# Methods for immune cell deconvolution

## Documentation for package ‘immunedeconv’ version 2.1.0

- DESCRIPTION file.

## Help Pages

.get_all_children | Recursive helper function for get_all_children.
annotate_cell_type | Annotate unified cell_type names
available_datasets | Available methods and datasets.
base_algorithm | Souce code for the BASE algorithm. This code is adapted from Varn et al., DOI: 10.1158/0008-5472.CAN-16-2490
cell_type_list | List with controlled cell-type vocabulary
cell_type_map | Table mapping the cell types from methods/datasets to a single, controlled vocabulary.
cell_type_mapping | Functions for mapping cell types between deconvolution methods and datasets.
cell_type_tree | Available cell types in the controlled vocabulary organized as a lineage tree.
check_cancer_types | process batch table and check cancer types.
create_base_compendium | Souce code to create the compendium used kin the BASE algorithm, containing up- and down-regulated weight sets that specify the This code is adapted from Varn et al., DOI: 10.1158/0008-5472.CAN-16-2490
custom_deconvolution | Collection of deconvolution methods that allow custom signature matrices.
custom_deconvolution_methods | List of methods that support the use of a custom signature
dataset_petitprez | Example RNA-seq dataset from the mMCP_Counter publication.
dataset_racle | Example RNA-seq dataset from the EPIC publication.
deconvolute | Perform an immune cell deconvolution on a dataset.
deconvolute_abis | Deconvolute using ABIS.
deconvolute_abis_default | Use ABIS to deconvolute a gene expression matrix.
deconvolute_base_algorithm | Deconvolute using BASE
deconvolute_base_custom | Deconvolute using BASE and a custom signature matrix
deconvolute_cibersort | Deconvolute using CIBERSORT or CIBERSORT abs.
deconvolute_cibersort_custom | Deconvolute using CIBERSORT or CIBERSORT abs and a custom signature matrix.
deconvolute_consensus_tme | Deconvolute using ConsensusTME.
deconvolute_consensus_tme_custom | Deconvolute using ConsesnusTME and a custom signature matrix
deconvolute_dcq | Deconvolute using DCQ
deconvolute_epic | Deconvolute using EPIC
deconvolute_epic_custom | Deconvolute using EPIC and a custom signature matrix.
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
deconvolute_mcp_counter | Deconvolute using MCP-counter
deconvolute_mmcp_counter | Deconvolute using mMCP-counter
deconvolute_mouse | Perform deconvolution on a mouse RNAseq dataset
deconvolute_quantiseq | Deconvolute using quanTIseq
deconvolute_seqimmucc | Deconvolute using seqImmuCC
deconvolute_timer | Deconvolute using TIMER
deconvolute_xcell | Deconvolute using xCell
deconvolution_methods | List of supported immune deconvolution methods
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.
eset_to_matrix | Convert a 'Biobase::ExpressionSet' to a gene-expression matrix.
find_children | Recursive helper function for map_cell_types.
fix_namespace | assign the following global variables .onLoad because of 'staged-install'
GetFractions.Abbas | Constrained regression method implemented in Abbas et al., 2009
get_all_children | Get all children of a certain cell type.
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
immunedeconv | Collection of immune cell deconvolution methods.
make_bulk_eset | Make a random expression set from a single-cell dataset
make_random_bulk | Make a random bulk sample from a single-cell dataset
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.
mouse_cell_type_mapping | Functions for mapping cell types between deconvolution methods.
mouse_deconvolution | Collection of deconvolution methods for mouse data.
mouse_genes_to_human | This function converts the mouse gene symbols into corresponding human ones.
node_by_name | Lookup dictionary for cell-type nodes
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
scale_to_million | Scale sample to TPM
seqImmuCC_LLSR | Source code for the Linear Least Square Regression performed in seqImmuCC.
set_cibersort_binary | Set Path to CIBERSORT R script ('CIBERSORT.R')
set_cibersort_mat | Set Path to CIBERSORT matrix file ('LM22.txt')
single_cell_simulation | Functions for generating simulated bulk samples from a single cell dataset.
summarise_children | sum up the fraction of all child nodes to a single value. Take into account which cell types are optional.
timer | Source code for the TIMER deconvolution method.
timer_available_cancers | TIMER signatures are cancer specific. This is the list of available cancer types.
xCell.data | Data object from xCell.