Mass spectrometry data acquisition and processing method

Abstract

The present invention belongs to the technical field of mass spectrometry, specifically a method for collecting and processing mass spectrometry flow cytometry data, including the steps of: (A1) collecting a spectrogram, with the acquisition card in an idle state; (A2) in N mass axis intervals A of the collected spectrogram i select data points exceeding a first threshold S i in the mass axis interval A i ; (A3) select n data points x i on both sides of the selected data points in the mass axis interval A j and obtain a score Z j ; (A4) determine whether the score Z j of the n data points is greater than a second threshold T i of the mass axis interval A where the data points are located i ; (A5) use the remaining data points to obtain the scores Z k of all data points x k ; (A6) determine whether the score Z k is greater than the second threshold T i ; if the number of data points with a positive result reaches a third threshold L i of the mass axis interval A i , a signal event of the mass axis interval A i occurs. The present invention has the advantages of high analysis rate and can be applied in flow cytometers.

Description

Technical Field

[0001] The present invention relates to the field of mass spectrometry technology, and in particular to a mass spectrometry flow data acquisition and processing method. Background Art

[0002] ICP-QTOF is a mass spectrometry flow cytometer that uses a high-speed acquisition card for data acquisition. During the data acquisition process, if data acquisition and screening are not performed inside the acquisition card, a large amount of data processing will be required when the PC's mass spectrometry software performs cell information analysis and processing, which will significantly reduce the processing speed of the flow cytometer.

[0003] Currently, two commonly used methods are:

[0004] 1. The acquisition card uploads all data for analysis. This method transmits large amounts of data and has high requirements for computer configuration. Moreover, when the sampling rate of the acquisition card increases, the processing speed of the flow cytometer will decrease, affecting the performance of the instrument.

[0005] 2. The acquisition card captures multiple segments of fixed-position data from each signal and uploads them. Although this method reduces the amount of data, it also uploads invalid data before the cell event begins. Summary of the invention

[0006] In order to solve the deficiencies in the above-mentioned prior art solutions, the present invention provides a mass spectrometry flow data acquisition and processing method.

[0007] The objective of the present invention is achieved through the following technical solutions:

[0008] The mass spectrometry flow data acquisition and processing method comprises the following steps:

[0009] (A1) Acquisition spectrum, the acquisition card is in idle state;

[0010] (A2) In the N mass axis intervals A of the collected spectrum i In the mass axis interval A i With the first threshold S i Correspondingly, select the mass axis interval A i exceeds the first threshold S i data points, i=1,2…N, N is an integer not less than 2;

[0011] (A3) In mass axis interval A i Select n data points to the left and right of the selected data point x j , and obtain for each data point x j Score Z j , j = 1, 2…n;

[0012] (A4) Determine the score Z of n data points jIs it greater than the mass axis interval A where the data point is located? i The second threshold T i ;

[0013] If the result is yes, remove the data point;

[0014] If the result is no, keep the data point;

[0015] (A5) Use the retained data points to obtain the mass axis interval A i All data points x k Score Z k , k=1,2…s, s is the mass axis interval A i All data points x k The number of s>n;

[0016] (A6) Determine the score Z of s data points k Is it greater than the mass axis interval A where the data point is located? i The second threshold T i ;

[0017] If the number of data points with the result of yes reaches the quality axis interval A i The third threshold L i , the mass axis interval A i The signal event occurs.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] 1. High analysis rate;

[0020] When no cell event occurs, no data is uploaded. When a cell event occurs, only valid fragment data is uploaded, which greatly improves the spectrum analysis rate.

[0021] 2. The calculation and judgment logic of the present invention is used to ensure that cell events occur effectively and the integrity of data is ensured. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The disclosure of the present invention will become easier to understand with reference to the accompanying drawings. It is easy for those skilled in the art to understand that these drawings are only used to illustrate the technical solution of the present invention and are not intended to limit the scope of protection of the present invention. In the drawings:

[0023] Figure 1 It is a schematic flow chart of the mass spectrometry flow data acquisition and processing method of the present invention;

[0024] Figure 2 It is a schematic diagram of the mass axis interval of the present invention. DETAILED DESCRIPTION

[0025] Figure 1-Figure 2The following description describes optional specific embodiments of the present invention to teach those skilled in the art how to implement and reproduce the present invention. In order to teach the technical solution of the present invention, some conventional aspects have been simplified or omitted. Those skilled in the art will understand that variations or replacements derived from these specific embodiments will be within the scope of the present invention. Those skilled in the art will understand that the following features can be combined in various ways to form multiple variations of the present invention. Thus, the present invention is not limited to the following optional specific embodiments, but is only limited by the claims and their equivalents.

