CN112730712B - Method for improving LC-MS data signal-to-noise ratio - Google Patents

Method for improving LC-MS data signal-to-noise ratio Download PDF

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CN112730712B
CN112730712B CN202011614196.5A CN202011614196A CN112730712B CN 112730712 B CN112730712 B CN 112730712B CN 202011614196 A CN202011614196 A CN 202011614196A CN 112730712 B CN112730712 B CN 112730712B
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李文杰
俞晓峰
李锐
韩双来
杨继伟
郭子杨
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FOCUSED PHOTONICS (HANGZHOU) Inc
Hangzhou Puyu Technology Development Co Ltd
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Abstract

The invention provides a method for improving LC-MS data signal-to-noise ratio, which comprises the following steps: (A1) obtaining chromatographic peak
Figure 290810DEST_PATH_IMAGE001
Starting position of
Figure 880054DEST_PATH_IMAGE002
And an end position
Figure 597474DEST_PATH_IMAGE003
(ii) a (A2) Will be provided with
Figure 930367DEST_PATH_IMAGE001
Division into peak portions
Figure 180957DEST_PATH_IMAGE004
And a non-peak portion
Figure 941103DEST_PATH_IMAGE005
Entering steps (B1) - (B6) and (C1) - (C2), respectively; (B1) according to
Figure 145819DEST_PATH_IMAGE001
Designing a basis function; (B2) to obtain
Figure 547982DEST_PATH_IMAGE004
First layer approximation coefficient of
Figure 653079DEST_PATH_IMAGE006
And first layer detail coefficients
Figure 584126DEST_PATH_IMAGE007
(ii) a (B3) To obtain
Figure 479400DEST_PATH_IMAGE004
Multi-layer approximation coefficient of
Figure 685254DEST_PATH_IMAGE008
And coefficient of detail of each layer
Figure 474218DEST_PATH_IMAGE009
(ii) a (B4) To obtain
Figure 340281DEST_PATH_IMAGE004
Approximate part of
Figure 519589DEST_PATH_IMAGE010
And details
Figure 201238DEST_PATH_IMAGE011
；
Figure 782392DEST_PATH_IMAGE011
EMD empirical mode decomposition is carried out; (B5) calculating an energy value for each modal component
Figure 648717DEST_PATH_IMAGE012
(ii) a (B6) Obtaining denoised peak partial information
Figure 542418DEST_PATH_IMAGE013
(ii) a (C1) Obtained by the way of steps (B1) - (B4)
Figure 90074DEST_PATH_IMAGE005
Approximate part of
Figure 463417DEST_PATH_IMAGE014
(ii) a (C2) Integration
Figure 438327DEST_PATH_IMAGE015
And an approximation part
Figure 825183DEST_PATH_IMAGE014
To obtain a denoised chromatographic peak
Figure 973268DEST_PATH_IMAGE016
. The invention has the advantages of good denoising effect and the like.

Description

Method for improving LC-MS data signal-to-noise ratio
Technical Field
The invention relates to chromatography, in particular to a method for improving the signal-to-noise ratio of LC-MS data.
Background
Liquid chromatography-mass spectrometry (LC-MS) is an important tool for qualitative analysis of complex mixture samples. The device integrates the advantages of two instruments, namely a liquid chromatography instrument and a mass spectrum instrument, has greater advantages, and is widely applied to various fields such as environment, food, geological detection and the like. The raw LC-MS data is the basis for qualitative analysis of LC-MS, but it may contain interference from instrument noise, neutrals, other compounds, etc., and if the raw LC-MS data is directly applied to qualitative analysis of a mixture sample, the resulting analysis results are unreliable. Furthermore, the complexity of LC-MS systems often makes it difficult for analysts to meet method detection limitations. Therefore, there is a need for an algorithm that can improve the signal-to-noise ratio of LC-MS while ensuring that the signal is not distorted.
In order to improve the signal-to-noise ratio of LC-MS data, some denoising algorithms are commonly used for processing, including:
1. fourier filtering methods, which have insufficient processing power for non-stationary signals and cannot obtain the time when each frequency occurs.
2. The wavelet denoising method can process non-stationary signals, but the threshold parameter selection of wavelet transformation is difficult.
3. The polynomial smoothing algorithm, also called SG filtering, weights the data in the window and can smooth the noise, but it is not adaptive.
In addition, the above algorithms all process the whole spectral line at the same time, and may cause signal distortion while filtering noise.
