geneData(gage)
geneData()所属R语言包:gage
View the expression data for selected genes
查看选定的基因表达数据
译者:生物统计家园网 机器人LoveR
描述----------Description----------
This function outputs and visualizes the expression data for seleted genes. Potential output files include: a tab-delimited text file, a heatmap in PDF format, and a scatter plot in PDF format.
此功能输出和可视化代表论着基因的表达数据。潜在产出的文件包括:制表符分隔的文本文件,PDF格式的热图,散点图和PDF格式。
用法----------Usage----------
geneData(genes, exprs, ref = NULL, samp = NULL, outname = "array",
txt = TRUE, heatmap = FALSE, scatterplot = FALSE, samp.mean = FALSE,
pdf.size = c(7, 7), cols = NULL, scale = "row", limit = NULL,
label.groups = TRUE, ...)
参数----------Arguments----------
参数:genes
character, either a vector of interesting genes IDs or a 2-column matrix, where the first column specifies gene IDs used in expData while the second column gives another type of IDs to use for the output data files.
性格,无论是有趣的基因向量的ID或2列的矩阵,其中第一列指定所用的基因IDexpData而第二列给出另一种类型的ID,用于输出数据文件。
参数:exprs
an expression matrix or matrix-like data structure, with genes as rows and samples as columns.
表达矩阵或矩阵类似的数据结构,行和列的样本的基因。
参数:ref
a numeric vector of column numbers for the reference condition or phenotype (i.e. the control group) in the exprs data matrix. Default ref = NULL, all columns are considered as target experiments.
一个参考条件,或在exprs数据矩阵型(即对照组)的列数的数字向量。默认REF = NULL,所有列被视为靶实验。
参数:samp
a numeric vector of column numbers for the target condition or phenotype (i.e. the experiment group) in the exprs data matrix. Default samp = NULL, all columns other than ref are considered as target experiments.
一列数为目标的条件或在exprs数据矩阵型(即实验组)的数字向量。默认SAMP = NULL,比文献中的所有列被视为靶实验。
参数:outname
a character string, to be used as the prefix of the output data files. Default to be "array".
一个字符串,可用于输出数据文件的前缀。默认为“阵列”。
参数:txt
boolean, whether to output the selected gene data as a tab-delimited text file. Default to be TRUE.
布尔值,是否输出作为一个制表符分隔的文本文件中选定的基因数据。默认为TRUE。
参数:heatmap
boolean, whether to plot heatmap for the selected gene data as a PDF file. Default to be FALSE.
布尔值,是否为PDF文件选定的基因数据绘制的热图。默认为FALSE。
参数:scatterplot
boolean, whether to make scatter plot for the selected gene data as a PDF file. Default to be FALSE.
布尔,是否要为PDF文件选定的基因数据的散点图。默认为FALSE。
参数:samp.mean
boolean, whether to take the mean of gene data over the ref and samp group when making the scatter plot. Default to be FALSE, i.e. make scatter plots for the first two ref-samp pairs and label them differently on the same graph panel.
布尔值,是否要在ref和桑普组的基因数据的均值散点图。默认是假的,即前两个REF-SAMP对散点图和他们不同的标签上相同的图形面板。
参数:pdf.size
a numeric vector to specify the the width and height of PDF graphics region in inches. Default to be c(7, 7).
一个数值向量PDF图形区域的高度和宽度,以英寸为单位指定。默认为C(7,7)。
参数:cols
a character vector to specify colors used for the heatmap image blocks. Default to be NULL, i.e. to generate a green-red spectrum based on the gene data automatically.
一个字符向量指定用于热图的图像块的颜色。默认为NULL,即根据基因数据自动生成一个绿色红色光谱。
参数:scale
character indicating if the values should be centered and scaled in either the row direction or the column direction, or none for the heatmap. The default is "row", other options include "column" and "none".
