purityCorrect-methods(MSnbase)
purityCorrect-methods()所属R语言包：MSnbase
Performs reporter ions purity correction
执行记者离子纯度校正
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Manufacturers sometimes provide purity correction values indicating the percentages of each reporter ion that have masses differing by +/- n Da from the nominal reporter ion mass due to isotopic variants. This correction is generally applied after reporter peaks quantitation.
制造商有时提供纯度的修正值，表明每个记者离子的百分比，有群众不同的+ / - N大，从记者的名义离子质谱，同位素变种。记者高峰定量后，这种修正是普遍适用。
Purity correction here is applied using solve from the base package using the purity correction values as coefficient of the linear system and the reporter quantities as the right-hand side of the linear system. 'NA' values are ignored and negative intensities after correction are also set to 'NA'.
这里的纯度校正应用于使用solvebase使用纯度为系数的线性系统和线性系统的右侧，记者数量修正值的包。 “不适用的值将被忽略，修正后的负强度也设置为无。
A more elaborated purity correction method is described in Shadforth et al., i-Tracker: for quantitative proteomics using iTRAQ. BMC Genomics. 2005 Oct 20;6:145. (PMID 16242023).
一个更详细的纯度校正方法描述在Shadforth等，我 - 追踪：iTRAQ的定量蛋白质组学。 BMC的基因组。 2005年10月20日; 6:145。 （显示16242023）。
Function makeImpuritiesMatrix creates a simple graphical interface to guide the user in the creation of such a matrix. The function takes the dimension of the square matrix (i.e the number of reporter ions) as argument. When available, default values taken from manufacturer's certificaiton sheets are provided, but batch specific values should be used whenever possible. makeImpuritiesMatrix returns the (possibly updated) matrix to be used with purityCorrect.
功能makeImpuritiesMatrix创建一个简单的图形界面来指导用户在建立这样一个矩阵。该函数方阵（即记者离子的数量）作为参数的尺寸。可用时，采取从制造商的认证是表的默认值提供，但批次的具体数值应尽可能使用。 makeImpuritiesMatrix返回可用于与purityCorrect（可能更新）矩阵。
参数----------Arguments----------
参数：object
An object of class "MSnSet".
对象类"MSnSet"。
参数：impurities
A square 'matrix' of dim equal to ncol(object) defining the correction coefficients to be applied. The reporter ions should be ordered along the columns and the relative percentages along the rows. As an example, below is the correction factors as provided in an ABI iTRAQ 4-plex certificate of analysis: <table summary="Rd table"> <tr> <td align="left"> reporter </td><td align="right"> % of -2 </td><td align="right"> % of -1 </td><td align="right"> % of +1 </td><td align="right"> % of +2 </td> </tr> <tr> <td align="left"> 114 </td><td align="right"> 0.0 </td><td align="right"> 1.0 </td><td align="right"> 5.9 </td><td align="right"> 0.2 </td> </tr> <tr> <td align="left"> 115 </td><td align="right"> 0.0 </td><td align="right"> 2.0 </td><td align="right"> 5.6 </td><td align="right"> 0.1 </td> </tr> <tr> <td align="left"> 116 </td><td align="right"> 0.0 </td><td align="right"> 3.0 </td><td align="right"> 4.5 </td><td align="right"> 0.1 </td> </tr> <tr> <td align="left"> 117 </td><td align="right"> 0.1 </td><td align="right"> 4.0 </td><td align="right"> 3.5 </td><td align="right"> 0.1 </td> </tr> <tr> <td align="left"> </td> </tr> </table> The impurity table will be <table summary="Rd table"> <tr> <td align="right"> 0.920 </td><td align="right"> 0.020 </td><td align="right"> 0.000 </td><td align="right"> 0.000 </td> </tr> <tr> <td align="right"> 0.059 </td><td align="right"> 0.923 </td><td align="right"> 0.030 </td><td align="right"> 0.001 </td> </tr> <tr> <td align="right"> 0.002 </td><td align="right"> 0.056 </td><td align="right"> 0.924 </td><td align="right"> 0.040 </td> </tr> <tr> <td align="right"> 0.000 </td><td align="right"> 0.001 </td><td align="right"> 0.045 </td><td align="right"> 0.923 </td> </tr> <tr> <td align="right"> </td> </tr> </table> where, the diagonal is computed as 100 - sum of rows of the original table and subsequent cells are directly filled in.