[0026] Example 1.

[0027] The mass spectrometry data acquisition and processing method of the embodiment of the present invention is as follows: Figure 1 As shown, including:

[0028] (A1) Acquisition spectrum, the acquisition card is in idle state;

[0029] (A2) If Figure 2 As shown, in the N mass axis intervals A of the collected spectrum i In the mass axis interval A i With the first threshold S i Correspondingly, select the mass axis interval A i exceeds the first threshold S i data points, i=1,2…N, N is an integer not less than 2;

[0030] (A3) In mass axis interval A i Select n data points to the left and right of the selected data point x j , and obtain for each data point x j Score Z j , j = 1, 2…n;

[0031] (A4) Determine the score Z of n data points j Is it greater than the mass axis interval A where the data point is located? i The second threshold T i ;

[0032] If the result is yes, remove the data point;

[0033] If the result is no, keep the data point;

[0034] (A5) Use the retained data points to obtain the mass axis interval A i All data points x k Score Z k , k=1,2…s, s is the mass axis interval A i All data points x k The number of s>n;

[0035] (A6) Determine the score Z of s data points k Is it greater than the mass axis interval A where the data point is located? i The second threshold T i ;

[0036] If the number of data points with the result of yes reaches the quality axis interval A i The third threshold L i , the mass axis interval A i The signal event occurs.

[0037] In order to accurately determine whether a signal event occurs, further, score Z j =(x j -u1) / σ1, u1 and σ1 are the mean and standard deviation of the n data points respectively;

[0038] Score Z k =(x k -u2) / σ2, u2 and σ2 are the mean and standard deviation of the retained data points respectively.

[0039] In order to obtain the threshold value scientifically and accurately, further, the first threshold value S i , the second threshold T i The sum of the third threshold L i The way to obtain is:

[0040] Detect the cell standard sample and obtain each mass axis interval A in the spectrum i All data points x in w Score Z w , w=1,2…s;

[0041] The score Z greater than 0 w The average value is taken as the second threshold T i ;

[0042] Get a value greater than the second threshold T i Score Z w The corresponding data point x w The average value v i , the first threshold S i =F i ·v i , F i is each mass axis interval A i The coefficient of is less than 1, i=1,2…N;

[0043] Get a value greater than the second threshold T i Score Z w The number of H i , the third threshold L i =[D i ·Hi ], D i is each mass axis interval A i The coefficients of which are less than 1, i=1,2…N.

[0044] In order to accurately determine whether a signal event occurs, further, score Z w =(x w -u3) / σ3, u3, σ3 are the mass axis interval A i All data points x in w The mean and standard deviation of the data.

[0045] In order to accurately determine the start of a cell event, the data acquisition and processing method further includes the following steps:

[0046] (A7) Obtain , b is the mass axis interval A where the signal event occurs in the spectrum i The number of i is the mass axis interval A i The ion efficiency, ;

[0047] (A8) Determine whether G is greater than the total ion efficiency;

[0048] If the result is yes, the cell event starts and the acquisition card enters the cell detection state;

[0049] If the result is no, the acquisition card has not entered the cell detection state.

[0050] In order to accurately determine the start of a cell event, further, the total ion efficiency is obtained as follows:

[0051] Detecting the cell standard sample to obtain M spectra, where M is an integer greater than 1000;

[0052] Total ion efficiency = number of signal events appearing in M ​​spectra / (M·theoretical number of signal events in each spectrum);

[0053] Ion efficiency of the mass axis interval = A of the mass axis interval in M ​​spectra i The number of signal events / (M·A in each spectrum i Theoretical number of signal events that occur).

