Enabling Cell-Type Deconvolution of Proteomics Data

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Documentation for package ‘proteoDeconv’ version 0.1.2

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package README

Help Pages

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