plotOnGene(GeneRegionScan)
plotOnGene()所属R语言包：GeneRegionScan
Plot probe level data on a gene
图探针水平上的基因数据
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Function that will investigate the probe level intensity of probes as a function of their location in a gene.
功能，将探针探针水平强度作为它们在基因中的位置的功能调查。
用法----------Usage----------
plotOnGene(object, gene, probeData=NULL, label=NULL, genename=NULL, summaryType="median",
interval=NULL, ylim=NULL, testType=NULL, forcePValue=FALSE, verbose=TRUE, cutoff=0.2, directions="all", ylab="expression")
参数----------Arguments----------
参数：object
A ProbeLevelSet object or a regular ExpressionSet object (in which case a probeData argument is required). See getLocalProbeIntensities and related functions on how to create a ProbeLevelSet.
一个ProbeLevelSet对象或定期ExpressionSet对象（在这种情况下probeData参数是必需的）。如何创建一个ProbeLevelSet getLocalProbeIntensities和相关职能。
参数：gene
A number of gene sequences as DNAstring, vectors of DNAStrings, character-vectors or readFASTA outputs.
一个号码作为DNAstring基因序列，向量DNAStrings，字符矢量或readFASTA输出的。
参数：probeData
Optional if a ProbeLevelSet is submitted as object argument. Otherwise, it must be a data frame with rownames corresponding to the featureNames of the ExpressionSet and a column named "sequence" with the probe sequences as character strings
可选如果提交对象参数ProbeLevelSet。否则，它必须是一个相应的ExpressionSet的featureNames和探针序列作为字符串名为“序列”列rownames数据框
参数：label
An optional character string specifying a column name in the pData of the object. If this argument is given, the gene plot will be colour coded based on the different groups (factors) in the pData entry. If a summaryType other than 'dots' is selected the summarisation is done stratified by the different groups in the pData. It can be a numeric or integer entry, but it will be coerced to factors.
一个可选的字符串对象的pData所指定的列名。如果这种说法，基因图将根据不同的群体，在PDATA项（因素）的颜色编码。如果选择“点”以外summaryType的summarisation完成在pData所不同群体分层。它可以是一个数字或整数的条目，但它会被强制因素。
参数：genename
Optional character string specifying a gene name to include in the plot. If not included and a FASTA sequence is given, it will default to the name in the FASTA sequence. Otherwise, it will default to 'Unknown genename'.
可选的字符串指定一个基因的名字，包括图。如果不包含，并给出一个FASTA序列，它会默认为FASTA格式的序列的名称。否则，它会默认为未知genename“。
参数：summaryType
Character string specifying one of the following summary methods: 'median', 'mean', 'quartiles' or 'dots' (i.e. no summary). Specifies how all the sample values or all the samples values in a group if 'label' is given, should be summarised. Defaults to 'median'.
字符串，指定以下的简易方法之一：“中位数”，“意味着”，“四分”或“点”（即无摘要）。指定所有样本值或一组中的所有样本值，如果给出标签，应该总结。默认为“中位数”。
参数：interval
Optional vector of two integers of bp positions. If given, the plot will only include the sequence from gene in the given interval. The x-axis annotation is preserved from original, so this is useful for zooming on specific regions.
可选向量两个BP位置的整数。如果给定，该图将只包括在给定的时间间隔的基因序列。 x轴的注解是从原来的保存，所以这是非常有用的，用于放大特定区域。
参数：ylim
Optional two integers. If given, this value will be the minimal and maximal value on the y-axis. This is useful if a few outlier probes have very high intensity values, as the default is to set the ylim from the maximal intensity value.
可选两个整数。如果给定的，这个值将y轴的最小和最大的价值。这是有用的，如果几个离群探针具有很高的强度值，作为默认设置的最大强度值ylim。
参数：testType
Optional character string, defining a statistic procedure to identify especially interesting probes. Can be either 'linear model', 'students' or 'wilcoxons'. If given, a label must also be specified. In this case the plotStatistics function will be called and probes that are significantly changed between the groups in label at the P-value set in cutoff (see cutoff argument) will be circled.
