## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(rmarkdown) library(knitr) library(NeighborFinder) ## ----load-data---------------------------------------------------------------- data(data) data$CRC_JPN[1:5, 1:5] %>% kable() ## ----load-metadata------------------------------------------------------------ data(metadata) metadata$CRC_JPN[1:5, 1:5] %>% kable() ## ----load-taxo---------------------------------------------------------------- data(taxo) taxo[1:5, ] %>% kable() ## ----load-graphs-------------------------------------------------------------- data(graphs) graphs$CRC_JPN[1:5, 1:5] %>% kable() graphs$CRC_JPN[5:10, 87:90] %>% kable() ## ----graph_step--------------------------------------------------------------- # G <- graph_step(data_with_annotation = data$CRC_JPN_CHN_EUR, # col_module_id = "msp_id", # annotation_level = "species", # seed = 20242025 # ) G <- graphs$CRC_JPN_CHN_EUR ## ----choose-params-values----------------------------------------------------- choose_params_values( data_with_annotation = data$CRC_JPN, object_of_interest = "Escherichia coli", sample_size = 100, prev_list = c(0.20, 0.25, 0.30), filtering_list = c(10, 20, 30), graph_file = graphs$CRC_JPN, col_module_id = "msp_id", annotation_level = "species", seed = 123 ) %>% dplyr::mutate(filtering_top = as.numeric(filtering_top)) %>% as.data.frame() %>% kable() ## ----apply-JPN---------------------------------------------------------------- # JAPAN res_CRC_JPN <- apply_NeighborFinder( data_with_annotation = data$CRC_JPN, object_of_interest = "Escherichia coli", col_module_id = "msp_id", annotation_level = "species", prev_level = 0.30, filtering_top = 30, .seed = 123 ) res_CRC_JPN %>% kable() ## ----network-JPN, fig.cap=c("Neighbors of E. coli in Japanese patients with CRC. Edge color encodes coefficient sign: green if positive, red if negative; edge width encodes magnitude.",""), fig.height=4, fig.width=7, message=FALSE---- visualize_network( res_CRC_JPN, taxo, object_of_interest = "Escherichia coli", col_module_id = "msp_id", annotation_level = "species", label_size = 5 ) visualize_network( res_CRC_JPN, taxo, object_of_interest = "Escherichia coli", col_module_id = "msp_id", annotation_level = "species", label_size = 5, annotation_option = TRUE, seed = 2 ) ## ----apply-covariate---------------------------------------------------------- # On CRC patients # CHINA res_CRC_CHN <- apply_NeighborFinder( data$CRC_CHN, object_of_interest = "Escherichia coli", col_module_id = "msp_id", annotation_level = "species", prev_level = 0.30, filtering_top = 30, covar = ~study_accession, meta_df = metadata$CRC_CHN, sample_col = "secondary_sample_accession", .seed = 123 ) # EUROPE res_CRC_EUR <- apply_NeighborFinder( data$CRC_EUR, object_of_interest = "Escherichia coli", col_module_id = "msp_id", annotation_level = "species", prev_level = 0.30, filtering_top = 30, covar = ~study_accession, meta_df = metadata$CRC_EUR, sample_col = "secondary_sample_accession", .seed = 123 ) ## ----network-covariate, fig.cap=c("Neighbors of E. coli in Chinese patients with CRC. Edge color encodes coefficient sign: green if positive, red if negative; edge width encodes magnitude.","Neighbors of E. coli in European patients with CRC. Edge color encodes coefficient sign: green if positive, red if negative; edge width encodes magnitude."), fig.height=4, fig.width=7, message=FALSE---- visualize_network( res_CRC_CHN, taxo, object_of_interest = "Escherichia coli", col_module_id = "msp_id", annotation_level = "species", label_size = 5 ) visualize_network( res_CRC_EUR, taxo, object_of_interest = "Escherichia coli", col_module_id = "msp_id", annotation_level = "species", label_size = 5 ) ## ----intersections-network, fig.cap="Neighbors of E. coli in patients with CRC. Edge color encodes coefficient sign: green if positive, red if negative; edge label indicates the number of datasets in which the interaction was detected; the width is proportional to the mean coefficient value.", fig.height=6, fig.width=8---- intersections_network( res_list = list(res_CRC_JPN, res_CRC_CHN, res_CRC_EUR), taxo, threshold = 2, "Escherichia coli", col_module_id = "msp_id", annotation_level = "species", label_size = 7, edge_label_size = 4, node_size = 15, annotation_option = TRUE, seed = 3 ) ## ----intersections-table------------------------------------------------------ intersections_table( res_list = list(res_CRC_JPN, res_CRC_CHN, res_CRC_EUR), threshold = 2, taxo, col_module_id = "msp_id", annotation_level = "species", "Escherichia coli" ) %>% kable()