mspeaks

Convert raw peak data to peak list (centroided data)

句法

峰列=mspeaks(X，，，，我ntensities） [[峰列，，，，pFWHH] = mspeaks(X，，，，我ntensities） [[峰列，，，，pFWHH，，，，pExt] = mspeaks(X，，，，我ntensities） mspeaks(X，，，，我ntensities， ...'根据'，BaseValue，...）） mspeaks(X，，，，我ntensities，...'Levels',LevelsValue，...）） mspeaks(X，，，，我ntensities，...“噪声试验器”，NoingerestimatorValue，...）） mspeaks(X，，，，我ntensities，...'Multiplier',MultiplierValue，...）） mspeaks(X，，，，我ntensities，...'Denoising',denoisingvalue，...）） mspeaks(X，，，，我ntensities，...'peakLocation',峰值值，...）） mspeaks(X，，，，我ntensities，...'fwhhfilter'，FWHHFilterValue，...）） mspeaks(X，，，，我ntensities，...'OverSegmentationFilter',OverSegmentationFilterValue，...）） mspeaks(X，，，，我ntensities，...'HeightFilter',高度缩写值，...）） mspeaks(X，，，，我ntensities，...'ShowPlot',ShowPlotValue，...）） mspeaks(X，，，，我ntensities， ...'风格'，StyleValue，...））

Description

峰列=mspeaks(X，，，，我ntensities）finds relevant peaks in raw, noisy peak signal data, and creates峰列，，，，a two-column matrix, containing the separation-axis value and intensity for each peak.Xis a vector of separation-unit values for a set of signals with peaks.我ntensities是一组共享相同分离单元范围的峰值的强度值矩阵。

[[峰列，，，，pFWHH] = mspeaks(X，，，，我ntensities）返回pFWHH,一个两列的矩阵表示左边,对吗t locations of the full width at half height (FWHH) markers for each peak. For any peak not resolved at FWHH,mspeaks改为返回峰形范围。什么时候我ntensities包括多个信号，然后pFWHHis a cell array of matrices.

[[峰列，，，，pFWHH，，，，pExt] = mspeaks(X，，，，我ntensities）返回pExt,一个两列的矩阵表示左边,对吗t locations of the peak shape extents determined after wavelet denoising. When我ntensities包括多个信号，然后pExtis a cell array of matrices.

mspeaks(X，，，，我ntensities，...'属性名称',适当的价值，...））呼叫mspeakswith optional properties that use property name/property value pairs. You can specify one or more properties in any order. Enclose each属性名称在单引号中。每个属性名称是病例不敏感的。这些属性名称/属性值对如下：

mspeaks(X，，，，我ntensities， ...'根据'，BaseValue，...））specifies the wavelet base.

mspeaks(X，，，，我ntensities，...'Levels',LevelsValue，...））指定小波分解的水平数。

mspeaks(X，，，，我ntensities，...“噪声试验器”，NoingerestimatorValue，...））specifies the method to estimate the threshold,t，，，，至filter out noisy components in the first high-band decomposition (y_h）。

mspeaks(X，，，，我ntensities，...'Multiplier',MultiplierValue，...））specifies the threshold multiplier constant.

mspeaks(X，，，，我ntensities，...'Denoising',denoisingvalue，...））controls the use of wavelet denoising to smooth the signal. Choices aretrue（默认）或false。

mspeaks(X，，，，我ntensities，...'peakLocation',峰值值，...））指定的比例要使用的峰高至select the points used to compute the centroid separation-axis value of the respective peak.峰值值必须是一个值≥ 0and≤ 1。Default is1。0。

mspeaks(X，，，，我ntensities，...'fwhhfilter'，FWHHFilterValue，...））针对报告的峰值指定分离单元的最小全宽度（FWHH）。从输出列表中排除了低于此值的FWHH的峰值峰列。

mspeaks(X，，，，我ntensities，...'OverSegmentationFilter',OverSegmentationFilterValue，...））specifies the minimum distance, in separation units, between neighboring peaks. When the signal is not smoothed appropriately, multiple maxima can appear to represent the same peak. Increase this filter value to join oversegmented peaks into a single peak.

