Package: MultIS 0.6.2

MultIS: Reconstruction of Clones from Integration Site Readouts and Visualization

Tools necessary to reconstruct clonal affiliations from temporally and/or spatially separated measurements of viral integration sites. For this means it utilizes correlations present in the relative readouts of the integration sites. Furthermore, facilities for filtering of the data and visualization of different steps in the pipeline are provided with the package.

Authors:Sebastian Wagner [cre, aut], Christoph Baldow [aut], Ingmar Glauche [ths]

MultIS_0.6.2.tar.gz
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MultIS.pdf |MultIS.html✨
MultIS/json (API)

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

Peer review:

On CRAN:

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

18 exports 0.00 score 55 dependencies 1 scripts 229 downloads

Last updated 3 years agofrom:52bee4a2be. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 17 2024
R-4.5-winNOTESep 17 2024
R-4.5-linuxNOTESep 17 2024
R-4.4-winNOTESep 17 2024
R-4.4-macNOTESep 17 2024
R-4.3-winNOTESep 17 2024
R-4.3-macNOTESep 17 2024

Exports:convert_columnwise_relativeevaluate_clusteringfilter_at_tp_biggest_nfilter_at_tp_minfilter_combine_measurementsfilter_is_namesfilter_matchfilter_measurement_namesfilter_namesfilter_nr_tp_minfilter_zero_columnsfilter_zero_rowsfind_best_nr_clusterget_similarity_matrixnormalize_timecourseplot_rsquarereconstructreconstruct_recursive

Dependencies:admiscclasscliclusterclvclValidcodetoolscolorspacecpp11dplyrexpmfansifarverforeachgenericsggplot2gluegtableigraphisobanditeratorslabelinglatticelifecycleltmmagrittrMASSMatrixmgcvmsmmunsellmvtnormnlmepillarpkgconfigplyrpolycorpoweRlawpracmaR6RColorBrewerRcppreshape2rlangrmutilscalesstringistringrsurvivaltibbletidyselectutf8vctrsviridisLitewithr

Quick Start - MultIS

Christoph Baldow, Sebastian Wagner, Ingmar Glauche

Rendered fromQuickStart.Rmdusingknitr::knitron Sep 17 2024.

Last update: 2021-08-06
Started: 2021-05-26

Readme and manuals

Help Manual

Help pageTopics
Create a stacked area plot that represents the abundance of integration sites over time.bushmanplot
Calculate the bw indexbw
Converts a matrix to relative abundancesconvert_columnwise_relative
Evaluate a clustering using the given methodevaluate_clustering
Evaluate a clustering using the bw indexevaluate_clustering_bw
Evaluate a clustering using a custom evaluation functionevaluate_clustering_custom
Evaluate a clustering using the dunn indexevaluate_clustering_dunn
Evaluate a clustering using the point-biserial indexevaluate_clustering_ptbiserial
Evaluate a clustering using the SD-indexevaluate_clustering_sdindex
Evaluate a clustering using the silhouette indexevaluate_clustering_silhouette
Filters a matrix of readouts for the n biggest IS at a certain measurementfilter_at_tp_biggest_n
Filters a matrix of readouts for IS that have a minimum occurrence in some measurementfilter_at_tp_min
Combines columns that have the same name. The columns are joined additively.filter_combine_measurements
Shortens the rownames of a readout matrix to the shortest distinct prefixfilter_is_names
Filters for columns containing a certain substring.filter_match
Splits a vector of strings by a given regexp, selects and rearranges the parts and joins them againfilter_measurement_names
Filters a vector of names and returns the shortest common prefix.filter_names
Filters for a minimum number of time points/measurementsfilter_nr_tp_min
Removes columns that only contain 0 or NA.filter_zero_columns
Removes rows that only contain 0 or NA.filter_zero_rows
Finds the best number of clusters according to silhouettefind_best_nr_cluster
Generate a similarity matrixget_similarity_matrix
Get the default ggplot color palette or a color palette based on the ggplot palette, but with sub-colors that differ in their luminanceggplot_colors
Show line plots of all integration sites over time, split into facets by their respective clone.lineplot_split_clone
Normalizes a time course using a given mapping from integration sites to clones.normalize_timecourse
Plots R^2 of two integration sitesplot_rsquare
Plots the clustering based on a clustering objectplot.clusterObj
Plots the similarity of integration sitesplot.ISSimilarity
Plots time series data, which consists of multiple measurements over time / place (cols) of different clones / integration sites (rows).plot.timeseries
Apply a clustering algorithm to a given time course.reconstruct
Calculate the k-medoids clustering for a given time course.reconstruct_kmedoid
Apply a clustering algorithm recursively to a given time course.reconstruct_recursive
Plot the relationship of integration sites as a graph.weighted_spring_model