FAST_single: Fit FAST model for single-section SRT data

In ProFAST: Probabilistic Factor Analysis for Spatially-Aware Dimension Reduction

Fit FAST model for single-section SRT data

Description

Fit FAST model for single-section SRT data.

Usage

FAST_single(
  seu,
  Adj_sp,
  q = 15,
  fit.model = c("poisson", "gaussian"),
  slot = "data",
  assay = NULL,
  reduction.name = "fast",
  verbose = TRUE,
  ...
)

Arguments

seu	a Seurat object.
Adj_sp	a sparse matrix, specify the adjacency matrix among spots.
q	an optional integer, specify the number of low-dimensional embeddings to extract in FAST. Larger q means more information extracted.
fit.model	an optional string, specify the version of FAST to be fitted. The Gaussian version models the log-count matrices while the Poisson verions models the count matrices; default as possion model.
slot	an optional string, specify the slot in Seurat object as the input of FAST model, default as 'data'.
assay	an optional string, specify the assay in Seurat object, default as 'NULL' that means the default assay in Seurat object.
reduction.name	an optional string, specify the reduction name for the fast embedding, default as 'fast'.
verbose	a logical value, whether output the information in iteration.
...	other arguments passed to FAST_run.

Value

return a list including the parameters set in the arguments.

See Also

FAST_run

ProFAST documentation built on May 29, 2024, 7:15 a.m.