Package: MiCARA 0.99.2
MiCARA: Microbiome Confounder-Adjusted Robust Analysis
Provides a comprehensive framework for multi-cohort microbiome differential abundance and residual correlation analysis. It integrates confounder-adjusted linear models with centered log-ratio transformed taxonomic and functional pathway profiles. The package features robust preprocessing, automated covariate handling, multiple-testing correction, and quality control diagnostics for multi-omics data. Interactive visualization tools are included to facilitate downstream interpretation of cross-domain interaction networks.
Authors:
MiCARA_0.99.2.tar.gz
MiCARA_0.99.2.zip(r-4.7-any)MiCARA_0.99.2.zip(r-4.6-any)MiCARA_0.99.2.zip(r-4.5-any)
MiCARA_0.99.2.tgz(r-4.6-any)MiCARA_0.99.2.tgz(r-4.5-any)
MiCARA_0.99.2.tar.gz(r-4.7-any)MiCARA_0.99.2.tar.gz(r-4.6-any)
MiCARA_0.99.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MiCARA/json (API)
| # Install 'MiCARA' in R: |
| install.packages('MiCARA', repos = c('https://biocstaging.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bushnaqsafa/micara/issues
- example_metadata - Synthetic Example Sample Metadata
- example_pathways - Synthetic Example Functional Pathways Matrix
- example_taxa - Synthetic Example Taxa Abundance Matrix
microbiomedifferentialexpressionsoftwaremetagenomicsnetworkinferencepathwaysnetworkpreprocessingqualitycontrol
Last updated from:efe9bb0dda. Checks:1 ERROR, 9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 208 | ||
| linux-devel | OK | 284 | ||
| source / vignettes | OK | 324 | ||
| linux-release | OK | 324 | ||
| macos-release | OK | 238 | ||
| macos-oldrel | OK | 285 | ||
| windows-devel | OK | 286 | ||
| windows-release | OK | 286 | ||
| windows-oldrel | OK | 204 | ||
| wasm-release | OK | 141 |
Exports:compute_global_fdrcompute_residualCLR_correlationsimpute_metadataplot_interaction_sankeyprep_humann_pathwaysprep_metaphlan_taxarun_diff_abundancevalidate_inputs
Dependencies:ade4ANCOMBCapeaskpassbackportsbase64encBiobaseBiocGenericsbiomformatBiostringsbitbit64bootbroombslibcachemcellrangercheckmateclassclicliprclustercodetoolscolorspacecpp11crayoncurldata.tabledata.treeDescToolsdigestdoParalleldoRNGdplyre1071energyevaluateExactexpmfarverfastmapfontawesomeforcatsforeachforeignFormulafsgenericsggplot2gldglmnetgluegridExtragslgtablegtoolshavenhighrHmischmshtmlTablehtmltoolshtmlwidgetshttrigraphIRangesisobanditeratorsjomojquerylibjsonliteknitrlabelinglatticelifecyclelme4lmerTestlmommagrittrMASSMatrixmemoisemgcvmicemimeminqamitmlmultcompmulttestmvtnormnetworkD3nlmenloptrnnetnumDerivopensslordinalpanpermutephyloseqpillarpixmappkgconfigplyrprettyunitsprogressproxypurrrquadprogR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreadrreadxlreformulasrematchreshape2rlangrmarkdownrngtoolsrootSolverpartrstudioapiS4VectorsS7sandwichsassscalesSeqinfoshapespstringistringrsurvivalsysTH.datatibbletidyrtidyselecttinytextzdbucminfutf8vctrsveganviridisLitevroomwithrxfunXVectoryamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Apply global multiple-testing correction to taxon-pathway associations | compute_global_fdr |
| Compute confounder-adjusted Residual CLR taxon-pathway correlations for Disease-Associated Features | compute_residualCLR_correlations |
| Synthetic Example Sample Metadata | example_metadata |
| Synthetic Example Functional Pathways Matrix | example_pathways |
| Synthetic Example Taxa Abundance Matrix | example_taxa |
| Impute Missing Metadata Covariates Using MICE | impute_metadata |
| Plot a taxon-pathway interaction Sankey diagram | plot_interaction_sankey |
| Clean HUMAnN Pathway Matrix | prep_humann_pathways |
| Clean MetaPhlAn Taxonomic Names | prep_metaphlan_taxa |
| Run Differential Abundance Analysis Using ANCOM-BC2 | run_diff_abundance |
| Validate and preprocess MiCARA input tables | validate_inputs |