This function generates visualizations to assess the impact of batch effects on spatially variable genes (SVGs) by analyzing changes in deviance and rank. The function bins the deviations into normalized standard deviation (nSD) intervals and creates histograms and scatter plots to illustrate the distribution of batch effects.
Arguments
- list_batch_df
A named list of data frames, where each data frame corresponds to a batch effect and contains columns with deviance and rank differences.
- sd_interval_dev
A numeric vector specifying the interval widths for standard deviation bins for each batch when analyzing the relative change in deviance. The order of values must correspond to the order of batches in
list_batch_df. If a single value is provided, it is applied to all batches; otherwise, it must have the same length aslist_batch_df.- sd_interval_rank
vector: A numeric vector specifying the interval widths for standard deviation bins when analyzing rank differences. The order of values must correspond to the order of batches inlist_batch_df. If a single value is provided, it is applied to all batches; otherwise, it must have the same length aslist_batch_df.
Value
A combined ggplot object containing:
Deviance Plots:
Histogram of deviance differences across SVGs, colored by nSD intervals.
Scatter plot comparing deviance values before and after batch correction.
Rank Plots:
Histogram of rank differences across SVGs, colored by nSD intervals.
Scatter plot comparing ranks before and after batch correction.
The function arranges plots for each batch in a grid format for easy comparison.
Examples
# use the result generated from featureSelect()
load(system.file("extdata","list_batch_df.rda", package = "BatchSVG"))
plots <- svg_nSD(list_batch_df = list_batch_df,
sd_interval_dev = 3, sd_interval_rank = 3)