From e48517bccf1f19bad41ad773303c5bc7acf06e79 Mon Sep 17 00:00:00 2001
From: browaeysrobin <robin.browaeys@ugent.be>
Date: Sat, 11 May 2024 10:15:05 +0200
Subject: [PATCH] Fix bug no default min_cells some functions

---
 DESCRIPTION                                               | 2 +-
 R/condition_specific_celltypes.R                          | 8 ++++----
 R/expression_processing.R                                 | 1 +
 R/lr_target_correlation.R                                 | 2 +-
 R/pipeline_wrappers.R                                     | 8 ++++----
 R/prioritization.R                                        | 8 ++++----
 man/add_extra_criterion.Rd                                | 2 +-
 man/generate_prioritization_tables.Rd                     | 2 +-
 ...zation_tables_condition_specific_celltypes_receiver.Rd | 2 +-
 ...tization_tables_condition_specific_celltypes_sender.Rd | 2 +-
 ...prioritization_tables_sampleAgnostic_multifactorial.Rd | 2 +-
 man/get_abundance_info.Rd                                 | 2 +-
 man/get_top_n_lr_pairs.Rd                                 | 2 +-
 man/lr_target_prior_cor_inference.Rd                      | 2 +-
 man/prioritize_condition_specific_receiver.Rd             | 2 +-
 man/prioritize_condition_specific_sender.Rd               | 2 +-
 man/process_abund_info.Rd                                 | 1 +
 man/process_abundance_expression_info.Rd                  | 2 +-
 18 files changed, 27 insertions(+), 25 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index aa55f81..3813984 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -63,4 +63,4 @@ VignetteBuilder:
   knitr
 Remotes: 
   github::saeyslab/nichenetr
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
diff --git a/R/condition_specific_celltypes.R b/R/condition_specific_celltypes.R
index ea45a6e..562097f 100644
--- a/R/condition_specific_celltypes.R
+++ b/R/condition_specific_celltypes.R
@@ -23,7 +23,7 @@
 #' batches = NA
 #' contrasts_oi = c("'High-Low','Low-High'")
 #' contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-#' 
+#' min_cells = 10
 #' metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 #' colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 #' abundance_data = metadata_abundance %>% tibble::as_tibble() %>% dplyr::group_by(sample_id , celltype_id) %>% dplyr::count() %>% dplyr::inner_join(metadata_abundance %>% tibble::as_tibble() %>% dplyr::distinct(sample_id , group_id ))
@@ -251,7 +251,7 @@ generate_prioritization_tables_condition_specific_celltypes_sender = function(se
 #' batches = NA
 #' contrasts_oi = c("'High-Low','Low-High'")
 #' contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-#' 
+#' min_cells = 10
 #' metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 #' colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 #' abundance_data = metadata_abundance %>% tibble::as_tibble() %>% dplyr::group_by(sample_id , celltype_id) %>% dplyr::count() %>% dplyr::inner_join(metadata_abundance %>% tibble::as_tibble() %>% dplyr::distinct(sample_id , group_id ))
@@ -482,7 +482,7 @@ generate_prioritization_tables_condition_specific_celltypes_receiver = function(
 #' batches = NA
 #' contrasts_oi = c("'High-Low','Low-High'")
 #' contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-#' 
+#' min_cells = 10
 #' metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 #' colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 #' abundance_data = metadata_abundance %>% tibble::as_tibble() %>% dplyr::group_by(sample_id , celltype_id) %>% dplyr::count() %>% dplyr::inner_join(metadata_abundance %>% tibble::as_tibble() %>% dplyr::distinct(sample_id , group_id ))
@@ -649,7 +649,7 @@ prioritize_condition_specific_sender <- function(
 #' batches = NA
 #' contrasts_oi = c("'High-Low','Low-High'")
 #' contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-#' 
+#' min_cells = 10