The signal of the LC-MS data has the characteristic of local mutation, and when the signal is processed by using a traditional denoising algorithm, the noise is removed, and the tip of the signal is usually removed, so that the response of a signal peak is reduced, and the subsequent analysis is not facilitated.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides the method for improving the signal-to-noise ratio of the LC-MS data, which has good denoising effect and undistorted useful signals.
The purpose of the invention is realized by the following technical scheme:
the method for improving the signal-to-noise ratio of LC-MS data comprises the following steps:
(A1) detecting the peak position p and the width w of the chromatographic peak s (t) to obtain the starting position w of the chromatographic peak s (t)1And an end position w2；
(A2) Dividing the chromatographic peak s (t) into peak portions s1(t) and non-peak portions s2(t) proceeding to step (B1) and step (C1), respectively;
(B1) designing a basis function according to the chromatographic peak s (t), wherein the discretization of the basis function is represented as F, and four orthogonal filters with the length of L are formed according to F; L-D, H-D and L-R, H-R, where L-R is a normalized representation of F, H-R is an orthogonal inverse filter of L-R, L-D is the inverse of L-R, and H-D is the inverse of H-R;
(B2) obtaining a peak portion s1First layer approximation coefficient a of (t)1And first layer detail coefficient d1；
Figure BDA0002874285060000021
L is the filter length;
(B3) by usingObtaining the peak portion s by way of the step (B2)1(t) multilayer approximation coefficient anAnd each layer detail coefficient d1，d2···dnN is an integer greater than 2;
(B4) will approximate the coefficient anAnd layer detail coefficient d1，d2···dnRespectively reconstructing to obtain peak portions s1(t) approximate fraction s1a(t) and details s1b(t)；
Detail section s1b(t) performing EMD empirical mode decomposition,
Figure BDA0002874285060000022
imf is the modal component at different scales, rn(t) is the residual component;
(B5) calculating an energy value for each modal component
Figure BDA0002874285060000023
Obtaining the energy mutation occurring at the k imf component;
(B6) reconstructing low-frequency imf components behind the kth imf component and residual error items thereof to obtain detail part information after effective information is extracted
Figure BDA0002874285060000024
Thereby obtaining the denoised peak partial information s'1(t)＝s1a(t)+s′1b(t)；
(C1) For non-peak portions s2(t) obtaining non-peak portions s in the manner of steps (B1) - (B4)2(t) approximate fraction s2a(t) and the details;
(C2) integrating the peak partial information s'1(t) and an approximation part s2a(t), a denoised chromatographic peak s' (t) is obtained.
Compared with the prior art, the invention has the beneficial effects that:
the denoising effect is good, and useful signals are not distorted;
the method comprises the steps of identifying the position of a signal peak by adopting a peak detection algorithm, constructing different basis functions for a peak part and a non-peak part according to the characteristics of the signal peak for processing, adopting a multi-level denoising algorithm for extracting useful information for signal waves, and adopting forced denoising processing for the non-wave position, so that the noise is effectively eliminated, the signal distortion is not caused, and the signal-to-noise ratio is effectively improved;
for the processing of signal peaks, imf component decomposition and reconstruction are carried out on the detail part of the scale where the noise is located, the difficulty of selecting a threshold coefficient can be avoided, meanwhile, the useful signal of the scale where the noise is located is reserved, and the signal can not be distorted.
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The disclosure of the present invention will become more readily understood with reference to the accompanying drawings. As is readily understood by those skilled in the art: these drawings are only for illustrating the technical solutions of the present invention and are not intended to limit the scope of the present invention. In the figure:
FIG. 1 is a diagram of raw signals according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a signal after wavelet transform;
fig. 3 is a schematic diagram of signals processed by a method according to an embodiment of the invention.
Detailed Description
Fig. 1-3 and the following description depict alternative embodiments of the invention to teach those skilled in the art how to make and use the invention. Some conventional aspects have been simplified or omitted for the purpose of teaching the present invention. Those skilled in the art will appreciate that variations or substitutions from these embodiments will be within the scope of the invention. Those skilled in the art will appreciate that the features described below can be combined in various ways to form multiple variations of the invention. Thus, the present invention is not limited to the following alternative embodiments, but is only limited by the claims and their equivalents.
