plotGrandLinear(ggbio)
plotGrandLinear()所属R语言包：ggbio
Manhattan for GWAS
曼哈顿的GWAS
译者：生物统计家园网 机器人LoveR
描述----------Description----------
A Manhattan plot is special scatter plot used to visualize data with a large number of data points, with a distribute of some higher-magnitude values. For example, in the GWAS(genome-wide association studies). Here we mainly focus on GWAS Manhattan plots. X-axis is genomic coordinates and Y-axis is negative logarithm of the associated P-value for each single nucleotide polymorphism. So higher the value, more stronger the association they are.
曼哈顿的图是特殊的散点图，用大量的数据点的数据可视化，与分发一些更高的幅度值。例如，在的GWAS（全基因组关联研究）。在这里，我们主要集中在GWAS的曼哈顿图。是基因组的X轴和Y轴的坐标是每个单核苷酸多态性的相关P值的负对数。如此高的价值，更强协会。
用法----------Usage----------
plotGrandLinear(obj, y, title, facet,
size, shape, color, alpha,
...,
geom = c("point", "line"),
color.type = c("twocolor", "identity", "seqnames"),
two.color = c("#0080FF", "#4CC4FF"),
cutoff = NULL,
cutoff.color = "red",
cutoff.size = 1,
legend = FALSE,
xlab = "Chromosome",
ylab = substitute(y),
theme_bw = TRUE)
参数----------Arguments----------
参数：obj
GRanges object which contains extra p value, before users pass this object, they need to make sure the pvalue has been changed to -log10(p).
GRanges对象，它包含额外的P值，用户通过这个对象之前，他们需要确保已改为pvalue LOG10（P）。
参数：y
Unevaluated name which should be one the of the column names indicating the p-value Or other score used as y value in the plot. This is required field.
未计算的名称应该是一个列名显示P-值或其他得分为y值使用中的图。这是必需的领域。
参数：title
Title for the plot, default plot without title.
标题的图，没有标题的默认图。
参数：facet
A facet formula, when provided, should be in two forms. First one, facet = group ~ seqnames, where group should be the name you want to facet by rows, if not, use . instead. this is faceted by seqnames, the different chromosomes will be in different panel. The second form, facet = group ~ . will give you a compact grand linear view, seqnames will not be in different panels, this is a better way to plot a overview, e.g. a Manhattan plot.
一个面的配方，提供时，应该有两种形式。第一位的，facet = group ~ seqnames，其中组应该是你想要的名字排面，如果没有，使用.代替。这是面由seqnames，不同的染色体将在不同的面板。第二种形式，facet = group ~ .会给你一个紧凑的盛大线性认为，seqnames不会在不同的面板，这是一个更好的方法绘制一个概述，如曼哈顿的图。
参数：size
Size for point or lines. Could equal a column name or a fixed number. When it's fixed, please use I() to wrap the value.
为点或线的大小。就相当于列名或一个固定的数字。当它固定的，请使用I()包装的价值。
参数：shape
Shape for point or lines. Could equal a column name or a fixed number. When it's fixed, please use I() to wrap the value.
点或线的形状。就相当于列名或一个固定的数字。当它固定的，请使用I()包装的价值。
参数：color
Color for point for lines. Could equal a column name or a fixed character. When it's fixed, please use I() to wrap the value.
颜色为线的点。就相当于列名或一个固定的字符。当它固定的，请使用I()包装的价值。
参数：alpha
Alpha blending. Could equal a column name or a fixed number. When it's fixed, please use I() to wrap the value.
Alpha混合。就相当于列名或一个固定的数字。当它固定的，请使用I()包装的价值。
参数：...
Extra arguments passed. Will be automatically dispatched to the right place, such as scales, space. When you try to use a faceted seqnames, you need to specify scales = "free" and space = "free", if you want a free scaled x-scale.
额外的参数传递。将自动分派到正确的地方，如尺度，空间。当您尝试使用面seqnames，你需要指定scales = "free"和space = "free"，如果你想要一个自由的缩放X-级。
参数：geom
"point"(default) or "line". When it's line, it will make sure the line is not connect cross different chromosomes.
“点”（默认）或“行”。当它的路线，它将确保线连接跨不同的染色体。
参数：color.type
"identity" use single color for all points, when it's enabled, you can specify color in the arguments to equal a character or an unevaluated name, when use specific color, try use I, for instance, color = I("red"); "seqnames" use default discrete color scheme for all chromosomes; "twocolor" use two colors to represent all the chromosomes, could specify color in the two.color argument.