正方形矩阵的点心等于NCOL（对象）定义要应用校正系数。记者离子应当责令沿沿行，列和相对百分比。作为一个例子，下面是在ABI iTRAQ的4复杂的分析证书规定的修正因素：<table summary="Rd table"> <TR> <TD ALIGN="LEFT">记者</ TD> <TD对齐=“”> -2％</ TD> <td align="right">％-1 </ TD> <td align="right">％+1 </ TD> <TD对齐=“权“> +2％</ TD> </ TR> <TR> <td ALIGN="LEFT"> 114 </ TD> <td align="right"> 0.0 </ TD> <TD =”右对齐“> 1.0 </ TD> <td align="right"> 5.9 </ TD> <td align="right"> 0.2 </ TD> </ TR> <TR> <TD ALIGN="LEFT"> 115 < / TD> <TD align="right"> 0.0 </ TD> <td align="right"> 2.0 </ TD> <td align="right"> 5.6 </ TD> <td align="right"> 0.1 </ TD> </ TR> <TR> <TD ALIGN="LEFT"> 116 </ TD> <td align="right"> 0.0 </ TD> <td align="right"> 3.0 </ TD > <td align="right"> 4.5 </ TD> <td align="right"> 0.1 </ TD> </ TR> <TR> <TD ALIGN="LEFT"> 117 </ TD> <TD对齐=“”> 0.1 </ TD> <td align="right"> 4.0 </ TD> <td align="right"> 3.5 </ TD> <td align="right"> 0.1 </ TD> < / TR> <TR> <td ALIGN="LEFT"> </ TD> </ TR> </表>将杂质表<table summary="Rd table"> <TR> <TD对齐=“右” > 0.920 </ TD> <td align="right"> 0.020 </ TD> <td align="right"> 0.000 </ TD> <td align="right"> 0.000 </ TD> </ TR> < TR> <td align="right"> 0.059 </ TD> <td align="right"> 0.923 </ TD> <td align="right"> 0.030 </ TD> <td align="right"> 0.001 </ TD> </ TR> <TR> <td align="right"> 0.002 </ TD> <td align="right"> 0.056 </ TD> <td align="right"> 0.924 </ TD> <td align="right"> 0.040 </ TD> </ TR> <TR> <td align="right"> 0.000 </ TD> <td align="right"> 0.001 </ TD> <TD对齐= “右”> 0.045 </ TD> <td align="right"> 0.923 </ TD> </ TR> <TR> <td align="right"> </ TD> </ TR> </ TABLE> ，对角线计算为100 - 原始表的行和随后的单元的总和，直接填写。
方法----------Methods----------
举例----------Examples----------
## quantifying full experiment[＃量化充分的实验]
file <- dir(system.file(package="MSnbase",dir="extdata"),full.name=TRUE,pattern="mzXML$")
aa <- readMSData(file,verbose=FALSE)
msnset <- quantify(aa,method="trap",reporters=iTRAQ4)
impurities <- matrix(c(0.929,0.059,0.002,0.000,
0.020,0.923,0.056,0.001,
0.000,0.030,0.924,0.045,
0.000,0.001,0.040,0.923),
nrow=4)
## or, using makeImpuritiesMatrix()[＃或，使用makeImpuritiesMatrix（）]
## Not run: impurities <- makeImpuritiesMatrix(4)[＃无法运行：杂质< - makeImpuritiesMatrix（4）]
msnset.crct <- purityCorrect(msnset,impurities)
head(exprs(msnset))
head(exprs(msnset.crct))
processingData(msnset.crct)
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。
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发表于 2012-2-26 07:31:27