Example 1:
the structure diagram of the method for improving the signal-to-noise ratio of LC-MS data of the embodiment of the invention comprises the following steps:
(A1) detecting the peak position p and the width w of the chromatographic peak s (t) to obtain the starting position w of the chromatographic peak s (t)1And an end position w2；
(A2) Dividing the chromatographic peak s (t) into peak portions s1(t) and non-peak portions s2(t) proceeding to step (B1) and step (C1), respectively;
(B1) designing a basis function according to the chromatographic peak s (t), wherein the discretization of the basis function is represented as F, and four orthogonal filters with the length of L are formed according to F; L-D, H-D and L-R, H-R, where L-R is a normalized representation of F, H-R is an orthogonal inverse filter of L-R, L-D is the inverse of L-R, and H-D is the inverse of H-R;
(B2) obtaining a peak portion s1First layer approximation coefficient a of (t)1And first layer detail coefficient d1；
Figure BDA0002874285060000041
L is the filter length;
(B3) obtaining the peak portion s by means of the step (B2)1(t) multilayer approximation coefficient anAnd each layer detail coefficient d1，d2···dnN is an integer greater than 2;
(B4) will approximate the coefficient anAnd each layer detail coefficient d1，d2···dnRespectively reconstructing to obtain peak portions s1(t) approximate fraction s1a(t) and details s1b(t)；
Detail section s1b(t) performing EMD empirical mode decomposition,
Figure BDA0002874285060000042
imf is the modal component at different scales, rn(t) is the residual component;
(B5) calculating an energy value for each modal component
Figure BDA0002874285060000043
Obtaining the energy mutation occurring at the k imf component;
(B6) reconstructing low-frequency imf components behind the kth imf component and residual error items thereof to obtain details after effective information is extractedPartial information
Figure BDA0002874285060000044
Thereby obtaining the denoised peak partial information s'1(t)＝s1a(t)+s′1b(t)；
(C1) For non-peak portions s2(t) obtaining non-peak portions s in the manner of steps (B1) - (B4)2(t) approximate fraction s2a(t) and the details;
(C2) integrating the peak partial information s'1(t) and an approximation part s2a(t), a denoised chromatographic peak s' (t) is obtained.
In order to reduce noise without distortion, further, in step (B1),
F＝[0.014 -0.015 -0.124 0.012 0.561 0.640 0.141 -0.028 0.021 0.010]，L＝10。
in order to reduce noise without distortion, further, in step (B2), the peak portion s1(t) convolved with a low-pass filter L.D to obtain a1；
Peak part s1(t) convolved with a high-pass filter H.D to obtain D1。
In order to reduce noise without distortion, further, in step (C1), the discretization of the basis function is expressed as:
F＝[0.014 -0.015 -0.124 0.012 0.283 0.321 0.141 -0.028 0.021 0.010]，L＝10。
for accurate peak finding, further, in step (a1), the peak position p of the chromatographic peak s (t) is detected by:
by a function
Figure BDA0002874285060000051
Performing continuous wavelet transform on chromatographic peak s (t) for mother wavelet, and detecting maximum value in wavelet coefficient matrix, wherein the maximum value corresponds to peak position p of chromatographic peak s (t)
In order to accurately obtain the width of the peak, further, in step (a1), the width w of the chromatographic peak s (t) is detected by:
by a function
Figure BDA0002874285060000052
And obtaining a wavelet transform coefficient matrix for the mother wavelet, and obtaining the width w of a chromatographic peak s (t).
Example 2:
the method for improving the signal-to-noise ratio of LC-MS data is applied to pesticide residue detection according to the embodiment 1 of the invention.
In the application example, the method for improving the signal-to-noise ratio of LC-MS data comprises the following steps:
(A1) obtaining a chromatographic peak s (t), detecting the peak position p and the width w of the chromatographic peak s (t) as shown in FIG. 1, and obtaining the starting position w of the chromatographic peak s (t)1And an end position w2；
The peak position p is obtained in the following manner:
by a function
Figure BDA0002874285060000053
Performing continuous wavelet transform on the chromatographic peak s (t) for the mother wavelet, and detecting a maximum value in a wavelet coefficient matrix, wherein the maximum value corresponds to the peak position p of the chromatographic peak s (t);
