Function reference • immunedeconv

Deconvolution Use the package to estimate immune cell fractions from bulk RNA-seq samples.
`deconvolution_methods`	List of supported immune deconvolution methods
`deconvolute()`	Perform an immune cell deconvolution on a dataset.
`set_cibersort_binary()`	Set Path to CIBERSORT R script (`CIBERSORT.R`)
`set_cibersort_mat()`	Set Path to CIBERSORT matrix file (`LM22.txt`)
`eset_to_matrix()`	Convert a `Biobase::ExpressionSet` to a gene-expression matrix.
Deconvolution for mouse data Use the package to estimate immune cell fractions from murine bulk RNA-seq samples.
`deconvolution_methods_mouse`	List of supported mouse deconvolution methods The methods currently supported are `mmcp_counter`, `seqimmucc`, `dcq`, `base` The object is a named vector. The names correspond to the display name of the method, the values to the internal name.
`deconvolute_mouse()`	Perform deconvolution on a mouse RNAseq dataset
Deconvolution methods Direct access to the individual deconvolution methods to access special features that are not available through `deconvolute()`.
`deconvolute_cibersort()`	Deconvolute using CIBERSORT or CIBERSORT abs.
`deconvolute_epic()`	Deconvolute using EPIC
`deconvolute_mcp_counter()`	Deconvolute using MCP-counter
`deconvolute_quantiseq()`	Deconvolute using quanTIseq
`deconvolute_timer()`	Deconvolute using TIMER
`deconvolute_xcell()`	Deconvolute using xCell
`deconvolute_abis()`	Deconvolute using ABIS.
`deconvolute_consensus_tme()`	Deconvolute using ConsensusTME.
`deconvolute_estimate()`	Source code for the ESTIMATE algorithm: Estimate of Stromal and Immune Cells in Malignant Tumor Tissues from Expression Data (https://doi.org/10.1038/ncomms3612) Source: http://r-forge.r-project.org/projects/estimate/ Copyright: 2013-2022, MD Anderson Cancer Center (MDACC) License: GPL-2
Deconvolution methods for mouse data Direct access to the individual mouse deconvolution methods to access special features that are not available through `deconvolute()`.
`deconvolute_mmcp_counter()`	Deconvolute using mMCP-counter
`deconvolute_seqimmucc()`	Deconvolute using seqImmuCC
`deconvolute_base_algorithm()`	Deconvolute using BASE
`deconvolute_dcq()`	Deconvolute using DCQ
`convert_human_mouse_genes()`	This function converts the mouse gene symbols into corresponding human ones, and vice versa.
Deconvolution methods with custom signature Access to the individual deconvolution methods that allow the use of a custom signature (matrix or gene set)
`custom_deconvolution_methods`	List of methods that support the use of a custom signature
`deconvolute_cibersort_custom()`	Deconvolute using CIBERSORT or CIBERSORT abs and a custom signature matrix.
`deconvolute_epic_custom()`	Deconvolute using EPIC and a custom signature matrix.
`deconvolute_base_custom()`	Deconvolute using BASE and a custom signature matrix
`deconvolute_consensus_tme_custom()`	Deconvolute using ConsesnusTME and a custom signature matrix
Cell type mapping Map cell types and datasets to a controlled vocabulary.
`cell_type_map`	Table mapping the cell types from methods/datasets to a single, controlled vocabulary.
`cell_type_tree`	Available cell types in the controlled vocabulary organized as a lineage tree.
`available_datasets`	Available methods and datasets.
`map_cell_types()`	Use a tree-hierarchy to map cell types among different methods.
`map_result_to_celltypes()`	Map a result table as generated by `deconvolute` to a user-defined list of cell types.
`get_dcq_cell_types_list()`	This function returns the list of all cell types in BASE/DCQ results, along with the cell type they are mapped to
`reduce_mouse_cell_types()`	Since DCQ and BASE provide estimates for several cell types, this function combines the results to align them with the rest of the methods
Simulation of bulk samples Use this package to simulate bulk RNA-seq samples from single cell RNA-seq data.
`scale_to_million()`	Scale sample to TPM
`make_random_bulk()`	Make a random bulk sample from a single-cell dataset
`make_bulk_eset()`	Make a random expression set from a single-cell dataset
Datasets List of datasets provided by the package
`dataset_racle`	Example RNA-seq dataset from the EPIC publication.
`dataset_petitprez`	Example RNA-seq dataset from the mMCP_Counter publication.
TIMER functions and objects related to the TIMER method
`timer_available_cancers`	TIMER signatures are cancer specific. This is the list of available cancer types.
`deconvolute_timer()`	Deconvolute using TIMER

Reference

Deconvolution

Deconvolution for mouse data

Deconvolution methods

Deconvolution methods for mouse data

Deconvolution methods with custom signature

Cell type mapping

Simulation of bulk samples

Datasets

TIMER