可选的字符串，定义一个统计程序，以确定特别有趣的探针。可无论是“线性模型”，“学生”或“wilcoxons”。如果给出一个标签还必须指定。在这种情况下的plotStatistics函数将被调用，将盘旋在标签的群体之间有显着改变，在截止一套P值（见截止参数）的探针。
参数：forcePValue
Logical. Is used if the testType argument is used. If TRUE all significantly changed probes have P-value given on the plot. If FALSE, only plots with less than 10 significant probes write P-values. Plots can become very cluttered with data if set to TRUE
逻辑。用于用于，如果testType参数。如果真探针均显着改变，有图给予的P值。如果为FALSE，只用不到10显著探针图写出P值。图可以成为非常杂乱的数据，如果设置为TRUE
参数：verbose
TRUE or FALSE
TRUE或FALSE
参数：cutoff
Integer specifying at what p-value probes should be circled when using the 'testType' variable. Defaults to 0.2. For cutoffs higher than 0.05, all probes with P >0.05 will be circled in grey instead of black.
整数，指定p值探针应盘旋时使用的“testType变量。默认为0.2。比0.05的临界值，P均> 0.05探针将在灰黑色的，而不是盘旋。
参数：directions
A character vector of the matching-directions that should be scanned (which combinations of complementary and reverse). Defaults to "all" which is shorthand for all possible directions, but can take anything from: c("matchForwardSense", "matchForwardAntisense", "matchReverseSense", "matchReverseAntisense")
应扫描（互补和反向组合）的匹配方向的一个特征向量。默认“所有”，这是对所有可能的方向速记，但可以采取任何来自：C（“matchForwardSense”，“matchForwardAntisense”，“matchReverseSense”，“matchReverseAntisense”）
参数：ylab
Label of Y-axis as in default plots
Y轴标签在默认图
Details
详情----------Details----------
At the very least, this function takes a ProbeLevelSet or an ExpressionSet + probeData and the sequence of a gene. It then compares the probe sequences given in the ProbeLevelSet or the probeData variable with the sequence of the gene given. Any probes with sequences found in the gene will be plotted, with their intensity level on the y-axis and their location in the gene on the x-axis. If no further arguments are given this gives a view of relative expression levels along the length of the gene, and can be used to investigate which exons are actively transcribed in the sample and which are not. An important argument that can be used for further investigation is the 'label' argument which specifies a column in the pData of the ExpressionSet. In this case the plots will be stratified by the factors specified in this column (so giving labels with numerical or Date class data will not work). This can be very useful when investigating how different sample conditions affect various regions of a gene. A transcript isoform that is relatively upregulated in a diseased state will for example not be discovered if a probeset or metaprobeset covering the entire gene is used to summarize the data, since the average expression intensity for the gene will remain constant. Using the plotOnGene function, however, and specifying a case / control label will reveal tendencies for probes at certain exon locations to have relation to this label. The testType argument further supports this functionality by providing statistical testing and highlighting of probes that correlate significantly to the given label. In the case / control example, a student's t-test would highlight all probes that matched with the exons of the gene that was only found in the disease-specific transcript isoform. When interpreting the data it is suggested that specific attention is paid to the pattern of probes in the same exon. A single probe with a P-value < 0.05 might be a false positive caused by chance or by cross hybridization of the probe sequence to something else. A range of probes in the same exon that all show P-values below or close to 0.05, however, is much more likely to be an actual case of a transcript isoform having this particular exon or exons being regulated between the groups in the label. Exon structure can be easily plotted on the graph using the exonStructure function.