mspeaks(X，，，，我ntensities，...'HeightFilter',高度缩写值，...））specifies the minimum height for reported peaks. Peaks with heights below this value are excluded from the output list峰列。

mspeaks(X，，，，我ntensities，...'ShowPlot',ShowPlotValue，...））控制原始信号的图表的显示，并在输出矩阵中包含峰峰列标记。

mspeaks(X，，，，我ntensities， ...'风格'，StyleValue，...））specifies the style for marking the peaks in the plot.

mspeaksfinds peaks in data from any separation technique that produces signal data, such as spectroscopy, nuclear magnetic resonance (NMR), electrophoresis, chromatography, or mass spectrometry.

我nput Arguments

`X`	Vector of separation-unit values for a set of signals with peaks. The number of elements in the vector equals the number of rows in the matrix`我ntensities`。the separation unit can quantify wavelength, frequency, distance, time, or m/z depending on the instrument that generates the signal data.
`我ntensities`	一组共享相同分离单元范围的峰值的强度值矩阵。每一行都对应于一个分离单位值，每个列对应于一组具有峰值或保留时间的信号。行的数量等于向量中的元素数量`X`。
`BaseValue`	整数来自`2`至`20`这指定了小波底座。默认：`4`
`LevelsValue`	整数来自`1`至`12`这指定了小波分解的水平数。默认：`10`
`NoingerestimatorValue`	Character vector, string, or scalar that specifies the method to estimate the threshold,`t`，，，，至filter out noisy components in the first high-band decomposition (`y_h`）。选择是: `mad`— Default. Median absolute deviation, which calculates`t=sqrt(2log(n））mad(y_h） / 0.6745`，，，，where`n`=行中的行数`我ntensities`矩阵。 `标准`— Standard deviation, which calculates`t=标准(y_h）`。 A positive real value.
`MultiplierValue`	positive real value that specifies the threshold multiplier constant. 默认：`1。0`
`denoisingvalue`	Controls the use of wavelet denoising to smooth the signal. Choices are`true`（默认）或`false`。小费我f your data was previously smoothed, for example, with the`mslowess`or`女士`功能，您不需要使用小波Denoisising。将此属性设置为`false`。
`峰值值`	Value that specifies the proportion of the peak height to use to select the points to compute the centroid separation-axis value of the respective peak. The value must be`≥ 0`and`≤ 1`。笔记什么时候`峰值值`=`1。0`，峰位置位于峰值的最大值。什么时候`峰值值`=`0`，，，，`mspeaks`从最接近最小到峰值的最小值到峰右侧的最小最小值的所有点计算峰位置。默认：`1。0`
`FWHHFilterValue`	positive real value that specifies the minimum full width at half height (FWHH), in separation units, for reported peaks. Peaks with FWHH below this value are excluded from the output list`峰列`。默认：`0`
`OverSegmentationFilterValue`	positive real value that specifies the minimum distance, in separation units, between neighboring peaks. When the signal is not smoothed appropriately, multiple maxima can appear to represent the same peak. Increase this filter value to join oversegmented peaks into a single peak. 默认：`0`
`高度缩写值`	positive real value that specifies the minimum height for reported peaks. 默认：`0`
`ShowPlotValue`	控制原始信号和平滑信号的图的显示，其中峰包含在输出矩阵中`峰列`标记。选择是`true`，，，，`false`，或者`我`，，，，an integer specifying the index of a spectrum in`我ntensities`。我f set to`true`，，，，the first spectrum in`我ntensities`被绘制。默认值为： `false`- 指定返回值时。 `true`— When you do not specify return values.
`StyleValue`	Character vector or string specifying the style for marking the peaks in the plot. Choices are: `'peak'`(default) — Places a marker at the peak crest. `'exttriangle'`— Draws a triangle using the peak crest and the extents. `'fwhhtriangle'`— Draws a triangle using the peak crest and the FWHH points. `'`— Places a marker at the peak crest and vertical lines at the extents. `“ fwhhline”`— Places a marker at the peak crest and a horizontal line at FWHH.

