collect-methods(xcms)
collect-methods()所属R语言包:xcms
Collect MS^n peaks into xcmsFragments
收集到xcmsFragments MS ^ n的峰
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Collecting Peaks into xcmsFragmentss from several MS-runs using xcmsSet and xcmsRaw.
收集到xcmsFragments的几座山峰的MS-使用xcmsSet和xcmsRaw运行。
参数----------Arguments----------
参数:object
(empty) xcmsFragments-class object
(空)xcmsFragments-class的对象
参数:xs
A xcmsSet-class object which contains picked ms1-peaks from several experiments
一个xcmsSet-class挑选几个实验的对象,它包含MS1峰
参数:compMethod
("floor", "round", "none"): compare-method which is used to find the parent peak of a MSnpeak through comparing the MZ-values of the MS1peaks with the MSnParentPeaks.
(“地板”,“圆”,“无”):比较方法用于找到通过比较与MSnParentPeaks的锰锌值的MS1peaks的父MSnpeak峰。
参数:snthresh, mzgap, uniq
these are the parameters for the getspec-peakpicker included in xcmsRaw.
这些是在xcmsRaw包括getspec peakpicker的参数。
Details
详情----------Details----------
After running collect(xFragments,xSet) The peak table of the xcmsFragments includes the ms1Peaks from all experiments stored in a xcmsSet-object. Further it contains the relevant msN-peaks from the xcmsRaw-objects, which were created temporarily with the paths in xcmsSet.
峰值表的xcmsFragments运行后收集(xFragments,XSET),包括从实验在xcmsSet对象存储ms1Peaks的。此外,它包含的xcmsRaw对象,暂时与在xcmsSet路径创造了有关MSN峰。
值----------Value----------
A matrix with columns:
一个矩阵的列:
参数:peakID
unique identifier of every peak
每峰的唯一标识符
参数:MSnParentPeakID
PeakID of the parent peak of a msLevel>1 - peak, it is 0 if the peak is msLevel 1.
父峰PeakID一个msLevel> 1 - 峰值,它是0如果高峰是msLevel 1,。
参数:msLevel
The msLevel of the peak.
高峰msLevel。
参数:rt
retention time of the peak midpoint
保留时间的高峰期的中点
参数:mz
the mz-Value of the peak
MZ-价值高峰
参数:intensity
the intensity of the peak
峰的强度
参数:sample
the number of the sample from the xcmsSet
从xcmsSet样品的数量
参数:GroupPeakMSn
Used for grouped xcmsSet groups
用于分组xcmsSet组
参数:CollisionEnergy
The collision energy of the fragment
碰撞能量的片段
方法----------Methods----------
collect(object, ...)
collect(object, ...)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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