Introduction | Installation | Run MetaDICT on a simulated dataset | Example dataset | Check the singular values of each dataset | Run MetaDICT function with taxa dissimilarity matrix | Run MetaDICT with the phylogenetic tree | Run MetaDICT with the taxonomy information | Run MetaDICT with the specified covariate | Run MetaDICT with customized parameters | Add new datasets to an existing integrated study | Community detection | Session information | References
Package: MetaDICT 1.3.0
Bo Yuan
MetaDICT: Microbiome data integration method via shared dictionary learning
MetaDICT is a method for the integration of microbiome data. This method is designed to remove batch effects and preserve biological variation while integrating heterogeneous datasets. MetaDICT can better avoid overcorrection when unobserved confounding variables are present.
Authors:
MetaDICT_1.3.0.tar.gz
MetaDICT_1.3.0.zip(r-4.7)MetaDICT_1.3.0.zip(r-4.6)MetaDICT_1.3.0.zip(r-4.5)
MetaDICT_1.3.0.tgz(r-4.6-any)MetaDICT_1.3.0.tgz(r-4.5-any)
MetaDICT_1.3.0.tar.gz(r-4.7-any)MetaDICT_1.3.0.tar.gz(r-4.6-any)
MetaDICT_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
MetaDICT/json (API)
| # Install 'MetaDICT' in R: |
| install.packages('MetaDICT', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/boyuan07/metadict/issues
Datasets:
- exampleData - Example microbiome dataset bundle
- exampleData_transfer - Example microbiome dataset bundle for transfer learning
On BioConductor:MetaDICT-1.3.0(bioc 3.24)MetaDICT-1.2.0(bioc 3.23)
microbiomebatcheffectsequencingclusteringsoftware
Last updated from:fabe04bd3f. Checks:1 NOTE, 9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | NOTE | 138 | ||
| linux-devel-x86_64 | OK | 259 | ||
| source / vignettes | OK | 306 | ||
| linux-release-x86_64 | OK | 314 | ||
| macos-release-arm64 | OK | 188 | ||
| macos-oldrel-arm64 | OK | 166 | ||
| windows-devel | OK | 811 | ||
| windows-release | OK | 461 | ||
| windows-oldrel | OK | 806 | ||
| wasm-release | OK | 150 |
Exports:community_detectiondata_checkMetaDICTmetadict_add_new_datapcoa_plot_continuouspcoa_plot_discreteplot_singular_values
Dependencies:abindapebackportsbootbroomcarcarDatacliclustercolorspacecorrplotcowplotcpp11DerivdigestdoBydplyrecodistedgeRfarverforecastFormulafracdiffgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableigraphisobandlabelinglatticelifecyclelimmalme4lmtestlocfitmagrittrMASSMatrixMatrixModelsmatrixStatsmgcvmicrobenchmarkminqamodelrnlmenloptrnnetnumDerivpbkrtestpermutepillarpkgconfigpolynompurrrquantregR6RANNrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrstatixS7scalesSparseMstatmodstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsveganviridisviridisLitewithrzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Taxa/Sample Community detection. | community_detection |
| Data Check | data_check |
| Example microbiome dataset bundle | exampleData |
| Example microbiome dataset bundle for transfer learning | exampleData_transfer |
| Microbiome data integration method via shared dictionary learning. | MetaDICT |
| Batch correction for new datasets using existing dictionary. | metadict_add_new_data |
| PCoA plots for continuous variables. | pcoa_plot_continuous |
| PCoA plots for discrete variables. | pcoa_plot_discrete |
| Generate Singular Value Plots for Each Dataset. | plot_singular_values |
