Bscore(cellHTS2)
Bscore()所属R语言包：cellHTS2
B score normalization
乙得分标准化
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Correction of plate and spatial effects of data stored in slot assayData of a cellHTS object using the B score method (without variance adjustment of the residuals). Using this method, a two-way median polish is fitted, on a per-plate basis, to account for row and column effects.
校正板和空间数据的影响，在存储插槽assayDatacellHTS对象，使用B的得分方法（无残差的方差调整）。使用这种方法，装有双向位数波兰，每板的基础上，考虑到行和列的效果。
用法----------Usage----------
Bscore(object, save.model = FALSE)
参数----------Arguments----------
参数：object
a cellHTS object that has already been configured. See details.
cellHTS已配置的对象。查看详情。
参数：save.model
a logical value specifying whether the per-plate models should be stored in slots rowcol.effects and overal.effects. See details.
一个逻辑值，指定是否应存储插槽rowcol.effects和overal.effects每板模型。查看详情。
Details
详情----------Details----------
This function is usually not called directly by the user, but from within the normalizePlates function. The normalization is performed in a per-plate fashion using the B score method, for each replicate and channel. In the B score method, the residual r_{ijp} of the measurement for row i and column j on the p-th plate is obtained by fitting a two-way median polish, in order to account for both row and column effects within the plate:
此功能通常不直接调用用户，但在normalizePlates功能。标准化是在每盘时尚，使用B的得分方法，为每个复制和渠道。在B的得分方法，剩余的r_{ijp}i和列j的P-TH板的连续测量，得到拟合双向位数波兰，以行和列的效果帐户内板块：
y_{ijp} is the measurement value in row i and column j of plate p (taken from slot assayData - only sample wells are considered), and yest_{ijp} is the corresponding fitted value. This is defined as the sum between the estimated average of the plate (mu_p), the estimated systematic offset for row i (R_{ip}), and the systematic offset for column j (C_{jp}).
y_{ijp}是我行测量值和列板的P（ - 被认为是唯一的样本井槽assayData）J，yest_{ijp}是相应的拟合值。这是我定义为估计平均之间的板（mu_p），行偏移估计系统的总和（R_{ip}），系统偏移j列（C_{jp}） 。
NOTE: In the original B score method, as presented by Malo et al., a further step is performed: for each plate p, each of the obtained residual values r_{ijp}'s are divided by the median absolute deviation of the residuals in plate p (MAD_p), resulting in:
注：在原来的B评分方法，作为圣马洛等，进行进一步的步骤：为每个板P，每个所获得的剩余价值。r_{ijp}的中位数绝对偏差除以板P（MAD_p）造成的残差：
The intention of such a further adjustment is to compensate for plate-to-plate variability in dynamic range. In the Bscore function, this step is not automatically performed, but can be done if B score normalization is called using the function normalizePlates with arguments method="Bscore" and varianceAdjust="byPlate". See the latter function for more details.
进一步调整的目的，是为了弥补板到板在动态范围的变化。在Bscore函数，这一步是没有自动执行，但可以做到的，如果B得分标准化被称为使用功能normalizePlates参数method="Bscore"和varianceAdjust="byPlate"。后者功能的更多细节，请参阅。
If save.model=TRUE, the models row and column offsets and overall offsets are stored in the slots rowcol.effects and overall.effects of object.
如果save.model=TRUE，模型的行和列偏移和整体偏移存储在插槽rowcol.effects和overall.effectsobject。
值----------Value----------
An object of class cellHTS with B-score normalized data stored in slot assayData.
存储插槽cellHTS类assayData得分的B-规范化的数据对象。
Furthermore, if save.model=TRUE, the row and column effects and the overall effects are stored in slots rowcol.effects and overall.effects , respectively. The latter slots are arrays with the same dimension as Data(object), except the overall.effects slot, which has dimensions nr Plates x nr Samples x nr Channels.
此外，如果save.model=TRUE，行和列效应和整体效应插槽rowcol.effects和overall.effects，分别存放在。后者的插槽为Data(object)同一维度的阵列，除了overall.effects插槽，其中有尺寸nr Plates x nr Samples x nr Channels。
After calling this function, the processing status of the cellHTS object is updated in the slot state to object@state["normalized"]=TRUE.
调用此函数后，处理cellHTS对象的状态更新插槽stateobject@state["normalized"]=TRUE。
作者（S）----------Author(s)----------
Ligia Bras
参考文献----------References----------
参见----------See Also----------
medpolish, loess, locfit.robust, plotSpatialEffects, normalizePlates, summarizeChannels plateEffects
medpolish，loess，locfit.robust，plotSpatialEffects，normalizePlates，summarizeChannelsplateEffects
举例----------Examples----------
data("KcViabSmall")
xb <- Bscore(KcViabSmall, save.model = TRUE)
## Calling Bscore function from "normalizePlates" and adding the per-plate variance adjustment step:[＃调用“normalizePlates”的Bscore功能和增加每板方差调整一步：]
xopt <- normalizePlates(KcViabSmall, method="Bscore", varianceAdjust="byPlate", save.model = TRUE)
## Access the slots overall.effects and rowcol.effects[＃访问的的插槽overall.effects和rowcol.effects]
ef1 = plateEffects(xb)
ef2 = plateEffects(xopt)
## double-check [＃双重检查]
stopifnot(
all(xb@rowcol.effects==xopt@rowcol.effects, na.rm=TRUE),
all(xb@overall.effects==xopt@overall.effects, na.rm=TRUE),
identical(ef1, ef2)
)
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 14:13:46