the width w of the chromatographic peak s (t) is obtained in the following manner:
by a function
Figure BDA0002874285060000061
Obtaining a wavelet transform coefficient matrix for the mother wavelet to obtain the width w of a chromatographic peak s (t);
(A2) dividing the chromatographic peak s (t) into peak portions s1(t) and non-peak portions s2(t) proceeding to step (B1) and step (C1), respectively;
(B1) designing a basis function according to the chromatographic peak s (t), wherein the discretization of the basis function is expressed as F ═ 0.014-0.015-0.1240.0120.5610.6400.141-0.0280.0210.010 ], and four orthogonal filters with the length L are formed according to F; l D, H & D and L R, H & R, L & R being a normalized representation of F, H & R being a quadrature inverse filter of L & R, L & D being the inverse of L & R, H & D being the inverse of H & R; l ═ 10;
(B2) peak part s1(t) and a low-pass filter LD convolution to obtain the peak part s1First layer approximation coefficient a of (t)1；
Figure BDA0002874285060000062
L is the filter length;
peak part s1(t) convolving with a high-pass filter H.D to obtain a first layer detail coefficient D1，
Figure BDA0002874285060000063
L is the filter length;
(B3) obtaining the peak portion s by means of the step (B2)1(t) multilayer approximation coefficient anAnd each layer detail coefficient d1，d2···dnN is an integer greater than 2; the embodiment is three layers;
(B4) will approximate the coefficient anAnd each layer detail coefficient d1，d2···dnRespectively reconstructing to obtain peak portions s1(t) approximate fraction s1a(t) and details s1b(t)；
Detail section s1b(t) performing EMD empirical mode decomposition,
Figure BDA0002874285060000064
imf is the modal component at different scales, rn(t) is the residual component;
(B5) calculating an energy value for each modal component
Figure BDA0002874285060000065
Obtaining the energy mutation occurring at the k imf component;
(B6) reconstructing low-frequency imf components behind the kth imf component and residual error items thereof to obtain detail part information after effective information is extracted
Figure BDA0002874285060000066
Thereby obtaining the denoised peak partial information s'1(t)＝s1a(t)+s′1b(t)；
(C1) For non-peak portions s2(t) obtaining non-peak portions s in the manner of steps (B1) - (B4)2(t) approximate fraction s2a(t) and the details;
for non-peak portions s2Discretization of the basis functions of (t);
F＝[0.014 -0.015 -0.124 0.012 0.283 0.321 0.141 -0.028 0.021 0.010]，L＝10。
(C2) integrating the peak partial information s'1(t) and an approximation part s2a(t), a denoised chromatographic peak s' (t) is obtained, as shown in FIG. 3.
Fig. 2 schematically shows a signal after processing an original signal using wavelet transformation, where the signal-to-noise ratio is low and the signal is distorted in non-peak portions as compared with the processing of the present embodiment.

Claims (6)

1. The method for improving the signal-to-noise ratio of LC-MS data comprises the following steps:
(A1) detecting chromatographic peak
Figure 560049DEST_PATH_IMAGE001
Peak position of
Figure 971308DEST_PATH_IMAGE002
And width
Figure 970488DEST_PATH_IMAGE003
Obtaining said chromatographic peak
Figure 444719DEST_PATH_IMAGE001
Starting position of
Figure 794929DEST_PATH_IMAGE004
And an end position
Figure 9878DEST_PATH_IMAGE005
；
(A2) Subjecting the chromatographic peak to
Figure 129144DEST_PATH_IMAGE001
Division into peak portions
Figure 771347DEST_PATH_IMAGE006
And a non-peak portion
Figure 608853DEST_PATH_IMAGE007
Entering steps (B1) - (B6) and (C1) - (C2), respectively;
(B1) according to the chromatographic peak
Figure 361914DEST_PATH_IMAGE001
Designing basis functions, said basis functions being discretized as
Figure 335686DEST_PATH_IMAGE008
According to
Figure 140001DEST_PATH_IMAGE008
Are formed into four lengths of
Figure 199224DEST_PATH_IMAGE009
The quadrature filter of (1);
Figure 755976DEST_PATH_IMAGE010
、
Figure 849834DEST_PATH_IMAGE011
and
Figure 833840DEST_PATH_IMAGE012
、
Figure 114780DEST_PATH_IMAGE013
，
Figure 209643DEST_PATH_IMAGE012
is that
Figure 158008DEST_PATH_IMAGE008
Is expressed in terms of the normalization of (a),
Figure 315844DEST_PATH_IMAGE013
is that
Figure 349659DEST_PATH_IMAGE012
The orthogonal inverse filter of (a) is,
Figure 248214DEST_PATH_IMAGE010
is that
Figure 582243DEST_PATH_IMAGE012
