Package: mfa 1.29.0
Kieran Campbell
mfa: Bayesian hierarchical mixture of factor analyzers for modelling genomic bifurcations
MFA models genomic bifurcations using a Bayesian hierarchical mixture of factor analysers.
Authors:
mfa_1.29.0.tar.gz
mfa_1.29.0.zip(r-4.5)mfa_1.29.0.zip(r-4.4)mfa_1.29.0.zip(r-4.3)
mfa_1.29.0.tgz(r-4.4-x86_64)mfa_1.29.0.tgz(r-4.4-arm64)mfa_1.29.0.tgz(r-4.3-x86_64)mfa_1.29.0.tgz(r-4.3-arm64)
mfa_1.29.0.tar.gz(r-4.5-noble)mfa_1.29.0.tar.gz(r-4.4-noble)
mfa_1.29.0.tgz(r-4.4-emscripten)mfa_1.29.0.tgz(r-4.3-emscripten)
mfa.pdf |mfa.html✨
mfa/json (API)
| # Install 'mfa' in R: |
| install.packages('mfa', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:mfa-1.29.0(bioc 3.21)mfa-1.28.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
immunooncologyrnaseqgeneexpressionbayesiansinglecellcpp
Last updated 2 months agofrom:cd714067fd. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 29 2024 |
| R-4.5-win-x86_64 | OK | Nov 29 2024 |
| R-4.5-linux-x86_64 | OK | Nov 29 2024 |
| R-4.4-win-x86_64 | OK | Nov 29 2024 |
| R-4.4-mac-x86_64 | OK | Nov 29 2024 |
| R-4.4-mac-aarch64 | OK | Nov 29 2024 |
| R-4.3-win-x86_64 | OK | Nov 29 2024 |
| R-4.3-mac-x86_64 | OK | Nov 29 2024 |
| R-4.3-mac-aarch64 | OK | Nov 29 2024 |
Exports:calculate_chicreate_syntheticempirical_lambdamfaplot_chiplot_dropout_relationshipplot_mfa_autocorrplot_mfa_trace
Dependencies:apeBiobaseBiocGenericsclicodacolorspacecorpcorcpp11crayoncubaturedigestdplyrfansifarverforcatsgenericsGGallyggmcmcggplot2ggstatsgluegtablehmsisobandlabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmcmcMCMCglmmMCMCpackmgcvmunsellnlmepatchworkpillarpkgconfigplyrprettyunitsprogresspurrrquantregR6RColorBrewerRcpprlangscalesSparseMstringistringrsurvivaltensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Calculate posterior chi precision parameters | calculate_chi |
| Create synthetic data | create_synthetic |
| Estimate the dropout parameter | empirical_lambda |
| Fit a MFA object | mfa |
| Plot posterior precision parameters | plot_chi |
| Plot the dropout relationship | plot_dropout_relationship |
| Plot MFA autocorrelation | plot_mfa_autocorr |
| Plot MFA trace | plot_mfa_trace |
| Print an mfa fit | print.mfa |
| Summarise an mfa fit | summary.mfa |
| Turn a trace list to a 'ggmcmc' object | to_ggmcmc |
