gvmap_manual_v1.0
Dai Yuting
October 11, 2017
gvmap
使用gvmap之前，请先安装 configr（剑峰师兄的大作^_^）和 rsvg这两个包，然后本地安装gvmap包。
library(configr)
library(gvmap)
library(rsvg)
setwd("/Users/daiyuting/Documents/projects/ball/analysis/metarnaseq/develop")
###################################
# step 1, modify your config file
###################################
config_file <- "test_data/gvmap.config.yaml"
data_file_name <- "test_data/gvmap.test.txt"
data_file <- read.table(data_file_name, header = T, sep = "\t")
data_file## SampleName Age Gender Fusion other_fusion KRAS
## 1 C064 Child Female 0 ETV6-PMEL Missense
## 2 C068 Child Male 0 ETV6-BORCS5 Nonsense
## 3 C176 Child Female 0 ETV6-NID1 Missense
## 4 S144 Adult Female 0 ERG-FUS 0
## 5 C093 Child Female 0 RUNX1-UGGT2 0
## 6 C121 Child Female ETV6-RUNX1 0 Frameshift
## 7 C143 Child Female ETV6-RUNX1 0 0
## 8 J44 0 Female 0 ZZZ3-AK5 Missense
## 9 C187 Child Male ETV6-RUNX1 0 Missense
## 10 C084 Child Male ETV6-RUNX1 0 0
## 11 SJHM013480 0 Male ETV6-RUNX1 0 0
## 12 C085 Child Male 0 IKZF1-SETD5 0
## 13 C111 Child Male 0 0 0
## 14 SJBALL015422 Child Female 0 RUNX1-DYRK1A 0
## 15 C091 Child Male 0 RUNX1-PRDM7 0
## 16 SJBALL015479 Child 0 0 PRKCB-NUFIP2 0
## 17 C138 Child 0 0 ARL11-RNASEH2B 0
## P53 NRAS
## 1 Frameshift Missense/Frameshift
## 2 0 0
## 3 0 0
## 4 0 0
## 5 Frameshift 0
## 6 0 Missense/Frameshift/Missense
## 7 Missense 0
## 8 0 0
## 9 0 0
## 10 0 Frameshift
## 11 Frameshift 0
## 12 0 0
## 13 0 0
## 14 0 0
## 15 0 Missense
## 16 0 0
## 17 0 0########################################
# step 2, set output file and run gvmap
########################################
output_svg_name <- "test_data/gvmap.output.svg"
gvmap(data_file = data_file, config_file, output_svg_name)## ** test_data/gvmap.output.svg already exists, the gvmap result will replace it.########################################
# step 2, save as pdf format
########################################
output_pdf_name <- "test_data/gvmap.output.pdf"
rsvg_pdf(output_svg_name, output_pdf_name)
########################################
# config parameter
########################################
# 绘图配置文件
map_config:
sample_col_num: 1 # 样本名所在的列
group_num: 3 # 图例中分组数目
group_1: # group 1的配置文件，分别是行名，颜色主题，对应数据所在列
- ["Age", "binary_col", 2]
- ["Gender","binary_col", 3]
- ["Fusion", "tag_col", 4]
- ["other_fusion", "pool_col", 5]
group_2:
- ["KRAS", "mutation_col", 6]
- ["P53", "mutation_col", 7]
- ["NRAS", "mutation_col", 8]
group_3:
- ["KRAS-2", "mutation_col", 6]
- ["P53-1", "mutation_col", 7]
- ["theme-1", "my_theme_col_1", 4]
- ["theme-2", "my_theme_col_2", 4]
- ["NRAS", "mutation_col", 8]
split_sample: # 拆分样本，即在图例中添加竖线
- "C143"
- "C091"
# 颜色配置文件
color_config:
bg_col: "#EEEEEE" # 背景色，默认浅灰色，适用于0和NA
tag_col: "#696969" # 目标颜色，默认深灰色
binary_col: ["#196ABD", "#C20B01"] # 二元色，默认蓝色和红色，可用于绘制性别这种类型的数据
white_col: "#FFFFFF"
black_col: "#000000"
mutation_col: # 突变色，每种颜色对应一种突变，具体参见测试文件的中的KRAS,P53,NRAS
missense: "#3987CC"
frameshift: "#DB3D3D"
nonsense: "#FF7F0E"
protein_del: "#7F7F7F"
protein_ins: "#8C564B"
one_hit: "#819981"
tow_hit: "#499E49"
three_hit: "#237023"
pool_col: ["#1B9E77", "#D95F02", "#7570B3", "#E7298A", "#66A61E", "#E6AB02", "#A6761D", "#A6CEE3", "#1F78B4", "#B2DF8A", "#33A02C", "#FB9A99", "#E31A1C", "#FDBF6F", "#FF7F00", "#CAB2D6", "#6A3D9A"] # 颜色池，适用于有多个不同元素的列
my_theme_col_1: "#00FFFF" # 自定义颜色，可以无限增加，但是目前只能有一种。参见测试文件中的theme-1
my_theme_col_2: "#CCCC33" # 自定义颜色，可以无限增加，但是目前只能有一种。参见测试文件中的theme-2
# 绘图配置文件
rect_config:
plot_width: 1600 # 画布的宽
plot_height: 1200 # 画布的高
width: 14 # 图例中每个小方块的宽
height: 16 # 图例中每个小方块的高
stroke_width: 0.5 # 图例中每个小方块的描线的粗细
span: 6 # 两组之间的距离
frame: True # 是否加黑色的方框
leg_font_size: 12 # 图例左边的字体大小
sample_font_size: 12 # 图例中样本的字体大小
font_family: "Arial" # 图例中所有文字的字体目前gvmap包的版本为1.0，后续会根据需求增加更多功能。(*^__^*) 。