FSV_sig {spatialDE} | R Documentation

## Plot Fraction Spatial Variance vs Q-value

### Description

Plot Fraction Spatial Variance vs Q-value

### Usage

    FSV_sig(
      results,
      ms_results = NULL,
      certain_only = FALSE,
      log_x = FALSE,
      do_label = TRUE,
      covariate_names = NULL
    )

### Arguments

`results` | results from SpatialDE.
`ms_results` | model selection results, should be a data frame with columns `g` for gene names and `model` for the model selected.
`certain_only` | only plot results with narrow 95% confidence interval.
`log_x` | Whether to display x axis in log scale.
`do_label` | display gene names for statistically significant genes, default `TRUE`.
`covariate_names` | names of covariates as a reference, default to `NULL`.

### Value

A `ggplot2` object.

### Author(s)

Davide Corso, Milan Malfait, Lambda Moses

### References

Svensson, V., Teichmann, S. & Stegle, O. SpatialDE: identification of spatially variable genes. Nat Methods 15, 343–346 (2018). https://doi.org/10.1038/nmeth.4636

SpatialDE 1.1.3: the version of the Python package used under the hood.

### Examples

    set.seed(42)
    spe <- mockSVG(size = 10, tot_genes = 200, de_genes = 20, return_SPE = TRUE)
    ## Run spatialDE with S4 integration
    results <- spatialDE(spe)
    ## Run model search
    msearch <- modelSearch(spe, de_results = results, qval_thresh = NULL,
      verbose = FALSE)

    plot <- FSV_sig(results, msearch)

[Package spatialDE version 1.0.0 Index]