如果值应在该行的方向或列方向,或没有热图居中,缩放字符显示。默认的是“行”,其他选项包括“列”和“无”。
参数:limit
numeric value to specify the maximal absolute value of gene data to visualize using the heatmap. Gene data beyong will be reset to equal this value. Default to NULL, i.e. plot all gene data values. This argument allows optimal differentiation between most gene data values when extremely positive/negative values exsit and squeeze the normal-value region. Recommend limit = 3 when the gene data is scaled by row.
数值指定绝对值最大的基因数据,可视化使用的热图。基因数据beyong将被重置,等于这个值。默认为NULL,即小区的所有基因数据值。这种说法使大多数基因数据值时,正/负值exsit和挤压的正常价值的区域之间的最佳分化。建议限制= 3的基因数据时行缩放。
参数:label.groups
boolean, whether to label the two sample groups, i.e. ref and samp, differently using side color bars along the heatmap area. Default to be TRUE.
布尔,是否标注两个样本组,即ref和桑普,沿热图区使用不同的侧面彩条。默认为TRUE。
参数:...
other arguments to be passed into the inside heatmap2 function.
其他参数被传递到内heatmap2函数。
Details
详情----------Details----------
This function integrated three most common presentation methods for gene expression data: tab-delimited text file, heatmap and scatter plot. Heatmap is ideal for visualizing relative changes with gene-wise standardized (or row-scaled) data. The heatmap is generated by calling a improved version of the heatmap.2 function from gplots package. Scatter plot is ideal for visualizing the modest or small but consistent changes over a gene set between two states under comparison.
此功能集成了三种最常见的基因表达数据的演示方法:制表符分隔的文本文件,热图和散点图。热图是理想的可视化与基因明智的标准化(或行规模)数据的相对变化。热图所产生的调用从gplots包heatmap.2功能的改进版本。散点图是理想的可视化了两下比较各国之间设置一个基因温和或小,但一致的变化。
Although geneData is designed to be a standard-alone function, it is frequently used in tandem with essGene function to present the changes of the essential genes in signficant gene sets.
虽然geneData设计是一个标准的功能,它经常被使用essGene函数提出在signficant基因组的基本基因的变化,在串联。
值----------Value----------
The function returns invisible 1 when successfully executed.
成功执行时,该函数返回无形1。
作者(S)----------Author(s)----------
Weijun Luo <luo_weijun@yahoo.com>
参考文献----------References----------
Generally Applicable Gene Set Enrichment for Pathways Analysis. BMC Bioinformatics 2009, 10:161
参见----------See Also----------
essGene extract the essential member genes in a gene set; gage the main function for GAGE analysis;
essGene提取的基因组中的重要成员的基因;gage压力计分析的主要功能;
举例----------Examples----------
data(gse16873)
cn=colnames(gse16873)
hn=grep('HN',cn, ignore.case =TRUE)
dcis=grep('DCIS',cn, ignore.case =TRUE)
#kegg test for 1-directional changes[KEGG测试为1方向变化]
data(kegg.gs)
gse16873.kegg.p <- gage(gse16873, gsets = kegg.gs,
ref = hn, samp = dcis)
rownames(gse16873.kegg.p$greater)[1:3]
gs=unique(unlist(kegg.gs[rownames(gse16873.kegg.p$greater)[1:3]]))
essData=essGene(gs, gse16873, ref =hn, samp =dcis)
head(essData)
ref1=1:6
samp1=7:12
#generated text file for data table, pdf files for heatmap and scatterplot[为数据表生成文本文件,PDF文件热图和散点图]
for (gs in rownames(gse16873.kegg.p$greater)[1:3]) {
outname = gsub(" |:|/", "_", substr(gs, 10, 100))
geneData(genes = kegg.gs[[gs]], exprs = essData, ref = ref1,
samp = samp1, outname = outname, txt = TRUE, heatmap = TRUE,
Colv = FALSE, Rowv = FALSE, dendrogram = "none", limit = 3, scatterplot = TRUE)
}
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。
|