[0054] In order to improve the analysis rate, the data acquisition and processing method further includes the following steps:

[0055] (A9) The acquisition card detects the spectrum in the cell detection state, caches the data of each mass axis interval in the spectrum to the DDR, and notifies the PC software to read the data;

[0056] (A10) Obtain the number of mass axis intervals in each spectrum whose signal is less than a threshold value. If the ratio of this number to the number of mass axis intervals in the spectrum is less than a set value, exit the cell detection state and stop caching data to the DDR.

[0057] In order to obtain the analysis data quickly and accurately, the data format of each mass axis interval in the spectrum cached to DDR is further as follows:

[0058] Repulsion count + the number of starting points of the 1st mass axis interval + the number of mass span points of the 1st mass axis interval + all signal data of the 1st mass axis interval + the number of starting points of the 2nd mass axis interval + the number of mass span points of the 2nd mass axis interval + all signal data of the 2nd mass axis interval +… + the number of starting points of the Nth mass axis interval + the number of mass span points of the Nth mass axis interval + all signal data of the Nth mass axis interval.

[0059] Example 2.

[0060] An application example of the mass spectrometry flow data acquisition and processing method in Example 1 of the present invention.

[0061] In this application example, Figure 1 As shown, the mass spectrometry flow data acquisition and processing method includes the following steps:

[0062] (A0) Detection of cell standard sample, in the obtained spectrum, there are 3 mass axis intervals A i , where the 30 data of the first mass axis interval A1 are: 20, 21, 22, 23, 40, 50, 32, 46, 12, 45, 36, 49, 200, 300, 200, 54, 15, 36, 50, 200, 400, 300, 64, 51, 26, 65, 25, 74, 56, 36, that is, s=30.

[0063] Using Z w =(x w -u3) / σ3 score Z w They are: -0.66, -0.65, -0.64, -0.63, -0.46, -0.36, -0.54, -0.4, -0.74, -0.41, -0.5, -0.37, 1.18, 2.2, 1.18, -0.32, -0.71, -0.5, -0.36, 1.18, 3.22, 2.2, -0.21, -0.35, -0.6, -0.2, -0.61, -0.11, -0.3, -0.5.

[0064] The score Z greater than 0 w The average value of is taken as the second threshold value T1=1.68.

[0065] Obtain a score Z greater than the second threshold T1 w (i.e. 2.2, 3.22, 2.2) corresponding to the data point x w The average value v1 of (i.e. 300, 400, 300), the first threshold S1=F1·v1=133, F1 =0.4.

[0066] Obtain a score Z greater than the second threshold T1 w The number H1=3, the third threshold L1=[D1·H1]=2, D1=0.8.

[0067] Similarly, respective thresholds of the second mass axis interval A2 and the third mass axis interval A3 are obtained.

[0068] The cell standard sample was detected and 10,000 spectra were obtained, M=10,000.

[0069] The total ion efficiency η0 = the number of signal events occurring in 10,000 spectra / (10,000·the theoretical number of signal events in each spectrum).

[0070] Ion efficiency η in the mass axis interval i =10000 mass axis interval A in the spectrum i Number of signal events / (10000·A in the mass axis interval of each spectrum i Theoretical number of signal events that occur).

[0071] (A1) Acquisition spectrum, the acquisition card is in idle state.

[0072] (A2) If Figure 2 As shown, in the three mass axis intervals A of the collected spectrum i In the mass axis interval A i With threshold T i Correspondingly, select the mass axis interval A i exceeds the threshold T i data points, i=1,2,3,N=3.

[0073] For example, in the first mass axis interval A1, the 30 data are: 18, 35, 25, 23, 15, 50, 32, 46, 12, 45, 36, 49, 100, 150, 100, 45, 15, 36, 32, 100, 180, 100, 64, 45, 13, 43, 52, 66, 64, 35, that is, s=30.

[0074] The data point that exceeds the first threshold S1=133 is 150.

[0075] (A3) In mass axis interval A i Select n data points to the left and right of the selected data point xj , and obtain for each data point x j Score Z j =(x j -u1) / σ1, u1, σ1 are the mean and standard deviation of n data points, j=1,2…n.

