Warning
This site has been replaced by the new QIIME 2 “amplicon distribution” documentation, as of the 2025.4 release of QIIME 2. You can still access the content from the “old docs” here for the QIIME 2 2024.10 and earlier releases, but we recommend that you transition to the new documentation at https://amplicon-docs.qiime2.org. Content on this site is no longer updated and may be out of date.
Are you looking for:
the QIIME 2 homepage? That’s https://qiime2.org.
learning resources for microbiome marker gene (i.e., amplicon) analysis? See the QIIME 2 amplicon distribution documentation.
learning resources for microbiome metagenome analysis? See the MOSHPIT documentation.
installation instructions, plugins, books, videos, workshops, or resources? See the QIIME 2 Library.
general help? See the QIIME 2 Forum.
Old content beyond this point… 👴👵
ancombc: Analysis of Composition of Microbiomes with Bias Correction¶
Citations |
|
---|
Docstring:
Usage: qiime composition ancombc [OPTIONS] Apply Analysis of Compositions of Microbiomes with Bias Correction (ANCOM- BC) to identify features that are differentially abundant across groups. Inputs: --i-table ARTIFACT FeatureTable[Frequency] The feature table to be used for ANCOM-BC computation. [required] Parameters: --m-metadata-file METADATA... (multiple The sample metadata. arguments will be merged) [required] --p-formula TEXT How the microbial absolute abundances for each taxon depend on the variables within the `metadata`. [required] --p-p-adj-method TEXT Choices('holm', 'hochberg', 'hommel', 'bonferroni', 'BH', 'BY', 'fdr', 'none') Method to adjust p-values. [default: 'holm'] --p-prv-cut NUMBER A numerical fraction between 0-1. Taxa with prevalences less than this value will be excluded from the analysis. [default: 0.1] --p-lib-cut INTEGER A numerical threshold for filtering samples based on library sizes. Samples with library sizes less than this value will be excluded from the analysis. [default: 0] --p-reference-levels TEXT... List[Str] Define the reference level(s) to be used for categorical columns found in the `formula`. These categorical factors are dummy coded relative to the reference(s) provided. The syntax is as follows: "column_name::column_value" [optional] --p-tol NUMBER The iteration convergence tolerance for the E-M algorithm. [default: 1e-05] --p-max-iter INTEGER The maximum number of iterations for the E-M algorithm. [default: 100] --p-conserve / --p-no-conserve Whether to use a conservative variance estimator for the test statistic. It is recommended if the sample size is small and/or the number of differentially abundant taxa is believed to be large. [default: False] --p-alpha NUMBER Level of significance. [default: 0.05] Outputs: --o-differentials ARTIFACT FeatureData[DifferentialAbundance] The calculated per-feature differentials. [required] Miscellaneous: --output-dir PATH Output unspecified results to a directory --verbose / --quiet Display verbose output to stdout and/or stderr during execution of this action. Or silence output if execution is successful (silence is golden). --example-data PATH Write example data and exit. --citations Show citations and exit. --use-cache DIRECTORY Specify the cache to be used for the intermediate work of this action. If not provided, the default cache under $TMP/qiime2/will be used. IMPORTANT FOR HPC USERS: If you are on an HPC system and are using parallel execution it is important to set this to a location that is globally accessible to all nodes in the cluster. --help Show this message and exit. Examples: # ### example: ancombc single formula qiime composition ancombc \ --i-table table.qza \ --m-metadata-file metadata.tsv \ --p-formula bodysite \ --o-differentials dataloaf.qza # ### example: ancombc multi formula with reference levels qiime composition ancombc \ --i-table table.qza \ --m-metadata-file metadata.tsv \ --p-formula 'bodysite + animal' \ --p-reference-levels bodysite::tongue animal::dog \ --o-differentials dataloaf.qza
Import:
from qiime2.plugins.composition.methods import ancombc
Docstring:
Analysis of Composition of Microbiomes with Bias Correction Apply Analysis of Compositions of Microbiomes with Bias Correction (ANCOM- BC) to identify features that are differentially abundant across groups. Parameters ---------- table : FeatureTable[Frequency] The feature table to be used for ANCOM-BC computation. metadata : Metadata The sample metadata. formula : Str How the microbial absolute abundances for each taxon depend on the variables within the `metadata`. p_adj_method : Str % Choices('holm', 'hochberg', 'hommel', 'bonferroni', 'BH', 'BY', 'fdr', 'none'), optional Method to adjust p-values. prv_cut : Float, optional A numerical fraction between 0-1. Taxa with prevalences less than this value will be excluded from the analysis. lib_cut : Int, optional A numerical threshold for filtering samples based on library sizes. Samples with library sizes less than this value will be excluded from the analysis. reference_levels : List[Str], optional Define the reference level(s) to be used for categorical columns found in the `formula`. These categorical factors are dummy coded relative to the reference(s) provided. The syntax is as follows: "column_name::column_value" tol : Float, optional The iteration convergence tolerance for the E-M algorithm. max_iter : Int, optional The maximum number of iterations for the E-M algorithm. conserve : Bool, optional Whether to use a conservative variance estimator for the test statistic. It is recommended if the sample size is small and/or the number of differentially abundant taxa is believed to be large. alpha : Float, optional Level of significance. Returns ------- differentials : FeatureData[DifferentialAbundance] The calculated per-feature differentials.