输出参数

`峰列`	两列矩阵，其中每一行对应于峰值。第一列包含分离单位值（指示沿分隔轴的峰位置）。第二列包含强度值。什么时候`我ntensities`包括多个信号，然后`峰列`是矩阵的单元格数组，每个矩阵都包含峰值列表。
`pFWHH`	两列矩阵指示每个峰的全宽度（FWHH）标记的全宽度的左右位置。对于未解决的任何峰值，`mspeaks`改为返回峰形范围。什么时候`我ntensities`包括多个信号，然后`pFWHH`is a cell array of matrices.
`pExt`	two-column matrix indicating the left and right locations of the peak shape extents determined after wavelet denoising. When`我ntensities`包括多个信号，然后`pExt`is a cell array of matrices.

Examples

加载一个包含两个质谱数据变量的BioInformatics Toolbox™软件中包含的垫子文件，MZ_lo_resandY_lo_res。MZ_lo_resis a vector of m/z values for a set of spectra.Y_lo_resis a matrix of intensity values for a set of mass spectra that share the same m/z range.
```
loadsample_lo_res
```
Adjust the baseline of the eight spectra stored inY_lo_res。
```
yb = msbackadj（mz_lo_res，y_lo_res）;
```
通过在每个光谱中找到相关峰，将原始质谱数据转换为峰列表。
```
p=mspeaks(MZ_lo_res,YB);
```
绘制第三频谱YB，，，，the matrix of baseline-corrected intensity values, with the detected peaks marked.
```
p = mspeaks（mz_lo_res，yb，“ Showplot”，，，，3);
```

Smooth the signal using themslowess功能。然后通过找到相关峰并绘制第三频谱，将平滑的数据转换为峰列表。

YS = mslowess(MZ_lo_res,YB,“ Showplot”，，，，3);

p = mspeaks（mz_lo_res，ys，'DENOISING'，，，，false,“ Showplot”，，，，3);

使用cellfun从输出中列出的八个峰值中删除M/z值的所有峰值的功能p。然后将第三频谱（红色）的峰上绘制在其平滑信号（蓝色）上。

Q = cellfun(@(p) p(p(:,1)>2000,:),P,“统一输出”，错误的）;图图（mz_lo_res，ys（：，3），'b'，，，，Q{3}(:,1),Q{3}(:,2),'rx'）xlabel('Mass/Charge (M/Z)'）ylabel(“相对强度”）轴（[0 20000 -5 95]）

Algorithms

mspeaks通过：

Smoothing the signal using undecimated wavelet transform with Daubechies coefficients
Assigning peak locations
估计噪声
Eliminating peaks that do not satisfy specified criteria

References

[[1] Morris, J.S., Coombes, K.R., Koomen, J., Baggerly, K.A., and Kobayash, R. (2005) Feature extraction and quantification for mass spectrometry in biomedical applications using the mean spectrum. Bioinfomatics21:9，，，，1764–1775.

[2] Yasui，Y.，Pepe，M.，Thompson，M.L.，Adam，B.L.，Wright，G.L.，Y.2003）蛋白质生物标志物发现的数据分析策略：高维蛋白质组学数据的癌症检测分析。生物统计学4：3，，，，449–463.

[[3] Donoho, D.L., and Johnstone, I.M. (1995) Adapting to unknown smoothness via wavelet shrinkage. J. Am. Statist. Asso.90，，，，1200–1224.

[4] Strang，G。和Nguyen，T。（1996）小波和过滤器库（韦尔斯利：剑桥出版社）。

[[5] Coombes, K.R., Tsavachidis, S., Morris, J.S., Baggerly, K.A., Hung, M.C., and Kuerer, H.M. (2005) Improved peak detection and quantification of mass spectrometry data acquired from surface-enhanced laser desorption and ionization by denoising spectra with the undecimated discrete wavelet transform. Proteomics5(16)，，，，4107–4117.

版本历史记录

在R2007A中引入

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