 #' metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 #' colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 #' abundance_data = metadata_abundance %>% tibble::as_tibble() %>% dplyr::group_by(sample_id , celltype_id) %>% dplyr::count() %>% dplyr::inner_join(metadata_abundance %>% tibble::as_tibble() %>% dplyr::distinct(sample_id , group_id ))
diff --git a/R/expression_processing.R b/R/expression_processing.R
index 53313bd..aa58e36 100644
--- a/R/expression_processing.R
+++ b/R/expression_processing.R
@@ -786,6 +786,7 @@ process_info_to_ic = function(info_object, ic_type = "sender", lr_network){
 #' sample_id = "tumor"
 #' group_id = "pEMT"
 #' celltype_id = "celltype"
+#' min_cells = 10
 #' metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)]
 #' colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 #' abundance_data = metadata_abundance %>% tibble::as_tibble() %>% dplyr::group_by(sample_id , celltype_id) %>% dplyr::count() %>% dplyr::inner_join(metadata_abundance %>% dplyr::distinct(sample_id , group_id ))
diff --git a/R/lr_target_correlation.R b/R/lr_target_correlation.R
index 889b5da..dadbe37 100644
--- a/R/lr_target_correlation.R
+++ b/R/lr_target_correlation.R
@@ -32,7 +32,7 @@
 #' batches = NA
 #' contrasts_oi = c("'High-Low','Low-High'")
 #' contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-#' 
+#' min_cells = 10
 #' metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 #' colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 #' abundance_data = metadata_abundance %>% tibble::as_tibble() %>% dplyr::group_by(sample_id , celltype_id) %>% dplyr::count() %>% dplyr::inner_join(metadata_abundance %>% tibble::as_tibble() %>% dplyr::distinct(sample_id , group_id ))
diff --git a/R/pipeline_wrappers.R b/R/pipeline_wrappers.R
index 11bcf36..001d1ae 100644
--- a/R/pipeline_wrappers.R
+++ b/R/pipeline_wrappers.R
@@ -1,7 +1,7 @@
 #' @title get_abundance_info
 #'
 #' @description \code{get_abundance_info} Visualize cell type abundances.
-#' @usage get_abundance_info(sce, sample_id, group_id, celltype_id, min_cells, senders_oi, receivers_oi, batches = NA)
+#' @usage get_abundance_info(sce, sample_id, group_id, celltype_id, min_cells = 10, senders_oi, receivers_oi, batches = NA)
 #'
 #' @inheritParams multi_nichenet_analysis
 #' @inheritParams combine_sender_receiver_info_ic
@@ -27,7 +27,7 @@
 #'
 #' @export
 #'
-get_abundance_info = function(sce, sample_id, group_id, celltype_id, min_cells, senders_oi, receivers_oi, batches = NA){
+get_abundance_info = function(sce, sample_id, group_id, celltype_id, min_cells = 10, senders_oi, receivers_oi, batches = NA){
   
   requireNamespace("dplyr")
   requireNamespace("ggplot2")
@@ -211,7 +211,7 @@ get_abundance_info = function(sce, sample_id, group_id, celltype_id, min_cells,
 #' @title process_abundance_expression_info
 #'
 #' @description \code{process_abundance_expression_info} Visualize cell type abundances. Calculate the average and fraction of expression of each gene per sample and per group. Calculate relative abundances of cell types as well. Under the hood, the following functions are used: `get_avg_frac_exprs_abund`, `process_info_to_ic`, `combine_sender_receiver_info_ic`
-#' @usage process_abundance_expression_info(sce, sample_id, group_id, celltype_id, min_cells, senders_oi, receivers_oi, lr_network, batches = NA, frq_list, abundance_info)
+#' @usage process_abundance_expression_info(sce, sample_id, group_id, celltype_id, min_cells = 10, senders_oi, receivers_oi, lr_network, batches = NA, frq_list, abundance_info)
 #'
 #' @inheritParams multi_nichenet_analysis
 #' @inheritParams combine_sender_receiver_info_ic
@@ -243,7 +243,7 @@ get_abundance_info = function(sce, sample_id, group_id, celltype_id, min_cells,
 #'
 #' @export
 #'
