## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", warning = FALSE, message = FALSE, fig.width = 8, fig.height = 7, fig.align = "center", out.width = "100%" ) ## ----library------------------------------------------------------------------ library(ggchord) library(ggplot2) data(seq_data_example) data(ribbon_data_example) data(gene_data_example) ## ----import-helpers, eval=FALSE----------------------------------------------- # library(ggchord) # # # FASTA -> seq_data（读取并合并全部示例 FASTA 文件） # seq_data <- invisible(read_fasta_lengths(files = "examples/fasta/*.fna")) # # # BLAST -outfmt 6/7 表格输出 -> ribbon_data（12 或 17 列自动识别） # ribbon_data <- invisible(read_blast(files = "examples/blastn/*.o7")) # # # GFF3 -> gene_data（默认取 CDS；anno 从 product/Name/... 属性提取） # gene_data <- invisible(read_gff3(files = "examples/gff3/*.gff3")) # # ggchord(seq_data, ribbon_data, gene_data) + # geom_seq() + geom_ribbon() + geom_gene() ## ----validate-clean, eval=FALSE----------------------------------------------- # data(seq_data_example) # data(ribbon_data_example) # data(gene_data_example) # # validate_ggchord_data(seq_data_example, ribbon_data_example, gene_data_example) # # clean_ggchord_data(seq_data_example, ribbon_data_example, gene_data_example, # unknown_id = "drop", out_of_range = "clip", # reversed_interval = "sort", invalid_pident = "clip") ## ----ribbon-tidy, eval=FALSE-------------------------------------------------- # kept <- filter_ggchord_ribbons(ribbon_data_example, min_pident = 90, # drop_self_links = TRUE, # sort_by = "pident") # dedup <- deduplicate_ggchord_ribbons(kept$data, by = "exact", # keep = "best_pident") # merged <- merge_ggchord_ribbons(dedup$data, max_gap = 0) ## ----tutorial-seq, eval=FALSE------------------------------------------------- # ggchord(seq_data_example) + # geom_seq() ## ----tutorial-seq-img, echo=FALSE, fig.cap="序列弧线。"---------------------------- knitr::include_graphics("../man/figures/seq_only_default.png") ## ----tutorial-ribbon, eval=FALSE---------------------------------------------- # ggchord(seq_data_example, ribbon_data_example) + # geom_seq() + geom_ribbon() ## ----tutorial-ribbon-img, echo=FALSE, fig.cap="按相似度着色的连接带。"------------------- knitr::include_graphics("../man/figures/ribbon_pident.png") ## ----tutorial-gene, eval=FALSE------------------------------------------------ # ggchord(seq_data_example, gene_data = gene_data_example) + # geom_seq() + geom_gene() + geom_gene_label_repel() ## ----tutorial-gene-img, echo=FALSE, fig.cap="带防重叠标签的基因箭头。"-------------------- knitr::include_graphics("../man/figures/gene_repel.png") ## ----tutorial-axis, eval=FALSE------------------------------------------------ # ggchord(seq_data_example) + # geom_seq() + geom_axis() + geom_seq_label() ## ----tutorial-axis-img, echo=FALSE, fig.cap="坐标轴与序列标签。"----------------------- knitr::include_graphics("../man/figures/axis_seq_label.png") ## ----tutorial-group, eval=FALSE----------------------------------------------- # seq_grouped <- transform(seq_data_example, # seq_group = c("host", "host", "phage", "phage")) # # ggchord(seq_grouped, ribbon_data_example, gene_data_example) + # geom_seq(seq_group = "seq_group", # seq_group_colors = c(host = "#E41A1C", phage = "#377EB8")) + # geom_ribbon() + geom_gene() ## ----tutorial-group-img, echo=FALSE, fig.cap="带组间空隙和组标签的分组序列。"