Spatially-aware normalisation for spatial transcriptomics data

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Documentation for package ‘SpaNorm’ version 1.7.16

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS
• Package README

Help Pages

$-method	An S4 class to store a SpaNorm model fit
add_vec_mat_gpu	Broadcast-add a vector to a matrix, GPU-aware
as.matrix.nbBlockDesign	A design with a per-group block, in compact form
calculateMu	Compute fitted means from a negative binomial GLM fit
checkGPU	Is an accelerated (GPU) torch device in use?
diag_mat	Build a diagonal matrix from a vector, GPU-aware
dim.nbBlockDesign	A design with a per-group block, in compact form
dimnames.nbBlockDesign	A design with a per-group block, in compact form
dnbinom_gpu	Negative binomial density (mean/size parameterisation), GPU-aware
fastSizeFactors	Filter genes based on expression
fastSizeFactors-method	Filter genes based on expression
filterGenes	Filter genes based on expression
filterGenes-method	Filter genes based on expression
fitNB	Fit a per-gene negative binomial GLM
getBackendDevice	Resolve the active torch backend device
getBackendDtype	Resolve the active torch backend dtype
getGPUMemoryBudget	Determine the accelerator memory budget for blocked fitting
gpuDtypeBytes	Bytes per element for the active backend dtype
hasBadValues	Does an object hold any NA/NaN/Inf?
HumanDLPFC	Human dorsolateral prefrontal cortex (DLPFC) visium sample
invert_mat	Invert a symmetric positive-definite matrix
invert_mat_batched	Invert a batch of symmetric positive-definite matrices
isPolished	Does a SpaNormFit carry a converged per-gene polish?
is_torch_tensor	Is an object a torch tensor?
matmul_gpu	Tensor-aware matrix multiplication
mult_vec_mat_gpu	Broadcast-multiply a vector and a matrix, GPU-aware
nbBlockDesign	A design with a per-group block, in compact form
nbDevianceMoments	First two moments of the NB unit deviance, by direct summation
nbUnitDeviance	NB unit deviance
plotCovariate	Diagnostic plot of predicted expression for a covariate
plotSpatial	Plot spatial transcriptomic annotations per spot
polishNB	Converge every gene of a shared negative binomial fit to its own optimum
polishSpaNorm	Converge each gene of a SpaNorm fit to its own optimum
polishSpaNorm-method	Converge each gene of a SpaNorm fit to its own optimum
print.nbBlockDesign	A design with a per-group block, in compact form
qlDispersion	Per-gene quasi-likelihood dispersion
qlMomentTable	A shared table of NB deviance moments
resetGPUCache	Clear the cached GPU device/memory-budget state
rowSums_gpu	Row sums, GPU-aware
setGPUMemoryBudget	Set the accelerator memory budget for blocked fitting
SpaNorm	Spatially-dependent normalisation for spatial transcriptomics data
SpaNorm-method	Spatially-dependent normalisation for spatial transcriptomics data
SpaNormFit	An S4 class to store a SpaNorm model fit
SpaNormFit-class	An S4 class to store a SpaNorm model fit
SpaNormPCA	GLM-based (SpaNorm) PCA
SpaNormPCA-method	GLM-based (SpaNorm) PCA
SpaNormSVG	Model-based spatially variable gene (SVG) calling
SpaNormSVG-method	Model-based spatially variable gene (SVG) calling
tcrossprod_gpu	Tensor-aware 'tcrossprod'
toGPUMatrix	Convert a matrix to a torch tensor on the active backend
toGPUVector	Convert a vector to a torch tensor on the active backend
topSVGs	Export top SVG results to a data frame
toRMatrix	Convert a torch tensor (or R object) to a base R matrix
tpsBasis	Thin-plate-style tensor spline basis over spatial coordinates