Package: APL 1.9.1

Clemens Kohl

APL: Association Plots

APL is a package developed for computation of Association Plots (AP), a method for visualization and analysis of single cell transcriptomics data. The main focus of APL is the identification of genes characteristic for individual clusters of cells from input data. The package performs correspondence analysis (CA) and allows to identify cluster-specific genes using Association Plots. Additionally, APL computes the cluster-specificity scores for all genes which allows to rank the genes by their specificity for a selected cell cluster of interest.

Authors:Clemens Kohl [cre, aut], Elzbieta Gralinska [aut], Martin Vingron [aut]

APL_1.9.1.tar.gz
APL_1.9.1.zip(r-4.5)APL_1.9.1.zip(r-4.4)APL_1.9.1.zip(r-4.3)
APL_1.9.1.tgz(r-4.4-any)APL_1.9.1.tgz(r-4.3-any)
APL_1.9.1.tar.gz(r-4.5-noble)APL_1.9.1.tar.gz(r-4.4-noble)
APL_1.9.1.tgz(r-4.4-emscripten)APL_1.7.5.tgz(r-4.3-emscripten)
APL.pdf |APL.html✨
APL/json (API)
NEWS

# Install 'APL' in R:

install.packages('APL', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/vingronlab/apl/issues

On BioConductor:APL-1.9.0(bioc 3.20)APL-1.8.0(bioc 3.19)

bioconductor-package

23 exports 1.31 score 176 dependencies

Last updated 30 days agofrom:d4d1f40d9e

Exports:%>%apl apl_coords apl_score apl_topGO as.cacomp as.list ca_3Dplot ca_biplot ca_coords cacomp cacomp_names cacomp_slot check_cacomp new_cacomp pick_dims plot_enrichment run_APL runAPL show show.cacomp subset_dims var_rows

Dependencies:abind AnnotationDbi askpass base64enc BH Biobase BiocGenerics Biostrings bit bit64 bitops blob bslib cachem caTools cli cluster codetools colorspace commonmark cowplot cpp11 crayon crosstalk curl data.table DBI DelayedArray deldir digest dotCall64 dplyr dqrng evaluate fansi farver fastDummies fastmap fitdistrplus FNN fontawesome fs future future.apply generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 ggrepel ggridges globals glue GO.db goftest gplots graph gridExtra gtable gtools here highr htmltools htmlwidgets httpuv httr ica igraph IRanges irlba isoband jquerylib jsonlite KEGGREST KernSmooth knitr labeling later lattice lazyeval leiden lifecycle listenv lmtest magrittr MASS Matrix MatrixGenerics matrixStats memoise mgcv mime miniUI munsell nlme openssl org.Hs.eg.db org.Mm.eg.db parallelly patchwork pbapply pillar pkgconfig plogr plotly plyr png polyclip progressr promises purrr R6 RANN rappdirs RColorBrewer Rcpp RcppAnnoy RcppArmadillo RcppEigen RcppHNSW RcppProgress RcppTOML reshape2 reticulate rlang rmarkdown ROCR rprojroot RSpectra RSQLite Rtsne S4Arrays S4Vectors sass scales scattermore sctransform Seurat SeuratObject shiny SingleCellExperiment sitmo sourcetools sp spam SparseArray SparseM spatstat.data spatstat.explore spatstat.geom spatstat.random spatstat.sparse spatstat.utils stringi stringr SummarizedExperiment survival sys tensor tibble tidyr tidyselect tinytex topGO UCSC.utils utf8 uwot vctrs viridisLite withr xfun xtable XVector yaml zlibbioc zoo

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

Help page	Topics
Association Plot	apl
Calculate Association Plot coordinates	apl_coords
Plot Association Plot with ggplot	apl_ggplot
Plot Association Plot with plotly	apl_plotly
Find rows most highly associated with a condition	apl_score
Run Gene overrepresentation analysis with topGO	apl_topGO
Create cacomp object from Seurat/SingleCellExperiment container	as.cacomp as.cacomp,cacomp-method as.cacomp,list-method as.cacomp,Seurat-method as.cacomp,SingleCellExperiment-method
Convert cacomp object to list.	as.list,cacomp-method
Plot of the first 3D CA projection of the data.	ca_3Dplot ca_3Dplot,cacomp-method ca_3Dplot,Seurat-method ca_3Dplot,SingleCellExperiment-method
Plot of 2D CA projection of the data.	ca_biplot ca_biplot,cacomp-method ca_biplot,Seurat-method ca_biplot,SingleCellExperiment-method
Calculate correspondence analysis row and column coordinates.	ca_coords
Correspondance Analysis	cacomp cacomp,dgCMatrix-method cacomp,matrix-method cacomp,Seurat-method cacomp,SingleCellExperiment-method
Prints slot names of cacomp object	cacomp_names
Access slots in a cacomp object	cacomp_slot
An S4 class that contains all elements needed for CA.	cacomp-class new_cacomp
Calculate residuals for Correspondence analysis	calc_residuals
Check if cacomp object was correctly created.	check_cacomp
Perform clipping of residuals	clip_residuals
Compute Freeman-Tukey residuals	comp_ft_residuals
Compute Negative-Binomial residuals	comp_NB_residuals
Compute Standardized Residuals	comp_std_residuals
Runs elbow method	elbow_method
Find most variable rows	inertia_rows
Helper function to check if object is empty.	is.empty
Calculates permuted association plot coordinates	permutation_cutoff
Compute statistics to help choose the number of dimensions	pick_dims pick_dims,cacomp-method pick_dims,Seurat-method pick_dims,SingleCellExperiment-method
Generates plot for results from apl_topGO	plot_enrichment
Random direction association plot coordinates	random_direction_cutoff
Recompute missing values of cacomp object.	recompute
removes 0-only rows and columns in a matrix.	rm_zeros
Compute and plot Association Plot	runAPL runAPL,dgCMatrix-method runAPL,matrix-method runAPL,Seurat-method runAPL,SingleCellExperiment-method run_APL
Internal function for `cacomp`	run_cacomp
Scree Plot	scree_plot
Prints cacomp object	show,cacomp-method show.cacomp
Subset dimensions of a caobj	subset_dims
Find most variable rows	var_rows

Package: APL 1.9.1

APL: Association Plots

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