How to adjust summary plot figure

Downstream analysis and statistics
1

Hello,
I’m using MaasLin3, but I can’t seem to adjust my x-axis in the summary plot. Do you think the settings would be similar to those for ggplot? Any help you could offer would be much appreciated. Thanks!

Screenshot from 2025-03-05 16-25-58
Screenshot from 2025-03-05 16-25-581289×551 71.5 KB

2

Hi Rafaela,

The functions maaslin_plot_results and maaslin_plot_results_from_output (run on your outputs) will return lists of patchwork objects which themselves contain the ggplot2 objects. If you overwrite the old objects with the edited objects (e.g., by adding + scale_x_continuous(breaks = c(-1, 0, 1))), the plots will display your modifications.

Will

3

Hi Will,

When I tried replotting the results, only the individual association plots are stored as a list. The summary plot just gets replotted to the output folder instead of being stored in the list. Am I missing something?

Thanks in advance!
Best wishes,
Gonçalo

replotting code:

scatter_plots <- maaslin_plot_results_from_output(
  output = 'output_directory_rv',
  metadata = samples_rv_maaslin,
  normalization = "NONE",
  transform = "LOG",
  median_comparison_abundance = F,
  max_significance = 0.1,
  plot_summary_plot = TRUE,
  summary_plot_first_n = 10)
4

Hmm, I’m not sure just by looking at it. This works for me; do you get the summary plot when you do this?

# Read abundance table
taxa_table_name <- system.file("extdata", "HMP2_taxonomy.tsv", package = "maaslin3")
taxa_table <- read.csv(taxa_table_name, sep = '\t', row.names = 1)

# Read metadata table
metadata_name <- system.file("extdata", "HMP2_metadata.tsv", package = "maaslin3")
metadata <- read.csv(metadata_name, sep = '\t', row.names = 1)

# Factor the categorical variables to test IBD against healthy controls
metadata$diagnosis <- 
    factor(metadata$diagnosis, levels = c('nonIBD', 'UC', 'CD'))
metadata$dysbiosis_state <- 
    factor(metadata$dysbiosis_state, levels = c('none', 'dysbiosis_UC', 'dysbiosis_CD'))
metadata$antibiotics <- 
    factor(metadata$antibiotics, levels = c('No', 'Yes'))

set.seed(1)
fit_out <- maaslin3(input_data = taxa_table,
                    input_metadata = metadata,
                    output = 'hmp2_output',
                    formula = '~ diagnosis + dysbiosis_state +
                        antibiotics + age + reads',
                    normalization = 'TSS',
                    transform = 'LOG',
                    augment = TRUE,
                    standardize = TRUE,
                    max_significance = 0.1,
                    median_comparison_abundance = TRUE,
                    median_comparison_prevalence = FALSE,
                    max_pngs = 250,
                    cores = 1)

outputs <- maaslin_plot_results_from_output('hmp2_output', metadata = metadata, 
                                 normalization = 'TSS', transform = 'LOG')


outputs$summary_plot$final