至少，这个功能需要ProbeLevelSet或ExpressionSet + probeData和基因序列。然后，它的探针在ProbeLevelSet或与特定基因序列的probeData变量序列比较。将绘制的基因中发现任何探针序列，y轴和他们的基因在x轴的位置上的强度水平。如果没有进一步给出参数，这给出了一个沿长度的基因相对表达水平的看法，可以用来探讨其中外显子都在积极转录样品中，哪些不是。可用于作进一步调查的一个重要参数是pData所的ExpressionSet在指定的列标签的说法。在这种情况下，图将在本专栏中指明的因素（因此数值或日期类的数据标签将不起作用）分层。调查时，不同的样本条件下如何影响一个基因的不同区域，这可以是非常有用的。成绩单亚型，相对上调在患病状态，例如不会被发现，如果一个probeset，或metaprobeset涵盖整个基因用于汇总数据，因为基因的平均表达强度将保持不变。使用的plotOnGene的功能，然而，指定情况下/控制标签，就会发现在某些外显子位置的倾向，有这个标签为探针。 testType说法进一步支持此功能，提供统计显著给定的标签关联的探针测试和突出。在病例/对照的例子，将突出学生的t检验所有探针匹配，只有在特定疾病的成绩单亚型基因的外显子。解释数据时建议特别注意的是，在相同的外显子的探针模式。单探针与一个P-值<0.05，可能是一个机会，或通过别的探针序列的交叉杂交造成的假阳性。在相同的外显子都显示P值低于或接近0.05，但是，更可能是实际情况的成绩单，这个特定的外显子或外显子在标签组之间调节亚型的探测范围。外显子结构，可以很容易地绘制图上使用exonStructure功能。
A special case is the search for SNPs which have effect on expression levels or variable splicing. The testType argument 'linear model' is designed for this. The linear model calls the internal function doProbeLinear which assign each of the levels in the 'label' column of the pdata a value between 1 and the number of levels, in the order in which they are sorted. For genotypes given as "AA", "AB", "BB" character strings this will give "AA" = 1, "AB" = 2 and "BB" = 3. The doProbeLinear then calculates a linear model between the intensity values and these numbers, and returns the P-value. In this case, low P-values can be interpreted as a case where the heterozygote samples have intermediary expression levels between the two homozygotes. This is the case that can be expected to be seen if the nucleotide type of SNP does in fact have any effect on the mRNA concentration levels in the sample.
一个特殊情况是单核苷酸多态性的搜索，这对表达水平或可变剪接的效果。是专为线性模型testType参数。线性模型调用的内部的功能doProbeLinear分配中的标签PDATA值介于1和级别的数量，在它们的排列顺序，列每个级别。对于为“AA级”，“AB”，“BB”的字符串，这将给予“AA”的“AB”= 2“BB”的= 3 = 1，给定的基因型。然后doProbeLinear计算强度值和这些数字之间的线性模型，并返回P值。在这种情况下，低P值可以解释为杂合子样品两者之间的纯合子的中介表达水平的情况下。这是可以预期的情况看出，如果单核苷酸多态性核苷酸类型，并在事实上有任何对样品中的mRNA浓度的影响。
值----------Value----------
No value, but plots the local expression levels relations of each probe found in the submitted gene sequence as a function of its location along this sequence. Various statistics and summarizations on pdata can be employed, as specified in details.
没有价值，但当地的表达水平在提交的基因序列，发现沿着这个序列中的位置的功能，为每个探针的关系图。可以采用PDATA各种统计数据和研究概述，详细规定。
作者（S）----------Author(s)----------
Lasse Folkersen
参见----------See Also----------
geneRegionScan, plotCoexpression
geneRegionScan，plotCoexpression
举例----------Examples----------
data(exampleProbeLevelSet)
plotOnGene(exampleProbeLevelSet, mrna, summaryType="dots", interval=c(500,1000))
plotOnGene(exampleProbeLevelSet, mrna, label="genotype3", testType="linear model")
exonStructure(mrna, genomic)
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。
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发表于 2012-2-25 18:59:25
