RIdeogram
1、加载包
> require(RIdeogram)
2、数据
（1）包内就有的数据集human_karyotype
> data(human_karyotype, package="RIdeogram")
> head(human_karyotype)
Chr Start End CE_start CE_end
1 1 0 248956422 122026459 124932724
2 2 0 242193529 92188145 94090557
3 3 0 198295559 90772458 93655574
4 4 0 190214555 49712061 51743951
5 5 0 181538259 46485900 50059807
6 6 0 170805979 58553888 59829934
（2）包内就有的数据集gene_density
> data(gene_density, package="RIdeogram")
> head(gene_density)
Chr Start End Value
1 1 1 1000000 65
2 1 1000001 2000000 76
3 1 2000001 3000000 35
4 1 3000001 4000000 30
5 1 4000001 5000000 10
6 1 5000001 6000000 10
（3）包内就有的数据集Random_RNAs_500
> data(Random_RNAs_500, package="RIdeogram")
> head(Random_RNAs_500)
Type Shape Chr Start End color
1 tRNA circle 6 69204486 69204568 6a3d9a
2 rRNA box 3 68882967 68883091 33a02c
3 rRNA box 5 55777469 55777587 33a02c
4 rRNA box 21 25202207 25202315 33a02c
5 miRNA triangle 1 86357632 86357687 ff7f00
6 miRNA triangle 11 74399237 74399333 ff7f00
3、绘图
（1）只画出人类染色体组型的图
> ideogram(karyotype = human_karyotype)
> convertSVG("chromosome.svg", device = "png")
chromosome.png
（2）不要中间的“拦腰斩” ---- 着丝粒位置
> human_karyotype <- human_karyotype[,1:3] # 所以只要前3列的chr， start， end 就行了
> ideogram(karyotype = human_karyotype)
> convertSVG("chromosome.svg", device = "png")
chromosome.png
（3）可视化整个人类基因组的基因密度
> ideogram(karyotype = human_karyotype, overlaid = gene_density)
> convertSVG("chromosome.svg", device = "png")
chromosome.png
换个颜色：
> ideogram(karyotype = human_karyotype, overlaid = gene_density, colorset1 = c("#fc8d59", "#ffffbf", "#91bfdb"))
> convertSVG("chromosome.svg", device = "png")
chromosome.png
（4）染色体表象旁边的轨道标签来映射一些全基因组数据
> ideogram(karyotype = human_karyotype, label = Random_RNAs_500, label_type = "marker")
> convertSVG("chromosome.svg", device = "png")
chromosome.png
仔细查看
Random_RNAs_500数据会发现里面是
可以自定义
起个名儿 标注形状 颜色
Type Shape Chr Start End color
1 名儿 circle/box/triangle 6 69204486 69204568 6a3d9a
这个形状除了这3种还能不能换其他的？？？不懂不懂
（5）laber还可以是其他类型
label_type = "heatmap"
> ideogram(karyotype = human_karyotype, overlaid = gene_density, label = LTR_density, label_type = "heatmap", colorset1 = c("#f7f7f7", "#e34a33"), colorset2 = c("#f7f7f7", "#2c7fb8"))
> convertSVG("chromosome.svg", device = "png")
chromosome.png
label_type = "line"
这个类型是用来在染色体旁边画折线图的，换一组数据，像如下有 value 的
> data(liriodendron_karyotype, package="RIdeogram")
> head(liriodendron_karyotype)
Chr Start End
1 1 0 118073833
2 2 0 98364873
3 3 0 207093695
4 4 0 50051714
5 5 0 45443526
6 6 0 35772468
> data(Fst_between_CE_and_CW, package="RIdeogram")
> head(Fst_between_CE_and_CW)
Chr Start End Value
1 1 1 2000000 0.0646357
2 1 1000001 3000000 0.0626714
3 1 2000001 4000000 0.0582397
4 1 3000001 5000000 0.0679570
5 1 4000001 6000000 0.0965196
6 1 5000001 7000000 0.0934111
> data(Pi_for_CE, package="RIdeogram")
> head(Pi_for_CE)
Chr Start End Value Color
1 1 1 2000000 0.00273566 fc8d62
2 1 1000001 3000000 0.00239580 fc8d62
3 1 2000001 4000000 0.00319407 fc8d62
4 1 3000001 5000000 0.00286900 fc8d62
5 1 4000001 6000000 0.00186596 fc8d62
6 1 5000001 7000000 0.00186182 fc8d62
> data(Pi_for_CE_and_CW, package="RIdeogram")
> head(Pi_for_CE_and_CW)
Chr Start End Value_1 Color_1 Value_2 Color_2
1 1 1 2000000 0.00273566 fc8d62 0.00385702 8da0cb
2 1 1000001 3000000 0.00239580 fc8d62 0.00331109 8da0cb
3 1 2000001 4000000 0.00319407 fc8d62 0.00374530 8da0cb
4 1 3000001 5000000 0.00286900 fc8d62 0.00339141 8da0cb
5 1 4000001 6000000 0.00186596 fc8d62 0.00305246 8da0cb
6 1 5000001 7000000 0.00186182 fc8d62 0.00323655 8da0cb
1个value
> ideogram(karyotype = liriodendron_karyotype, overlaid = Fst_between_CE_and_CW, label = Pi_for_CE, label_type = "line", colorset1 = c("#e5f5f9", "#99d8c9", "#2ca25f"))
> convertSVG("chromosome.svg", device = "png")
chromosome.png
2个value
> ideogram(karyotype = liriodendron_karyotype, overlaid = Fst_between_CE_and_CW, label = Pi_for_CE_and_CW, label_type = "line", colorset1 = c("#e5f5f9", "#99d8c9", "#2ca25f"))
> convertSVG("chromosome.svg", device = "png")
chromosome.png
label_type = "polygon" 多边形
1个value
> ideogram(karyotype = liriodendron_karyotype, overlaid = Fst_between_CE_and_CW, label = Pi_for_CE, label_type = "polygon", colorset1 = c("#e5f5f9", "#99d8c9", "#2ca25f"))
> convertSVG("chromosome.svg", device = "png")
chromosome.png
2个value
> ideogram(karyotype = liriodendron_karyotype, overlaid = Fst_between_CE_and_CW, label = Pi_for_CE_and_CW, label_type = "polygon", colorset1 = c("#e5f5f9", "#99d8c9", "#2ca25f"))
> convertSVG("chromosome.svg", device = "png")
chromosome.png
（6）可视化两个或三个基因组之间的基因组同线性结果
先略过 https://cran.r-project.org/web/packages/RIdeogram/vignettes/RIdeogram.html 最下面
4、输出
convertSVG("chromosome.svg", device = "png", dpi = 600)
名儿 格式：“tiff”、“pdf”、“jpg” 分辨率