---------------- knitr::include_graphics("../man/figures/tutorial_seq_group.png") ## ----tutorial-ribbon-map, eval=FALSE------------------------------------------ # rb_scored <- transform(ribbon_data_example, # bitscore = seq_len(nrow(ribbon_data_example)) * 10) # # ggchord(seq_data_example, rb_scored) + # geom_seq() + # geom_ribbon(ribbon_color_by = "bitscore", # ribbon_alpha_by = "bitscore", # ribbon_direction = "linetype") ## ----tutorial-ribbon-map-img, echo=FALSE, fig.cap="连续填充、透明度与方向映射。"------------ knitr::include_graphics("../man/figures/tutorial_ribbon_mapping.png") ## ----tutorial-highlight, eval=FALSE------------------------------------------- # regions <- data.frame(seq_id = "MT108731.1", # start = 1000, end = 4000, color = "orange") # # ggchord(seq_data_example, ribbon_data_example) + # geom_seq() + geom_ribbon() + # geom_seq_region(regions = regions) + # geom_ribbon_highlight(ribbon_ids = 1) ## ----tutorial-highlight-img, echo=FALSE, fig.cap="序列区间与连接带高亮。"---------------- knitr::include_graphics("../man/figures/tutorial_highlights.png") ## ----tutorial-feature, eval=FALSE--------------------------------------------- # features <- data.frame(seq_id = c("MT108731.1", "MT118296.1"), # start = c(1000, 500), end = c(4000, 2000), # strand = c("+", "-"), type = c("CDS", "tRNA")) # # ggchord(seq_data_example, ribbon_data_example) + # geom_seq() + geom_ribbon() + geom_feature(features) ## ----tutorial-feature-img, echo=FALSE, fig.cap="用 geom_feature() 绘制的通用 feature。"---- knitr::include_graphics("../man/figures/tutorial_features.png") ## ----tutorial-theme, eval=FALSE----------------------------------------------- # ggchord(seq_data_example, ribbon_data_example, gene_data_example) + # geom_seq() + geom_ribbon() + geom_gene() + geom_axis() + # scale_color_manual(values = c("MT108731.1" = "#E41A1C", # "MT118296.1" = "#377EB8", # "OQ646790.1" = "#4DAF4A", # "OR222515.1" = "#984EA3")) + # theme(panel.background = element_rect(fill = "grey95"), # legend.position = "bottom", legend.box = "horizontal") ## ----tutorial-theme-img, echo=FALSE, fig.cap="统一图例的主题化图形。"-------------------- knitr::include_graphics("../man/figures/legend_bottom.png") ## ----tutorial-fine, eval=FALSE------------------------------------------------ # ggchord(seq_data_example, ribbon_data_example, gene_data_example, # title = "ggchord") + # geom_seq(seq_radius = c(3.3, 2.5, 1.8, 1.25), # seq_orientation = c(-1, -1, 1, -1), # seq_colors = c("MT108731.1" = "#E76F51", # "MT118296.1" = "#264653", # "OQ646790.1" = "#2A9D8F", # "OR222515.1" = "#D9A62E")) + # geom_ribbon(ribbon_alpha = 0.45) + # geom_gene() + # geom_gene_label_repel(gene_label_size = 2, seed = 42) + # geom_seq_label() + # geom_axis() + # theme(plot.background = element_rect(fill = "#FBF9F6", colour = NA), # panel.background = element_rect(fill = "#FBF9F6", colour = NA)) ## ----tutorial-fine-img, echo=FALSE, fig.cap="精细控制下的完整弦图。"--------------------- knitr::include_graphics("../man/figures/combined_fine.png") ## ----flexible-formats, eval=FALSE--------------------------------------------- # # 1. 全部使用同一个值 # gene_label_rotation = 20 # # # 2. 每条序列按链方向分别指定 # gene_label_rotation = c("+" = -15, "-" = -45) # # # 3. 按序列 ID 名称指定 # gene_label_rotation = list( # "MT118296.1" = c("+" = -15, "-" = -45), # "OR222515.1" = c("+" = 30, "-" = -30), # "MT108731.1" = c("+" = 15, "-" = -15), # "OQ646790.1" = c("+" = 0, "-" = 0) # ) # # # 4. 按序列顺序指定（"1" 表示第一条序列） # gene_label_rotation = list( # "1" = c("+" = -15, "-" = -45), # "2" = c("+" = 30, "-" = -30), # "3" = c("+" = 15, "-" = -15), # "4" = c("+" = 0, "-" = 0) # ) # # # 5. 无名列表：按序列顺序（与 #4 等价） # gene_label_rotation = list( # c("+" = -15, "-" = -45), # c("+" = 30, "-" = -30), # c("+" = 15, "-" = -15), # c("+" = 0, "-" = 0) # ) # # # 6. 长度为一的列表会循环应用到每条序列 # gene_label_rotation = list(20)