Package: sccomp 1.9.0

Stefano Mangiola

sccomp: Robust Outlier-aware Estimation of Composition and Heterogeneity for Single-cell Data

A robust and outlier-aware method for testing differential tissue composition from single-cell data. This model can infer changes in tissue composition and heterogeneity, and can produce realistic data simulations based on any existing dataset. This model can also transfer knowledge from a large set of integrated datasets to increase accuracy further.

Authors:Stefano Mangiola [aut, cre]

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sccomp.pdf |sccomp.html✨
sccomp/json (API)

# Install 'sccomp' in R:

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

Bug tracker:https://github.com/stemangiola/sccomp/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

counts_obj - Counts_obj
sce_obj - Sce_obj
seurat_obj - Seurat_obj

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

bioconductor-package

11 exports 1.69 score 109 dependencies

Last updated 2 months agofrom:13c5322829

Exports:plot_summary sccomp_boxplot sccomp_estimate sccomp_glm sccomp_predict sccomp_remove_outliers sccomp_remove_unwanted_variation sccomp_replicate sccomp_test simulate_data test_contrasts

Dependencies:abind askpass backports BH Biobase BiocGenerics bit bit64 boot callr checkmate cli clipr codetools colorspace cpp11 crayon curl DelayedArray desc digest distributional dotCall64 dplyr fansi farver forcats future future.apply generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 ggrepel globals glue gridExtra gtable hms httr inline IRanges isoband jsonlite labeling lattice lifecycle listenv loo magrittr MASS Matrix MatrixGenerics matrixStats mgcv mime munsell nlme numDeriv openssl parallelly patchwork pillar pkgbuild pkgconfig posterior prettyunits processx progress progressr ps purrr QuickJSR R6 RColorBrewer Rcpp RcppEigen RcppParallel readr rlang rstan rstantools S4Arrays S4Vectors scales SeuratObject SingleCellExperiment sp spam SparseArray StanHeaders stringi stringr SummarizedExperiment sys tensorA tibble tidyr tidyselect tzdb UCSC.utils utf8 vctrs viridisLite vroom withr XVector zlibbioc

Overview of the sccomp package

Stefano Mangiola

Rendered fromintroduction.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2024-04-18
Started: 2021-09-19

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
The 'sccomp' package.	sccomp-package sccomp
counts_obj	counts_obj
multi_beta_glm main	multi_beta_glm
plot_summary	plot_summary
plot	plot.sccomp_tbl
sccomp_boxplot	sccomp_boxplot
Main Function for SCCOMP Estimate	sccomp_estimate
DEPRECATED - sccomp_glm main	sccomp_glm
sccomp_predict	sccomp_predict
sccomp_remove_outliers main	sccomp_remove_outliers
sccomp_remove_unwanted_variation	sccomp_remove_unwanted_variation
sccomp_replicate	sccomp_replicate
sccomp_test	sccomp_test
sce_obj	sce_obj
seurat_obj	seurat_obj
simulate_data	simulate_data
test_contrasts	test_contrasts