mergeScans(limma)
mergeScans()所属R语言包：limma
Merge two scans of two-color arrays
合并两两色阵列扫描
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Merge two sets of intensities of two-color arrays that are scanned twice at two different scanner settings, one at a lower gain setting with no saturated spot intensities and the other at a higher gain setting with a higher signal-to-noise ratio and some saturated spot intensities.
合并两套两色的阵列，在两个不同的扫描仪设置扫描两次，在没有饱和点的强度和更高的增益设置一个更高的信号噪声比其他较低的增益设置和一些强度饱和点强度。
用法----------Usage----------
mergeScansRG(RGlow, RGhigh, AboveNoiseLowG=NULL, AboveNoiseLowR=NULL, outlierp=0.01)
参数----------Arguments----------
参数：RGlow
object of class RGList containing red and green intensities constituting two-color microarray data scanned at a lower gain setting.
类对象RGList含有红色和绿色的强度，构成两色的芯片在一个较低的增益设置扫描的数据。
参数：RGhigh
object of class RGList containing red and green intensities constituting two-color microarray data scanned at a higher gain setting.
类对象RGList含有红色和绿色的强度，构成两色的芯片在一个更高的增益设置扫描的数据。
参数：AboveNoiseLowG
matrix of 1 or 0 for low scan intensities of green color, 1 for spots above noise level or 0 otherwise. One column per array.
矩阵的1或0，绿色的扫描强度低1点以上的噪音水平，否则为0。每个阵列的一列。
参数：AboveNoiseLowR
matrix of 1 or 0 for low scan intensities of red color, 1 for spots above noise level or 0 otherwise. One column per array.
矩阵的1或0，红色的扫描强度低1点以上的噪音水平，否则为0。每个阵列的一列。
参数：outlierp
p-value for outliers. 0 for no outlier detection or any value between 0 and 1. Default p-value is 0.01.
P-值离群。 0无异常检测或者0和1之间的任何值。 P-值是0.01。
Details
详情----------Details----------
This function merges two separate scans of each fluorescent label on a two-color array scanned at two different scanner settings by using a nonlinear regression model consisting of two linear regression lines and a quadratic function connecting the two, which looks like a hockey stick. The changing point, i.e. the saturation point, in high scan is also estimated as part of model. Signals produced for certain spots can sometimes be very low (below noise) or too high (saturated) to be accurately read by the scanner. The proportions of spots that are below noise or above saturation are affected by the settings of the laser scanner used to read the arrays, with low scans minimizing saturation effects and high scans maximizing signal-to-noise ratios. Saturated spots can cause bias in intensity ratios that cannot be corrected for using conventional normalization methods.
此功能合并在两个不同的扫描仪设置扫描通过使用非线性回归模型组成的两个线性回归直线和二次函数连接两个，它看起来像一个曲棍球棒两种颜色数组的每个荧光标记的两个单独的扫描。不断变化的点，即饱和点，在高扫描也估计作为模型的一部分。有时可能会产生某些点的信号非常低（低于噪声）或过高（饱和）必须准确地通过扫描仪读取。受用于读取与低扫描信号信噪比最大化减少饱和效应和高扫描阵列，激光扫描仪的设置，噪音低于或高于饱和点的比例。饱和点可能会导致在强度比使用传统的规范化方法，不能用于纠正偏差。
Each fluorescent label on a two-color array can be scanned twice: for example, a high scan targeted at reaching saturation level for the brightest 1 percent of the spots on the array, and a low scan targeted at the lowest level of intensity which still allowed accurate grid placement on the arrays. By merging data from two separate laser scans of each fluorescent label on an array, we can avoid the potential bias in signal intensities due to below noise or above saturation and, thus provide better estimates of true differential expression as well as increase usable spots.
每两色阵列上的荧光标记，可以扫描两次：例如，针对高扫描达到饱和程度，最亮的1％的磁盘阵列上的斑点，低强度的最低水平扫描针对性仍然允许阵列上准确的电网布局。我们可以通过合并两个单独的每一个阵列上的荧光标记激光扫描数据，避免在以下噪音或以上饱和的信号强度由于潜在的偏见，从而提供更好的估计真正的差异表达以及增加可用点。
The merging process is designed to retain signal intensities from the high scan except when scanner saturation causes the high scan signal to be under-measured. The saturated spots are predicted from the corresponding low scans by the fitted regression model. It also checks any inconsistency between low and high scans.
合并过程中被保留从高扫描时，扫描仪饱和导致高扫描信号，是衡量信号强度。从相应的低扫描拟合回归模型的饱和点预测。它还会检查任何低和高扫描之间的不一致。
值----------Value----------
An object of class RGList-class with the following components:
一个对象类RGList-class以下组件：
参数：G
numeric matrix containing the merged green (cy3) foreground intensities. Rows correspond to spots and columns to arrays.
数字矩阵包含合并的绿色（CY3）前景强度。行对应点和列数组。
参数：R
numeric matrix containing the merged red (cy5) foreground intensities. Rows correspond to spots and columns to arrays.
数字矩阵包含合并的红色（CY5）前景强度。行对应点和列数组。
参数：Gb
numeric matrix containing the green (cy3) background intensities from high scan.
数字矩阵包含绿色（CY3）背景强度高扫描。
参数：Rb
numeric matrix containing the red (cy5) background intensities from high scan.
数字矩阵包含红色（CY5）背景强度高扫描。
参数：other
list numeric matrices Gsaturated, Rsatured, Goutlier and Routlier. The first two contain saturation flags (1=saturated, 0=otherwise) for the green (cy3) and red (Cy5) channels of the high scan. The second two contain outlier flags (1=outlier, 0=otherwise) for the green (cy3) and red (Cy5) channels.
列出数字矩阵Gsaturated，Rsatured，Goutlier和Routlier。前两个含有饱和标志（1 =饱和，0 =其他）绿色（CY3）和红色（Cy5标记）高扫描通道。第二个包含离群标志（1 =离群，0 =否则）绿色（CY3）和红色（Cy5标记）通道。
作者（S）----------Author(s)----------
Dongseok Choi <a href="mailto:choid@ohsu.edu">choid@ohsu.edu</a>.
参考文献----------References----------
举例----------Examples----------
## Not run: [＃无法运行：]
#RG1: An RGList from low scan[RG1的：从低扫描RGList]
#RG2: An RGList from high scan[RG2的：从高扫描RGList]
RGmerged <- mergeScansRG(RG1,RG2,AboveNoiseLowG=ANc3,AboveNoiseLowR=ANc5)
#merge two scans when all spots are above noise in low scan and no outlier detection.[合并两次扫描时噪音低扫描所有点以上，并没有异常检测。]
RGmerged <- mergeScansRG(RG1,RG2,outlierp=0)
## 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 23:19:00