[0076] For example, in the first mass axis interval A1, 20 data points on both sides of the data point 150 are selected: 15, 50, 32, 46, 12, 45, 36, 49, 100, 150, 100, 45, 15, 36, 32, 100, 180, 100, 64, 45, 13, that is, n=20.

[0077] The scores corresponding to the 20 data points are: -1.02, -0.23, -0.64, -0.32, -1.09, -0.34, -0.55, -0.25, 0.9, 2.02, 0.9, -0.34, -1.02, -0.55, -0.64, 0.9, 2.7, 0.9, 0.08, -0.34, -1.07.

[0078] (A4) Determine the score Z of n data points j Is it greater than the mass axis interval A where the data point is located? i The threshold T i ;

[0079] If the result is yes, remove the data point;

[0080] If the result is no, keep the data point;

[0081] Taking the first quality axis interval A1 as an example, the scores 2.02 and 2.7 exceed the second threshold T1, and the corresponding data points 150 and 180 need to be eliminated, and 18 data points are retained.

[0082] (A5) Use the retained data points to obtain the mass axis interval A i All data points x k Score Z k =(x k -u2) / σ2, k=1,2…s, u2, σ2 are the mean and standard deviation of the retained data points, s is the mass axis interval A i All data points x k , s=30>n=20.

[0083] Taking the first mass axis interval A1 as an example, u2= 60.23, σ2=44.3, the scores corresponding to all 30 data points in the first mass axis interval A1 are:

[0084] -0.95, -0.57, -0.79, -0.84, -1.02, -0.23, -0.64, -0.32, -1.09, -0.34, -0.55, -0.25, 0.9, 2.02, 0.9, -0.34, -1.02, -0.55, -0.64, 0.9, 2.7, 0.9, 0.08, -0.34, -1.07, -0.39, -0.19, 0.13, 0.08, -0.57.

[0085] (A6) Determine the score Z of s data points k Is it greater than the mass axis interval A where the data point is located? i The second threshold T i ;

[0086] If the result is that the number of data points reaches the third threshold L i , the mass axis interval A i The signal event occurs.

[0087] Taking the first quality axis interval A1 as an example, there are two scores exceeding the second threshold, namely 2.02 and 2.7, and the third threshold L1=2 is reached, and a signal event occurs.

[0088] (A7) Obtain , b is the mass axis interval A where the signal event occurs in the spectrum i The number of i is the mass axis interval A i The ion efficiency, .

[0089] (A8) Determine whether G is greater than the total ion efficiency η0.

[0090] If the result is yes, the cell event starts and the acquisition card enters the cell detection state.

[0091] If the result is no, the acquisition card has not entered the cell detection state.

[0092] (A9) When the acquisition card is in the cell detection state, it detects the spectrum, caches the data of each mass axis interval in the spectrum to the DDR, and notifies the PC software to read the data.

[0093] The data format of each mass axis interval in the spectrum cached to DDR is:

[0094] Repulsion count + starting point number of the 1st mass axis interval + mass span point number of the 1st mass axis interval + all signal data of the 1st mass axis interval + starting point number of the 2nd mass axis interval + mass span point number of the 2nd mass axis interval + all signal data of the 2nd mass axis interval + starting point number of the 3rd mass axis interval + mass span point number of the 3rd mass axis interval + all signal data of the 3rd mass axis interval.

[0095] The rejection count records the timestamp information. For an acquisition card with a 1G sampling rate, one rejection acquisition takes 100μs to calculate, and each rejection interval is 10μs. In this case, the first rejection count is 0, the second is 110*1000, and the Nth rejection count is 110*1000*(n-1).

[0096] An example of data transmitted for each spectrum data transmission.

[0097] .

[0098] As shown in the table above, the starting point number of each mass axis interval is the number of points of the relative repulsion count. Under one method, the starting point number and span point number of each interval of each spectrum are fixed.

[0099] (A10) Obtain the number of mass axis intervals in each spectrum whose signal is less than the threshold. If the ratio of this number to the number of mass axis intervals in the spectrum is less than a set value of 2 / 3, exit the cell detection state and stop caching data to the DDR.

