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[pre-commit.ci] pre-commit autoupdate #192

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86aae55
[pre-commit.ci] pre-commit autoupdate
pre-commit-ci[bot] Jul 6, 2026
6a3801f
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Jul 6, 2026
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2 changes: 1 addition & 1 deletion .pre-commit-config.yaml
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Expand Up @@ -2,7 +2,7 @@
# R specific hooks: https://github.com/lorenzwalthert/precommit
repos:
- repo: https://github.com/lorenzwalthert/precommit
rev: v0.4.3.9014
rev: v0.4.3.9026
hooks:
- id: style-files
args: [--style_pkg=styler, --style_fun=tidyverse_style]
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1 change: 0 additions & 1 deletion R/BASE.R
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Expand Up @@ -121,7 +121,6 @@ base_algorithm <- function(data, reg, perm = 100, median.norm = T) {
}



#' Souce code to create the compendium used kin the BASE algorithm, containing
#' up- and down-regulated weight sets that specify the
# specificity by which each gene is expressed by a given cell.
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4 changes: 0 additions & 4 deletions R/custom_deconvolution_methods.R
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Expand Up @@ -15,7 +15,6 @@
NULL



#' List of methods that support the use of a custom signature
#'
#' The available methods are
Expand All @@ -40,7 +39,6 @@ custom_deconvolution_methods <- c(
###########################################################################



#' Deconvolute using CIBERSORT or CIBERSORT abs and a custom signature matrix.
#'
#' @param gene_expression_matrix a m x n matrix with m genes and n samples
Expand Down Expand Up @@ -127,8 +125,6 @@ deconvolute_epic_custom <- function(gene_expression_matrix, signature_matrix,
}




#' Deconvolute using ConsesnusTME and a custom signature matrix
#'
#' @param gene_expression_matrix a m x n matrix with m genes and n samples. Data
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1 change: 0 additions & 1 deletion R/estimate.R
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Expand Up @@ -9,7 +9,6 @@
#'



#' ESTIMATE algortihm: This function computes stromal, immune, and ESTIMATE scores
#' per sample using gene expression data, through GSEA. The ESTIMATE score is used
#' to compute an estimate of the tumor purity
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2 changes: 0 additions & 2 deletions R/immune_deconvolution_methods.R
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Expand Up @@ -73,7 +73,6 @@ set_cibersort_mat <- function(path) {
}



###########################################################################
# Deconvolution functions for consistently accessing each method
#
Expand Down Expand Up @@ -380,7 +379,6 @@ deconvolute_consensus_tme <- function(gene_expression_matrix,
}



#' Annotate unified cell_type names
#'
#' map the cell_types of the different methods to a common name
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2 changes: 0 additions & 2 deletions R/mouse_cell_type_mapping.R
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Expand Up @@ -54,8 +54,6 @@ reduce_mouse_cell_types <- function(deconvolution.results,
}




#' This function returns the list of all cell types in BASE/DCQ results,
#' along with the cell type they are mapped to
#' @param method the method for which we want to get the cell types
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4 changes: 0 additions & 4 deletions R/mouse_deconvolution_methods.R
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Expand Up @@ -34,8 +34,6 @@ deconvolution_methods_mouse <- c(
)




############################################################################
# Deconvolution functions for consistently accessing each method
#
Expand All @@ -45,7 +43,6 @@ deconvolution_methods_mouse <- c(
############################################################################



#' Deconvolute using mMCP-counter
#'
#' @param gene_expression_matrix a m x n matrix with m genes and n samples. Should be TPM normalized
Expand Down Expand Up @@ -202,7 +199,6 @@ deconvolute_base_algorithm <- function(gene_expression_matrix, n_permutations =
}



#' Perform deconvolution on a mouse RNAseq dataset
#'
#' @param gene_expression_matrix a m x n matrix with m genes and n samples.
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4 changes: 0 additions & 4 deletions tests/testthat/test_custom_matrices.R
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Expand Up @@ -4,7 +4,6 @@ test_mat <- read_tsv("bulk_mat.tsv") %>%
test_mat <- as.matrix(test_mat)



test_that("seqimmucc works with a custom signature matrix", {
test_mat <- dataset_racle$expr_mat
sign_mat <- matrix(120 * runif(15000), ncol = 10)
Expand All @@ -22,7 +21,6 @@ test_that("seqimmucc works with a custom signature matrix", {
})



test_that("EPIC works with a custom signature matrix", {
sign_mat <- matrix(120 * runif(10 * nrow(test_mat)), ncol = 10)
colnames(sign_mat) <- c(
Expand Down Expand Up @@ -72,8 +70,6 @@ test_that("EPIC works with a custom signature matrix and variances", {
})




test_that("ConsensusTME works with a custom signature matrix", {
sign_mat <- matrix(120 * runif(1500), ncol = 10)
colnames(sign_mat) <- c(
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