Package: cpam 0.1.3.9000
cpam: Changepoint Additive Models for Time Series Omics Data
Provides a comprehensive framework for time series omics analysis, integrating changepoint detection, smooth and shape-constrained trends, and uncertainty quantification. It supports gene- and transcript-level inferences, p-value aggregation for improved power, and both case-only and case-control designs. It includes an interactive 'shiny' interface. The methods are described in Yates et al. (2024) <doi:10.1101/2024.12.22.630003>.
Authors:
cpam_0.1.3.9000.tar.gz
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cpam.pdf |cpam.html✨
cpam/json (API)
NEWS
| # Install 'cpam' in R: |
| install.packages('cpam', repos = c('https://l-a-yates.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/l-a-yates/cpam/issues
Pkgdown site:https://l-a-yates.github.io
Last updated 1 days agofrom:aef8ae80c8. Checks:9 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 14 2025 |
| R-4.5-win | OK | Mar 14 2025 |
| R-4.5-mac | OK | Mar 14 2025 |
| R-4.5-linux | OK | Mar 14 2025 |
| R-4.4-win | OK | Mar 14 2025 |
| R-4.4-mac | OK | Mar 14 2025 |
| R-4.4-linux | OK | Mar 14 2025 |
| R-4.3-win | OK | Mar 14 2025 |
| R-4.3-mac | OK | Mar 14 2025 |
Exports:%>%compute_p_valuesestimate_changepointplot_clusterplot_cpamprepare_cpamresultsselect_shapets_filtervisualise
Dependencies:base64encBHbslibcachemclicolorspacecommonmarkcpp11crayondigestdplyredgeRfansifarverfastmapfontawesomefsgenericsggplot2gluegtablehtmltoolshttpuvisobandjquerylibjsonlitelabelinglaterlatticelifecyclelimmalocfitmagrittrMASSMatrixmatrixStatsmemoisemgcvmimemunsellmvnfastnlmepbmcapplypillarpkgconfigpromisespurrrR6rappdirsRColorBrewerRcppRcppArmadillorlangsassscalesscamshinyshinyjssourcetoolsstatmodstringistringrtibbletidyrtidyselecttximportutf8vctrsviridisLitewithrxtable
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute p-values for each target ID | compute_p_values |
| The cpam class | cpam cpam-class |
| Use model selection to estimate changepoints | estimate_changepoint |
| Plot clustered targets | plot_cluster |
| Plot fitted changepoint additive models | plot_cpam |
| Prepare a cpam object | prepare_cpam |
| Create a results table from a cpam object | results |
| Use model selection to select a shape for each target | select_shape |
| Removes lowly expressed genes | ts_filter |
| Launches a Shiny app to visualise the data and fitted models of a cpam object | visualise visualize |