-process_abundance_expression_info = function(sce, sample_id, group_id, celltype_id, min_cells, senders_oi, receivers_oi, lr_network, batches = NA, frq_list, abundance_info){
+process_abundance_expression_info = function(sce, sample_id, group_id, celltype_id, min_cells = 10, senders_oi, receivers_oi, lr_network, batches = NA, frq_list, abundance_info){
   
   requireNamespace("dplyr")
   requireNamespace("ggplot2")
diff --git a/R/prioritization.R b/R/prioritization.R
index 0916e69..3f74b29 100644
--- a/R/prioritization.R
+++ b/R/prioritization.R
@@ -37,7 +37,7 @@ scale_quantile_adapted = function(x, outlier_cutoff = 0){
 #' batches = NA
 #' contrasts_oi = c("'High-Low','Low-High'")
 #' contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-#' 
+#' min_cells = 10
 #' metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 #' colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 #' abundance_data = metadata_abundance %>% tibble::as_tibble() %>% dplyr::group_by(sample_id , celltype_id) %>% dplyr::count() %>% dplyr::inner_join(metadata_abundance %>% tibble::as_tibble() %>% dplyr::distinct(sample_id , group_id ))
@@ -273,7 +273,7 @@ generate_prioritization_tables = function(sender_receiver_info, sender_receiver_
 #' batches = NA
 #' contrasts_oi = c("'High-Low','Low-High'")
 #' contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-#' 
+#' min_cells = 10
 #' metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 #' colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 #' abundance_data = metadata_abundance %>% tibble::as_tibble() %>% dplyr::group_by(sample_id , celltype_id) %>% dplyr::count() %>% dplyr::inner_join(metadata_abundance %>% tibble::as_tibble() %>% dplyr::distinct(sample_id , group_id ))
@@ -381,7 +381,7 @@ get_top_n_lr_pairs = function(prioritization_tables, top_n, groups_oi = NULL, se
 #' batches = NA
 #' contrasts_oi = c("'High-Low','Low-High'")
 #' contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-#' 
+#' min_cells = 10
 #' metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 #' colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 #' abundance_data = metadata_abundance %>% tibble::as_tibble() %>% dplyr::group_by(sample_id , celltype_id) %>% dplyr::count() %>% dplyr::inner_join(metadata_abundance %>% tibble::as_tibble() %>% dplyr::distinct(sample_id , group_id ))
@@ -672,7 +672,7 @@ generate_prioritization_tables_tests = function(sender_receiver_info, sender_rec
 #' batches = NA
 #' contrasts_oi = c("'High-Low','Low-High'")
 #' contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-#' 
+#' min_cells = 10
 #' metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 #' colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 #' abundance_data = metadata_abundance %>% tibble::as_tibble() %>% dplyr::group_by(sample_id , celltype_id) %>% dplyr::count() %>% dplyr::inner_join(metadata_abundance %>% tibble::as_tibble() %>% dplyr::distinct(sample_id , group_id ))
diff --git a/man/add_extra_criterion.Rd b/man/add_extra_criterion.Rd
index 1f0336f..5a41a71 100644
--- a/man/add_extra_criterion.Rd
+++ b/man/add_extra_criterion.Rd
@@ -33,7 +33,7 @@ celltype_id = "celltype"
 batches = NA
 contrasts_oi = c("'High-Low','Low-High'")
 contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-
+min_cells = 10
 metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 abundance_data = metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::group_by(sample_id , celltype_id) \%>\% dplyr::count() \%>\% dplyr::inner_join(metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::distinct(sample_id , group_id ))
diff --git a/man/generate_prioritization_tables.Rd b/man/generate_prioritization_tables.Rd
index 1457e41..61650ad 100644
--- a/man/generate_prioritization_tables.Rd
+++ b/man/generate_prioritization_tables.Rd
@@ -50,7 +50,7 @@ celltype_id = "celltype"
 batches = NA
 contrasts_oi = c("'High-Low','Low-High'")
 contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-
