multivariate normal vector \(W_i\) with mean 0 via MASS::mvrnorm.

  • Independently and identically distributed noise \(Z_i\) was sampled using stats::rnorm with mean 0 and standard deviation \(\sqrt{0.3}\).

  • The simulated gene expression for each cell was computed as: $$G_i = W_i + Z_i + 10$$

  • To form a kidney-shaped spatial pattern, each cell position was transformed to \((x, y) = (6x - 3, 6y - 3)\) and retained only if its Euclidean distance from the origin satisfied: $$\sqrt{x^2 + y^2} \le 1 - 2\sin(\theta) + \cos(\theta^2)$$ where \(\theta = \mathrm{atan2}(y, x)\).

Each element of simRanPatternRasts is a SpatialExperiment object with:

  • One simulated gene (1 row)

  • 250–300 spatial pixels (columns)

  • An assay named "pixelval" containing expression values

  • colData with columns: num_cell, cellID_list, geometry, and sample_id

  • Spatial coordinates (x, y)

See also

SpatialExperiment, mvrnorm, rnorm

Examples

data(simRanPatternRasts)
simRanPatternRasts[[1]]
#> class: SpatialExperiment 
#> dim: 1 280 
#> metadata(0):
#> assays(1): pixelval
#> rownames(1): 1
#> rowData names(0):
#> colnames(280): pixel151 pixel152 ... pixel588 pixel589
#> colData names(6): num_cell cellID_list ... geometry sample_id
#> reducedDimNames(0):
#> mainExpName: NULL
#> altExpNames(0):
#> spatialCoords names(2) : x y
#> imgData names(0):
assays(simRanPatternRasts[[1]])$pixelval[1, 1:5]
#> Error in assays(simRanPatternRasts[[1]]): could not find function "assays"