Package: proteoDeconv 0.1.2

Måns Zamore

proteoDeconv: Enabling Cell-Type Deconvolution of Proteomics Data

Tools for deconvoluting proteomics data to identify and quantify cell types (e.g., immune cell types) in complex biological samples.

Authors:Måns Zamore [aut, cre]

proteoDeconv_0.1.2.tar.gz
proteoDeconv_0.1.2.zip(r-4.7-any)proteoDeconv_0.1.2.zip(r-4.6-any)proteoDeconv_0.1.2.zip(r-4.5-any)
proteoDeconv_0.1.2.tgz(r-4.6-any)proteoDeconv_0.1.2.tgz(r-4.5-any)
proteoDeconv_0.1.2.tar.gz(r-4.7-any)proteoDeconv_0.1.2.tar.gz(r-4.6-any)
proteoDeconv_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
proteoDeconv/json (API)

# Install 'proteoDeconv' in R:

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

Bug tracker:https://github.com/computationalproteomics/proteodeconv/issues

Pkgdown/docs site:https://computationalproteomics.github.io

On CRAN:

3.65 score 9 stars 6 scripts 16 exports 107 dependencies

Last updated from:2379af2771. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time	Files	Syslog
linux-devel	NOTE	222
source / vignettes	OK	297
linux-release	NOTE	181
macos-release	NOTE	269
macos-oldrel	NOTE	254
windows-devel	NOTE	163
windows-release	NOTE	235
windows-oldrel	NOTE	158
wasm-release	OK	176

Exports:convert_to_tpm create_phenoclasses create_signature_matrix deconvolute deconvolute_bayesdebulk deconvolute_cibersort deconvolute_cibersortx deconvolute_epic extract_identifiers handle_duplicates handle_missing_values handle_scaling map_cell_groups simulate_data unlog2_data update_gene_symbols

Dependencies:abind ade4 ape basilisk BH Biobase BiocGenerics BiocParallel biomformat Biostrings bit bit64 bitops cli clipr clue cluster codetools cpp11 crayon data.table DelayedArray digest dir.expiry dplyr farver filelock foreach formatR futile.logger futile.options generics GenomicRanges ggplot2 glue gtable here HGNChelper hms igraph impute IRanges isoband iterators jsonlite labeling lambda.r lattice lifecycle magrittr MASS Matrix MatrixGenerics matrixStats mgcv MsCoreUtils multtest nlme permute phyloseq pillar pixmap pkgconfig plyr png prettyunits progress proxyC purrr R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppTOML RCurl readr reshape2 reticulate rlang rprojroot S4Arrays S4Vectors S7 scales Seqinfo SimBu snow sp SparseArray sparseMatrixStats splitstackshape stringi stringr SummarizedExperiment survival tibble tidyr tidyselect tzdb utf8 vctrs vegan viridisLite vroom withr XVector

Introduction to proteoDeconv

Introduction | Loading required packages | Example data overview | Data preprocessing | Preprocessing options | Creating a signature matrix | Performing deconvolution | Available deconvolution algorithms | Formatting and visualizing results | Conclusion | References

Rendered fromproteoDeconv.Rmdusingknitr::rmarkdown

Last update: 2025-03-07
Started: 2025-03-06

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Convert protein abundance data to TPM-like normalization	convert_to_tpm
Create phenoclasses matrix for cell type deconvolution	create_phenoclasses
Create signature matrix using CIBERSORTx	create_signature_matrix
Deconvolute protein data using multiple algorithms	deconvolute
Deconvolute bulk proteome data using BayesDeBulk	deconvolute_bayesdebulk
Deconvolute mixture data using CIBERSORT	deconvolute_cibersort
Deconvolute using CIBERSORTx Docker image	deconvolute_cibersortx
Deconvolute bulk data using EPIC	deconvolute_epic
Extract primary identifiers from e.g. protein groups	extract_identifiers
Handle duplicate identifiers in an expression matrix	handle_duplicates
Handle missing values	handle_missing_values
Handle scaling of protein abundance data	handle_scaling
Map column names to cell type groups using patterns	map_cell_groups
Simulate artifical mixtures from bulk proteome measurements	simulate_data
Convert data from log2 scale to linear scale	unlog2_data
Update gene symbols in a matrix to approved HGNC nomenclature	update_gene_symbols

Usage by other packages (reverse dependencies)