findPeaks.centWave-methods(xcms)
findPeaks.centWave-methods()所属R语言包：xcms
Feature detection for high resolution LC/MS data
高分辨率LC / MS数据的功能检测
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Peak density and wavelet based feature detection for high resolution LC/MS data in centroid mode
峰值电流密度和高分辨率的LC / MS数据的质心模式基于小波特征检测
参数----------Arguments----------
参数：object
xcmsSet object
xcmsSet对象
参数：ppm
maxmial tolerated m/z deviation in consecutive scans, in ppm (parts per million)
maxmial容忍的m / z偏差在连续扫描，以ppm（百万分之一）
参数：peakwidth
Chromatographic peak width, given as range (min,max) in seconds
色谱峰宽，范围（最小值，最大值）在几秒钟内
参数：snthresh
signal to noise ratio cutoff, definition see below.
信号噪声比截止，定义见下文。
参数：prefilter
prefilter=c(k,I). Prefilter step for the first phase. Mass traces are only retained if they contain at least k peaks with intensity >= I.
prefilter=c(k,I)。第一阶段为预过滤步骤。大规模的痕迹只保留如果它们包含至少k峰强度> =I。
参数：mzCenterFun
Function to calculate the m/z center of the feature: wMean intensity weighted mean of the feature m/z values, mean mean of the feature m/z values, apex use m/z value at peak apex, wMeanApex3 intensity weighted mean of the m/z value at peak apex and the m/z value left and right of it, meanApex3 mean of the m/z value at peak apex and the m/z value left and right of it.
函数来计算的m / z为中心的功能：wMean强度特征m / z值的加权平均，meanm / z值的功能意味着，apex使用M / z值，在峰顶wMeanApex3强度在峰顶的m / z值的m / z值的左，右，加权平均，meanApex3m / z值意味着在峰顶和m / z值的左和它的权利。
参数：integrate
Integration method. If =1 peak limits are found through descent on the mexican hat filtered data, if =2 the descent is done on the real data. Method 2 is very accurate but prone to noise, while method 1 is more robust to noise but less exact.
集成方法。如果=1峰值限制被发现筛选后的数据通过血统的墨西哥帽，如果=2血统是做真实的数据。方法2是非常准确，但容易产生噪音，而方法1是更强大的噪音，但不太准确。
参数：mzdiff
minimum difference in m/z for peaks with overlapping retention times, can be negative to allow overlap
最小的m / z差异峰重叠的保留时间，可以是负的，允许重叠
参数：fitgauss
logical, if TRUE a Gaussian is fitted to each peak
逻辑，如果真高斯拟合每个峰
参数：scanrange
scan range to process
扫描范围内处理
参数：noise
optional argument which is useful for data that was centroided without any intensity threshold, centroids with intensity < noise are omitted from ROI detection
可选参数，这是非常有用的数据centroided没有任何强度阈值，强度<重心noise省略的投资回报率检测
参数：sleep
number of seconds to pause between plotting peak finding cycles
暂停之间绘制峰寻找周期秒数
参数：verbose.columns
logical, if TRUE additional peak meta data columns are returned
逻辑，如果真正的额外峰元数据列返回
Details
详情----------Details----------
This algorithm is most suitable for high resolution LC/{TOF,OrbiTrap,FTICR}-MS data in centroid mode. In the first phase of the method mass traces (characterised as regions with less than ppm m/z deviation in consecutive scans) in the LC/MS map are located. In the second phase these mass traces are further analysed. Continuous wavelet transform (CWT) is used to locate chromatographic peaks on different scales.
这种算法是最适合高分辨率的LC / {飞行时间，的Orbitrap，FTICR}-MS数据的质心模式。在第一阶段的方法大规模的痕迹在LC / MS的图（比ppmm / z为连续扫描的偏差以内区域的特点）的位置。在第二阶段进一步分析这些大规模的痕迹。连续小波变换（CWT）用于定位不同尺度上的色谱峰。
值----------Value----------
A matrix with columns:
一个矩阵的列：
参数：mz
weighted (by intensity) mean of peak m/z across scans
加权（强度）意味着整个扫描峰的m / z
参数：mzmin
m/z peak minimum
的m / z峰最低
参数：mzmax
m/z peak maximum
m / z为最大峰值
参数：rt
retention time of peak midpoint
高峰期的中点的保留时间
参数：rtmin
leading edge of peak retention time
峰的保留时间的领先优势
参数：rtmax
trailing edge of peak retention time
峰的保留时间后缘
参数：into
integrated peak intensity
综合峰的强度
参数：intb
baseline corrected integrated peak intensity
基线校正集成峰值强度
参数：maxo
maximum peak intensity
最大峰值强度
参数：sn
Signal/Noise ratio, defined as (maxo - baseline)/sd, where <br> maxo is the maximum peak intensity, <br> baseline the estimated baseline value and <br> sd the standard deviation of local chromatographic noise.
信号/噪声比，定义(maxo - baseline)/sd，其中参考maxo是最大峰值强度，参考baseline估计的基线值和参考sd当地色谱噪声的标准偏差。
参数：egauss
RMSE of Gaussian fit
均方根误差的高斯拟合
参数：
if verbose.columns is TRUE additionally :
如果verbose.columns是TRUE此外：
参数：mu
Gaussian parameter mu
高斯参数亩;
参数：sigma
Gaussian parameter sigma
高斯参数西格马
参数：h
Gaussian parameter h
高斯参数h
参数：f
Region number of m/z ROI where the peak was localised
区域的m / z的投资回报率是本地化的高峰
参数：dppm
m/z deviation of mass trace across scans in ppm
跨ppm的扫描质量跟踪的m / z偏差
参数：scale
Scale on which the peak was localised
尺度上的本地化高峰
参数：scpos
Peak position found by wavelet analysis
小波分析发现峰的位置
参数：scmin
Left peak limit found by wavelet analysis (scan number)
小波分析发现左峰限制（扫描数）
参数：scmax
Right peak limit found by wavelet analysis (scan number)
小波分析发现右峰限制（扫描数）
方法----------Methods----------
findPeaks.centWave(object, ppm=25, peakwidth=c(20,50), snthresh=10, prefilter=c(3,100), mzCenterFun="wMean", integrate=1, mzdiff=-0.001, fitgauss=FALSE, scanrange= numeric(), noise=0, sleep=0, verbose.columns=FALSE)
findPeaks.centWave(object, ppm=25, peakwidth=c(20,50), snthresh=10, prefilter=c(3,100), mzCenterFun="wMean", integrate=1, mzdiff=-0.001, fitgauss=FALSE, scanrange= numeric(), noise=0, sleep=0, verbose.columns=FALSE)
作者（S）----------Author(s)----------
Ralf Tautenhahn
参考文献----------References----------
"Highly sensitive feature detection for high resolution LC/MS" BMC Bioinformatics 2008, 9:504
参见----------See Also----------
findPeaks-methods xcmsRaw-class
findPeaks-methodsxcmsRaw-class
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 16:05:10
