Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
warning = FALSE,
message = FALSE,
eval=FALSE,
echo=TRUE
)
## ----message=FALSE, warning=FALSE---------------------------------------------
# library(itol.toolkit) # main package
# library(dplyr) # data manipulation
# library(data.table) # file read
# library(ape) # tree operation
# library(stringr) # string operation
# library(tidyr) # data manipulation
## ----message=FALSE, warning=FALSE---------------------------------------------
# tree <- system.file("extdata","tree_of_itol_templates.tree",package = "itol.toolkit")
# data("template_groups")
# data("template_parameters_count")
# hub <- create_hub(tree = tree)
#
# ## 1,7 data
# df_group <- data.frame(id = unique(template_groups$group),
# data = unique(template_groups$group))
#
# ## 2 data
# df_count <- cbind(template_groups,as.data.frame(rowSums(template_parameters_count)))
#
# ## 3 data
# df_rename <- data.frame(id = template_groups$template,
# new_label = str_to_title(str_replace_all(template_groups$template,"_"," ")))
#
# ## 5 data
# tab_tmp_01 <- as.data.frame(t(template_parameters_count))
# tab_tmp_connect <- convert_01_to_connect(tab_tmp_01)
# tab_tmp_connect <- full_join(tab_tmp_connect, template_groups, by=c("row" = "template"))
# tab_tmp_connect <- tab_tmp_connect %>% filter(val > 10) %>% filter(row != col)
#
# ## 6 data
# tab_tmp <- fread(system.file("extdata","parameter_groups.txt",package = "itol.toolkit"))
# tab_id_group <- tab_tmp[,c(1,2)]
# tab_tmp <- tab_tmp[,-c(1,2)]
# tab_tmp_01 <- convert_01(object = tab_tmp)
# tab_tmp_01 <- cbind(tab_id_group,tab_tmp_01)
#
# order <- c("type","separator","profile","field","common themes","specific themes","data")
#
# tab_tmp_01_long <- tab_tmp_01 %>% tidyr::gather(key = "variable",value = "value",c(-parameter,-group))
#
# template_start_group <- tab_tmp_01_long %>% group_by(group,variable) %>% summarise(sublen = sum(value)) %>% tidyr::spread(key=variable,value=sublen)
# template_start_group$group <- factor(template_start_group$group,levels = order)
# template_start_group <- template_start_group %>% arrange(group)
# start_group <- data.frame(Var1 = template_start_group$group, Freq = apply(template_start_group[,-1], 1, max))
# start_group$start <- 0
# for (i in 2:nrow(start_group)) {
# start_group$start[i] <- sum(start_group$Freq[1:(i-1)])
# }
# template_start_group[template_start_group == 0] <- NA
# template_end_group <- template_start_group[,2:(ncol(template_start_group)-1)] + start_group$start
# template_end_group <- data.frame(group = order,template_end_group)
# template_end_group_long <- template_end_group %>% tidyr::gather(key = "variable",value = "value",-group)
# names(template_end_group_long)[3] <- "end"
# template_end_group_long$start <- rep(start_group$start,length(unique(template_end_group_long$variable)))
# template_end_group_long <- template_end_group_long %>% na.omit()
# template_end_group_long$length <- sum(start_group$Freq)
# template_end_group_long <- template_end_group_long[,c(2,5,4,3,1)]
# template_end_group_long$group <- factor(template_end_group_long$group,levels = order)
#
# ## 8 data
# df_values <- fread(system.file("extdata","templates_frequence.txt",package = "itol.toolkit"))
# names(df_values) <- c("id","Li,S. et al. (2022) J. Hazard. Mater.","Zheng,L. et al. (2022) Environ. Pollut.","Welter,D.K. et al. (2021) mSystems","Zhang,L et al. (2022) Nat. Commun.","Rubbens,P. et al. (2019) mSystems","Laidoudi,Y. et al. (2022) Pathogens","Wang,Y. et al. (2022) Nat. Commun.","Ceres,K.M. et al. (2022) Microb. Genomics","Youngblut,N.D. et al. (2019) Nat. Commun.","BalvĂn,O. et al. (2018) Sci. Rep.","Prostak,S.M. et al. (2021) Curr. Biol.","Dijkhuizen,L.W. et al. (2021) Front. Plant Sci.","Zhang,X. et al. (2022) Microbiol. Spectr.","Peris,D. et al. (2022) PLOS Genet.","Denamur,E. et al. (2022) PLOS Genet.","Dezordi,F.Z. et al. (2022) bioRxiv","Lin,Y. et al. (2021) Microbiome","Wang,Y. et al. (2022) bioRxiv","Qi,Z. et al. (2022) Food Control","Zhou,X. et al. (2022) Food Res. Int.","Zhou,X. et al. (2022) Nat. Commun.")
# names(df_values) <- str_remove_all(names(df_values),"[()]")
# names(df_values) <- str_replace_all(names(df_values),",","-")
#
# ## 9 data
# df_value <- fread(system.file("extdata","templates_frequence.txt",package = "itol.toolkit"))
# df_value <- df_value %>% tidyr::pivot_longer(-templates) %>% na.omit() %>% select(templates,value) %>% as.data.frame()
# df_value$value <- log(df_value$value)
## ----tree colors clade in node, message=FALSE, warning=FALSE------------------
# unit_1 <- create_unit(data = df_group,
# key = "E1_template_types",
# type = "TREE_COLORS",
# subtype = "clade",
# line_type = c(rep("normal",4),"dashed"),
# size_factor = 5,
# tree = tree)
#
# unit_2 <- create_unit(data = df_count,
# key = "E2_parameter_number",
# type = "DATASET_SYMBOL",
# position = 1,
# tree = tree)
#
# unit_3 <- create_unit(data = df_rename,
# key = "E3_template_rename",
# type = "LABELS",
# tree = tree)
#
# unit_4 <- create_unit(data = template_groups,
# key = "E4_template_name_color",
# type = "DATASET_STYLE",
# subtype = "label",
# position = "node",
# size_factor = 1.5,
# tree = tree)
#
# unit_5 <- create_unit(data = tab_tmp_connect[,1:4],
# key = "E5_template_similarity",
# type = "DATASET_CONNECTION",
# tree = tree)
#
# unit_6 <- create_unit(data = template_end_group_long,
# key = "E6_template_parameters_structure",
# type = "DATASET_DOMAINS",
# tree = tree)
#
# unit_7 <- create_unit(data = df_group,
# key = "E7_template_types",
# type = "DATASET_COLORSTRIP",
# tree = tree)
#
# unit_8 <- create_unit(data = df_values,
# key = "E8_usage_count_among_publications",
# type = "DATASET_HEATMAP",
# tree = tree)
#
# unit_9 <- create_unit(data = df_value,
# key = "E9_log_transformed_usage_count",
# type = "DATASET_BOXPLOT",
# tree = tree)
## ----message=FALSE------------------------------------------------------------
# unit_2@specific_themes$basic_plot$size_max <- 40
#
# unit_5@specific_themes$basic_plot$size_max <- 100
#
# unit_8@specific_themes$heatmap$color$min <- "#ffd966"
# unit_8@specific_themes$heatmap$color$max <- "#cc0000"
# unit_8@specific_themes$heatmap$use_mid <- 0
#
# unit_9@specific_themes$basic_plot$size_max <- 100
## -----------------------------------------------------------------------------
# hub <- hub +
# unit_1 +
# unit_2 +
# unit_3 +
# unit_4 +
# unit_5 +
# unit_6 +
# unit_7 +
# unit_8 +
# unit_9
#
# write_hub(hub,getwd())
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