“身份”使用单一颜色，所有的点时，它的启用，您可以指定颜色在参数等于一个字符或一个未计算的名称，使用特定的颜色时，尽量使用I，例如，颜色我（“红色”）;“seqnames”使用默认的所有染色体的离散配色方案“twocolor”使用两种颜色来代表所有的染色体，可以指定颜色在two.color参数。
参数：two.color
A character vector of two. Default is chosen from dichromat palette "BluetoOrange.8", make sure it's color-blind safe.
一个两个特征向量。默认是从dichromat调色板“BluetoOrange.8”的选择，确保它是色盲的安全。
参数：cutoff
A numeric vector which used as cutoff for Manhattan plot.
一个数值向量作为截止曼哈顿图使用。
参数：cutoff.color
A character specifying the color used for cutoff. Default is "red".
一个字符指定的截止使用的颜色。默认为“红色”。
参数：cutoff.size
A numeric value which used as cutoff line size.
一个数值，用来作为截止线的大小。
参数：legend
A logical value indicate whether to show legend or not. Default is FALSE which disabled the legend.
一个逻辑值，指明是否显示图例与否。默认值为FALSE，禁用的传说。
参数：xlab
Label for xscale.
为XSCALE的标签。
参数：ylab
Label for yscale.
为yscale的标签。
参数：theme_bw
A logical value indicate whether to show gray background or not. Default is TRUE, use theme_bw() in ggplot2.
一个逻辑值，表明是否显示灰色背景或没有。默认值为true，使用在ggplot2 theme_bw（）。
Details
详情----------Details----------
If scales and space are free, then the mapping between position and values in the data will be the same across all panels
如果尺度和空间是免费的，那么之间的位置，并在数据值的映射将是相同的所有小组
值----------Value----------
Return a ggplot object.
返回ggplot对象。
作者（S）----------Author(s)----------
Tengfei Yin
举例----------Examples----------
## Not run: [＃无法运行：]
library(GenomicRanges)
library(ggbio)
data(hg19IdeogramCyto)
data(hg19Ideogram)
chrs <- as.character(levels(seqnames(hg19IdeogramCyto)))
seqlths <- seqlengths(hg19Ideogram)[chrs]
set.seed(1)
nchr <- length(chrs)
nsnps <- 1000
gr.snp <- GRanges(rep(chrs,each=nsnps),
IRanges(start = do.call(c, lapply(chrs, function(chr){
N <- seqlths[chr]
runif(nsnps,1,N)
})), width = 1),
SNP=sapply(1 nchr*nsnps), function(x) paste("rs",x,sep='')),
pvalue = -log10(runif(nchr*nsnps)),
group = sample(c("Normal", "Tumor"), size = nchr*nsnps,
replace = TRUE)
)
## processing the name[＃处理名称]
nms <- seqnames(seqinfo(gr.snp))
nms.new <- gsub("chr", "", nms)
names(nms.new) <- nms
gr.snp <- renameSeqlevels(gr.snp, nms.new)
## compact view[＃紧凑视图]
## no facet by samples, but make sure you want it that way[＃无面样品，但要确保你想用那种方式]
## default is two color[＃默认是两种颜色]
plotGrandLinear(gr.snp, y = pvalue, geom = "point")
## facet by samples, comparison across groups[＃面样本，跨组比较]
plotGrandLinear(gr.snp, y = pvalue, geom = "point",
facet = group ~ ., color.type = "twocolor")
## change two color[＃改变两种颜色。]
plotGrandLinear(gr.snp, y = pvalue, geom = "point",
facet = group ~ ., color.type = "twocolor",
two.color = c("red", "blue"))
## geom line[＃GEOM行]
plotGrandLinear(gr.snp, y = pvalue,
geom = "line", facet = group ~ .)
## add size and change color[＃增加大小和变化的颜色。]
plotGrandLinear(gr.snp, y = pvalue, size = pvalue,geom = "point",
facet = group ~ ., color.type = "seqnames")
plotGrandLinear(gr.snp, y = pvalue, size = I(0.05),
geom = "point", facet = group ~ .)
plotGrandLinear(gr.snp, y = pvalue, color = group, geom = "point",
facet = group ~ .,
color.type = "identity")
plotGrandLinear(gr.snp, y = pvalue, color = I("blue"), geom = "point", facet = group ~ .,
color.type = "identity")
## facet by seqnames, slower[＃面seqnames，慢]
plotGrandLinear(gr.snp, y = pvalue,geom = "point",
facet = group ~ seqnames, scales = "free", space = "free")
## End(Not run)[＃结束（不运行）]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-2-25 19:44:30