In the reverse direction of (a) to (b),
Figure 908051DEST_PATH_IMAGE011
is that
Figure 429163DEST_PATH_IMAGE013
The reverse direction of (1);
(B2) obtaining peak portions
Figure 131408DEST_PATH_IMAGE006
First layer approximation coefficient of
Figure 788786DEST_PATH_IMAGE014
And first layer detail coefficients
Figure 554004DEST_PATH_IMAGE015
；
Figure 296832DEST_PATH_IMAGE016
，
Figure 537189DEST_PATH_IMAGE017
，
Figure 580232DEST_PATH_IMAGE009
Is the filter length;
(B3) obtaining peak portions by means of step (B2)
Figure 998575DEST_PATH_IMAGE006
Multi-layer approximation coefficient of
Figure 743546DEST_PATH_IMAGE018
And coefficient of detail of each layer
Figure 272747DEST_PATH_IMAGE019
，
Figure 153984DEST_PATH_IMAGE020
Is an integer greater than 2;
(B4) will approximate the coefficients
Figure 8808DEST_PATH_IMAGE018
And coefficient of detail of each layer
Figure 978425DEST_PATH_IMAGE019
Respectively reconstructing to obtain peak parts
Figure 311318DEST_PATH_IMAGE006
Approximate part of
Figure 578220DEST_PATH_IMAGE021
And details
Figure 338365DEST_PATH_IMAGE022
；
Detailed description of the invention
Figure 792349DEST_PATH_IMAGE022
Performing EMD empirical mode decomposition on the mixed solution,
Figure 194512DEST_PATH_IMAGE023
，
Figure 315921DEST_PATH_IMAGE024
for the modal components at the different scales,
Figure 512547DEST_PATH_IMAGE025
is the residual component;
(B5) calculating an energy value for each modal component
Figure 470138DEST_PATH_IMAGE026
，
Figure 939908DEST_PATH_IMAGE027
Obtained at the first
Figure 400976DEST_PATH_IMAGE028
An
Figure 17771DEST_PATH_IMAGE024
The components have sudden energy changes;
(B6) will be first
Figure 197080DEST_PATH_IMAGE028
An
Figure 941045DEST_PATH_IMAGE024
Low frequency after component
Figure 771466DEST_PATH_IMAGE024
Reconstructing the component and the residual error item thereof to obtain the detail part information after extracting the effective information
Figure 309895DEST_PATH_IMAGE029
To obtain the denoised peak information
Figure 225767DEST_PATH_IMAGE030
；
(C1) For non-peak parts
Figure 773423DEST_PATH_IMAGE031
Obtaining non-peak portions in the manner of steps (B1) - (B4)
Figure 209084DEST_PATH_IMAGE031
Approximate part of
Figure 436190DEST_PATH_IMAGE032
And a detailed section;
(C2) integrating the peak portion information
Figure 590091DEST_PATH_IMAGE033
And an approximation part
Figure 925127DEST_PATH_IMAGE032
To obtain a denoised chromatographic peak
Figure 215294DEST_PATH_IMAGE034
。
2. The method of claim 1, wherein in step (B1), F = [ 0.014-0.015-0.1240.0120.5610.6400.141-0.0280.0210.010 ]]，
Figure 813634DEST_PATH_IMAGE035
。
3. The method of improving the signal-to-noise ratio of LC-MS data of claim 1, wherein in step (B2), the peak portions are
Figure 189252DEST_PATH_IMAGE036
And a low-pass filter
Figure 327978DEST_PATH_IMAGE037
Convolution to obtain
Figure 472651DEST_PATH_IMAGE038
；
Peak part
Figure 41561DEST_PATH_IMAGE036
And a high-pass filter
Figure 170054DEST_PATH_IMAGE039
Convolution to obtain
Figure 597624DEST_PATH_IMAGE040
。
4. The method for improving the signal-to-noise ratio of LC-MS data of claim 1, wherein in step (C1), the discretization of the basis functions is represented as:
F=[0.014 -0.015 -0.124 0.012 0.283 0.321 0.141 -0.028 0.021 0.010]，
Figure 377230DEST_PATH_IMAGE041
。
5. the method for improving signal-to-noise ratio of LC-MS data of claim 1, wherein in step (A1), a chromatographic peak is detected
Figure 333685DEST_PATH_IMAGE001
Peak position of
Figure 198741DEST_PATH_IMAGE042
The method comprises the following steps:
by a function
Figure 430002DEST_PATH_IMAGE043
Is a mother wavelet to a chromatographic peak
Figure 814847DEST_PATH_IMAGE001
Performing a continuous wavelet transform, detecting maxima in a matrix of wavelet coefficients, the methodMaximum value corresponding to chromatographic peak
Figure 722629DEST_PATH_IMAGE001
Peak position of
Figure 560135DEST_PATH_IMAGE044
。
6. The method for improving signal-to-noise ratio of LC-MS data of claim 1, wherein in step (A1), a chromatographic peak is detected
Figure 50547DEST_PATH_IMAGE001
Width of (2)
Figure 24319DEST_PATH_IMAGE045
The method comprises the following steps:
by a function
Figure 103003DEST_PATH_IMAGE046
Obtaining a wavelet transform coefficient matrix for the mother wavelet to obtain a chromatographic peak
Figure 162226DEST_PATH_IMAGE001
Width of (2)
Figure 984557DEST_PATH_IMAGE045
。
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