Package: PAC 1.1.4

PAC: Partition-Assisted Clustering and Multiple Alignments of Networks

Implements partition-assisted clustering and multiple alignments of networks. It 1) utilizes partition-assisted clustering to find robust and accurate clusters and 2) discovers coherent relationships of clusters across multiple samples. It is particularly useful for analyzing single-cell data set. Please see Li et al. (2017) <doi:10.1371/journal.pcbi.1005875> for detail method description.

Authors:Ye Henry Li, Dangna Li

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PAC.pdf |PAC.html✨
PAC/json (API)

# Install 'PAC' in R:
install.packages('PAC', repos = c('https://yhenryli.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.30 score 7 scripts 548 downloads 71 mentions 16 exports 38 dependencies

Last updated 4 years agofrom:6452c154fa. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 12 2024
R-4.5-win-x86_64NOTEOct 12 2024
R-4.5-linux-x86_64NOTEOct 12 2024
R-4.4-win-x86_64NOTEOct 12 2024
R-4.4-mac-x86_64NOTEOct 12 2024
R-4.4-mac-aarch64NOTEOct 12 2024
R-4.3-win-x86_64NOTEOct 12 2024
R-4.3-mac-x86_64NOTEOct 12 2024
R-4.3-mac-aarch64NOTEOct 12 2024

Exports:aggregateDataannotateCladesannotationMatrix_withSubpopPropBSPLeaveCenterconstellationPlotfmeasuregetExtraneousCladeSubpopulationsgetRepresentativeNetworksheatmapInputMANMINetworkPlot_topEdgesPACrefineSubpopulationLabelsrenamePrunedSubpopulationsrunElbowPointAnalysissamplePass

Dependencies:clicolorspacecpp11dplyrfansifarvergenericsggplot2ggrepelgluegtableigraphinfotheoisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmeparmigenepillarpkgconfigR6RColorBrewerRcpprlangRtsnescalestibbletidyselectutf8vctrsviridisLitewithr

Using the PAC package

Rendered fromintro.Rmdusingknitr::rmarkdownon Oct 12 2024.

Last update: 2020-03-20
Started: 2016-03-25

Readme and manuals

Help Manual

Help pageTopics
Aggregates results from the clustering and merging step.aggregateData
Creates annotation matrix for the clades in aggregated format. The matrix contains average signals of each dimension for each clade in each sampleannotateClades
Adds subpopulation proportion for the annotation matrix for the cladesannotationMatrix_withSubpopProp
Finds N Leaf centers in the dataBSPLeaveCenter
Makes constellation plot, in which the centroids are clusters are embedded in the t-SNE 2D plane and the cross-sample relationships are plotted as lines connecting related sample clusters (clades).constellationPlot
F-measure Calculationfmeasure
Calculate the (global) average spread of subpopulations in clades with 2 subpopulations on the constellation plot.getAverageSpreadOf2SubpopClades
Calculates subpopulations in clades (with two or more subpopulations) that are too far away from other subpopulations (within the same clade) on the constellation plot; these far away subpopulations should be pruned away from the original clades.getExtraneousCladeSubpopulations
Representative NetworksgetRepresentativeNetworks
Creates the matrix that can be easily plotted with a heatmap function available in an R packageheatmapInput
Calculates the Jaccard similarity matrix.JaccardSM
Creates network alignments using network constructed from subpopulations after PACMAN
Mutual information network connection matrix generation (mrnet algorithm) using the parmigene package. Mutual information calculated with infotheo package.MINetwork_matrix_topEdges
Outputs the vectorized summary of a network based on the number of edges connected to a nodeMINetwork_simplified_topEdges
Plots mutual information network (mrnet algorithm) connection using the parmigene package. Mutual information calculated with infotheo package.MINetworkPlot_topEdges
Wrapper to output the mutual information networks for subpopulations with size larger than a desired threshold.outputNetworks_topEdges_matrix
Outputs the representative/clade networks (plots and summary vectors) for subpopulations with size larger than a desired threshold. Saves the networks and the data matrices without the smaller subpopulations.outputRepresentativeNetworks_topEdges
Partition Assisted Clustering PAC 1) utilizes dsp or bsp-ll to recursively partition the data space and 2) applies a short round of kmeans style postprocessing to efficiently output clustered labels of data points.PAC
Calculates the within cluster spreadrecordWithinClusterSpread
Refines the subpopulation labels from PAC using network alignment and small subpopulation information. Outputs a new set of files containing the representative labels.refineSubpopulationLabels
Prune away specified subpopulations in clades that are far away.renamePrunedSubpopulations
Runs elbow point analysis to find the practical optimal number of clades to output. Outputs the average within sample cluster spread for all samples and the elbow point analysis plot with loess line fitted through the results.runElbowPointAnalysis
Run PAC for Specified SamplessamplePass