Maaslin2 | R Documentation |

MaAsLin2 finds associations between microbiome meta-omics features and complex metadata in population-scale epidemiological studies. The software includes multiple analysis methods (including support for multiple covariates and repeated measures), filtering, normalization, and transform options to customize analysis for your specific study.

Maaslin2( input_data, input_metadata, output, min_abundance = 0.0, min_prevalence = 0.1, min_variance = 0.0, normalization = "TSS", transform = "LOG", analysis_method = "LM", max_significance = 0.25, random_effects = NULL, fixed_effects = NULL, correction = "BH", standardize = TRUE, cores = 1, plot_heatmap = TRUE, heatmap_first_n = 50, plot_scatter = TRUE, max_pngs = 10, save_scatter = FALSE, save_models = FALSE, reference = NULL )

`input_data` |
The tab-delimited input file of features. |

`input_metadata` |
The tab-delimited input file of metadata. |

`output` |
The output folder to write results. |

`min_abundance` |
The minimum abundance for each feature. |

`min_prevalence` |
The minimum percent of samples for which a feature is detected at minimum abundance. |

`min_variance` |
Keep features with variance greater than. |

`max_significance` |
The q-value threshold for significance. |

`normalization` |
The normalization method to apply. |

`transform` |
The transform to apply. |

`analysis_method` |
The analysis method to apply. |

`random_effects` |
The random effects for the model, comma-delimited for multiple effects. |

`fixed_effects` |
The fixed effects for the model, comma-delimited for multiple effects. |

`correction` |
The correction method for computing the q-value. |

`standardize` |
Apply z-score so continuous metadata are on the same scale. |

`plot_heatmap` |
Generate a heatmap for the significant associations. |

`heatmap_first_n` |
In heatmap, plot top N features with significant associations. |

`plot_scatter` |
Generate scatter plots for the significant associations. |

`max_pngs` |
Set the maximum number of scatter plots for signficant associations to save as png files. |

`save_scatter` |
Save all scatter plot ggplot objects to an RData file. |

`cores` |
The number of R processes to run in parallel. |

`save_models` |
Return the full model outputs and save to an RData file. |

`reference` |
The factor to use as a reference for a variable with more than two levels provided as a string of 'variable,reference' semi-colon delimited for multiple variables. |

List containing the results from applying the model.

Himel Mallick<himel.stat.iitk@gmail.com>,

Ali Rahnavard<gholamali.rahnavard@gmail.com>,

Maintainers: Lauren McIver<lauren.j.mciver@gmail.com>,

input_data <- system.file( 'extdata','HMP2_taxonomy.tsv', package="Maaslin2") input_metadata <-system.file( 'extdata','HMP2_metadata.tsv', package="Maaslin2") fit_data <- Maaslin2( input_data, input_metadata,'demo_output', transform = "AST", fixed_effects = c('diagnosis', 'dysbiosisnonIBD','dysbiosisUC','dysbiosisCD', 'antibiotics', 'age'), random_effects = c('site', 'subject'), normalization = 'NONE', reference = 'diagnosis,nonIBD', standardize = FALSE)

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