fit_maple | R Documentation |

This function allows you to detect sub-populations and explain membership with relevant covariates in multi-sample spatial transcriptomics experiments.

fit_maple( seurat_obj, K, emb = "PCs", n_dim = 8, covars = NULL, MCAR = FALSE, CAR = FALSE, smooth = TRUE, r = 3, nsim = 2000, burn = 1000, z_init = NULL )

`seurat_obj` |
An integrated Seurat object. |

`K` |
The number of sub-populations to infer. Each should be present in each sample. |

`emb` |
The cell spot embedding to use. Either one of "PCs", "scGNN", "harmony", "HVGs", or "SVGs". |

`n_dim` |
The number of dimensions to use. |

`covars` |
Column names of Seurat meta data to use as covariates. If none specified, will fit a global intercept and sample-indicator model for cell type membership probabilities. |

`MCAR` |
Logical. Include multivariate CAR random intercepts in gene expression model? |

`CAR` |
Logical. Include univariate CAR random intercepts in multinomial gene expression model? |

`smooth` |
Logical. Use manual spatial smoothing controlled by r parameter? |

`r` |
Spatial smoothing parameter for if smooth == TRUE. Should be greater than 0 with larger values enforcing stronger prior spatial association. |

`nsim` |
Number of total MCMC iterations to conduct. |

`burn` |
Number of initial MCMC iterations to discard as burn in. The number of saved iterations is nsim-burn. |

`z_init` |
Initialized cluster allocation vector to aid in MCMC convergence. If NULL z_init will be set using hierarchical clustering. |

A list of MCMC samples, including the MAP estimate of cluster indicators (z)

## Not run: brain1 <- LoadData("stxBrain", type = "anterior1") brain2 <- LoadData("stxBrain", type = "anterior2") brain1 <- SCTransform(brain1, assay = "Spatial", verbose = FALSE) brain2 <- SCTransform(brain2, assay = "Spatial", verbose = FALSE) brain <- merge(brain1,brain2) DefaultAssay(brain) <- "SCT" VariableFeatures(brain) <- c(VariableFeatures(brain1),VariableFeatures(brain2)) brain <- RunPCA(brain) brain_fit_PCs <- fit_maple(brain,K = 6,emb = "PCs") ## End(Not run)

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