Claims

1. A mass spectrometry data acquisition and processing method, comprising the following steps: (A1) Acquisition spectrum, the acquisition card is in idle state; (A2) In the N mass axis intervals A of the collected spectrum i In the mass axis interval A i With the first threshold S i Correspondingly, select the mass axis interval A i exceeds the first threshold S i data points, i=1,2…N, N is an integer not less than 2; (A3) In mass axis interval A i Select n data points to the left and right of the selected data point x j , and obtain for each data point x j Score Z j =(x j -u1) / σ1, j=1,2…n, u1 and σ1 are the mean and standard deviation of n data points respectively; (A4) Determine the score Z of n data points j Is it greater than the mass axis interval A where the data point is located? i The second threshold T i ; If the result is yes, remove the data point; If the result is no, keep the data point; (A5) Use the retained data points to obtain the mass axis interval A i All data points x k Score Z k =(x k -u2) / σ2, k=1,2…s, u2, σ2 are the mean and standard deviation of the retained data points, s is the mass axis interval A i All data points x k The number of s>n; (A6) Determine the score Z of s data points k Is it greater than the mass axis interval A where the data point is located? i The second threshold T i ; If the number of data points with the result of yes reaches the quality axis interval A i The third threshold L i , the mass axis interval A i The signal event occurs; (A7) Obtain , b is the mass axis interval A where the signal event occurs in the spectrum i The number of i is the mass axis interval A i The ion efficiency, ; (A8) Determine whether G is greater than the total ion efficiency; If the result is yes, the cell event starts and the acquisition card enters the cell detection state; If the result is no, the acquisition card has not entered the cell detection state; The total ion efficiency is obtained as follows: Detecting the cell standard sample to obtain M spectra, where M is an integer greater than 1000; Total ion efficiency = number of signal events appearing in M ​​spectra / (M·theoretical number of signal events in each spectrum); Ion efficiency of the mass axis interval = A of the mass axis interval in M ​​spectra i The number of signal events / (M·A in each spectrum i Theoretical number of signal events that occur).

2. The mass spectrometry data acquisition and processing method according to claim 1, characterized in that: The first threshold S i , the second threshold T i The sum of the third threshold L i The way to obtain is: Detect the cell standard sample and obtain each mass axis interval A in the spectrum i All data points x in w Score Z w , w=1,2…s; The score Z greater than 0 w The average value is taken as the second threshold T i ; Get a value greater than the second threshold T i Score Z w The corresponding data point x w The average value v i , the first threshold S i =F i ·v i , F i is each mass axis interval A i The coefficient of is less than 1, i=1,2…N; Get a value greater than the second threshold T i Score Z w The number of H i , the third threshold L i =[D i ·H i ], D i is each mass axis interval A i The coefficients of which are less than 1, i=1,2…N.

3. The mass spectrometry data acquisition and processing method according to claim 2, characterized in that: F i =0.4,D i =0.8。 4. The mass spectrometry data acquisition and processing method according to claim 2, characterized in that: Score Z w =(x w -u3) / σ3, u3, σ3 are the mass axis interval A i All data points x in w The mean and standard deviation of the data.

5. The mass spectrometry data acquisition and processing method according to claim 1, characterized in that: The data collection and processing method further comprises the following steps: (A9) The acquisition card detects the spectrum in the cell detection state, caches the data of each mass axis interval in the spectrum to the DDR, and notifies the PC software to read the data; (A10) Obtain the number of mass axis intervals in each spectrum whose signal is less than a threshold value. If the ratio of this number to the number of mass axis intervals in the spectrum is less than a set value, exit the cell detection state and stop caching data to the DDR.

6. The mass spectrometry data acquisition and processing method according to claim 5, characterized in that: The data format of each mass axis interval in the spectrum cached to DDR is: Repulsion count + the number of starting points of the 1st mass axis interval + the number of mass span points of the 1st mass axis interval + all signal data of the 1st mass axis interval + the number of starting points of the 2nd mass axis interval + the number of mass span points of the 2nd mass axis interval + all signal data of the 2nd mass axis interval +… + the number of starting points of the Nth mass axis interval + the number of mass span points of the Nth mass axis interval + all signal data of the Nth mass axis interval.

7. The mass spectrometry data acquisition and processing method according to claim 5, characterized in that: The set value is 2 / 3.

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