+min_cells = 10
 metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 abundance_data = metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::group_by(sample_id , celltype_id) \%>\% dplyr::count() \%>\% dplyr::inner_join(metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::distinct(sample_id , group_id ))
diff --git a/man/generate_prioritization_tables_condition_specific_celltypes_receiver.Rd b/man/generate_prioritization_tables_condition_specific_celltypes_receiver.Rd
index 554a618..c12829e 100644
--- a/man/generate_prioritization_tables_condition_specific_celltypes_receiver.Rd
+++ b/man/generate_prioritization_tables_condition_specific_celltypes_receiver.Rd
@@ -50,7 +50,7 @@ celltype_id = "celltype"
 batches = NA
 contrasts_oi = c("'High-Low','Low-High'")
 contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-
+min_cells = 10
 metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 abundance_data = metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::group_by(sample_id , celltype_id) \%>\% dplyr::count() \%>\% dplyr::inner_join(metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::distinct(sample_id , group_id ))
diff --git a/man/generate_prioritization_tables_condition_specific_celltypes_sender.Rd b/man/generate_prioritization_tables_condition_specific_celltypes_sender.Rd
index 6e65073..74ea0db 100644
--- a/man/generate_prioritization_tables_condition_specific_celltypes_sender.Rd
+++ b/man/generate_prioritization_tables_condition_specific_celltypes_sender.Rd
@@ -50,7 +50,7 @@ celltype_id = "celltype"
 batches = NA
 contrasts_oi = c("'High-Low','Low-High'")
 contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-
+min_cells = 10
 metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 abundance_data = metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::group_by(sample_id , celltype_id) \%>\% dplyr::count() \%>\% dplyr::inner_join(metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::distinct(sample_id , group_id ))
diff --git a/man/generate_prioritization_tables_sampleAgnostic_multifactorial.Rd b/man/generate_prioritization_tables_sampleAgnostic_multifactorial.Rd
index 07f3be6..72d431f 100644
--- a/man/generate_prioritization_tables_sampleAgnostic_multifactorial.Rd
+++ b/man/generate_prioritization_tables_sampleAgnostic_multifactorial.Rd
@@ -50,7 +50,7 @@ celltype_id = "celltype"
 batches = NA
 contrasts_oi = c("'High-Low','Low-High'")
 contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-
+min_cells = 10
 metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 abundance_data = metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::group_by(sample_id , celltype_id) \%>\% dplyr::count() \%>\% dplyr::inner_join(metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::distinct(sample_id , group_id ))
diff --git a/man/get_abundance_info.Rd b/man/get_abundance_info.Rd
index 2fb8ae6..27692a2 100644
--- a/man/get_abundance_info.Rd
+++ b/man/get_abundance_info.Rd
@@ -4,7 +4,7 @@
 \alias{get_abundance_info}
 \title{get_abundance_info}
 \usage{
-get_abundance_info(sce, sample_id, group_id, celltype_id, min_cells, senders_oi, receivers_oi, batches = NA)
+get_abundance_info(sce, sample_id, group_id, celltype_id, min_cells = 10, senders_oi, receivers_oi, batches = NA)
 }
 \arguments{
 \item{sce}{SingleCellExperiment object of the scRNAseq data of interest. Contains both sender and receiver cell types.}
diff --git a/man/get_top_n_lr_pairs.Rd b/man/get_top_n_lr_pairs.Rd
index 75ba25f..94f2d0e 100644
--- a/man/get_top_n_lr_pairs.Rd
+++ b/man/get_top_n_lr_pairs.Rd
@@ -37,7 +37,7 @@ celltype_id = "celltype"
 batches = NA
 contrasts_oi = c("'High-Low','Low-High'")
 contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-
+min_cells = 10
 metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 abundance_data = metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::group_by(sample_id , celltype_id) \%>\% dplyr::count() \%>\% dplyr::inner_join(metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::distinct(sample_id , group_id ))
diff --git a/man/lr_target_prior_cor_inference.Rd b/man/lr_target_prior_cor_inference.Rd
index 5257c97..a1621b6 100644
--- a/man/lr_target_prior_cor_inference.Rd
+++ b/man/lr_target_prior_cor_inference.Rd
@@ -45,7 +45,7 @@ celltype_id = "celltype"
 batches = NA
 contrasts_oi = c("'High-Low','Low-High'")
 contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-
+min_cells = 10
 metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 abundance_data = metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::group_by(sample_id , celltype_id) \%>\% dplyr::count() \%>\% dplyr::inner_join(metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::distinct(sample_id , group_id ))
diff --git a/man/prioritize_condition_specific_receiver.Rd b/man/prioritize_condition_specific_receiver.Rd
index 6cba11c..fda5fe0 100644
--- a/man/prioritize_condition_specific_receiver.Rd
+++ b/man/prioritize_condition_specific_receiver.Rd
@@ -49,7 +49,7 @@ celltype_id = "celltype"
 batches = NA
 contrasts_oi = c("'High-Low','Low-High'")
 contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-
+min_cells = 10
 metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 abundance_data = metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::group_by(sample_id , celltype_id) \%>\% dplyr::count() \%>\% dplyr::inner_join(metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::distinct(sample_id , group_id ))
diff --git a/man/prioritize_condition_specific_sender.Rd b/man/prioritize_condition_specific_sender.Rd
index fe00b3f..986b73b 100644
--- a/man/prioritize_condition_specific_sender.Rd
+++ b/man/prioritize_condition_specific_sender.Rd
@@ -49,7 +49,7 @@ celltype_id = "celltype"
 batches = NA
 contrasts_oi = c("'High-Low','Low-High'")
 contrast_tbl = tibble(contrast = c("High-Low","Low-High"), group = c("High","Low"))
-
+min_cells = 10
 metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)] 
 colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 abundance_data = metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::group_by(sample_id , celltype_id) \%>\% dplyr::count() \%>\% dplyr::inner_join(metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::distinct(sample_id , group_id ))
diff --git a/man/process_abund_info.Rd b/man/process_abund_info.Rd
index 280b343..0900dd8 100644
--- a/man/process_abund_info.Rd
+++ b/man/process_abund_info.Rd
@@ -23,6 +23,7 @@ library(dplyr)
 sample_id = "tumor"
 group_id = "pEMT"
 celltype_id = "celltype"
+min_cells = 10
 metadata_abundance = SummarizedExperiment::colData(sce)[,c(sample_id, group_id, celltype_id)]
 colnames(metadata_abundance) =c("sample_id", "group_id", "celltype_id")
 abundance_data = metadata_abundance \%>\% tibble::as_tibble() \%>\% dplyr::group_by(sample_id , celltype_id) \%>\% dplyr::count() \%>\% dplyr::inner_join(metadata_abundance \%>\% dplyr::distinct(sample_id , group_id ))
diff --git a/man/process_abundance_expression_info.Rd b/man/process_abundance_expression_info.Rd
index 944074f..46ab785 100644
--- a/man/process_abundance_expression_info.Rd
+++ b/man/process_abundance_expression_info.Rd
@@ -4,7 +4,7 @@
 \alias{process_abundance_expression_info}
 \title{process_abundance_expression_info}
 \usage{
-process_abundance_expression_info(sce, sample_id, group_id, celltype_id, min_cells, senders_oi, receivers_oi, lr_network, batches = NA, frq_list, abundance_info)
+process_abundance_expression_info(sce, sample_id, group_id, celltype_id, min_cells = 10, senders_oi, receivers_oi, lr_network, batches = NA, frq_list, abundance_info)
 }
 \arguments{
 \item{sce}{SingleCellExperiment object of the scRNAseq data of interest. Contains both sender and receiver cell types.}