JP4839248B2 - Mass spectrometry system - Google Patents

Description

  The present invention relates to an analysis system for a mass spectrometry spectrum using a mass spectrometer. Substances (particularly proteins, peptides, metabolites, etc.) contained in a large number of samples (particularly biological samples such as urine and blood). The present invention relates to a system for automatically optimizing the contents of mass spectrometry within the real time of measurement in order to perform identification or quantitative analysis with high accuracy and efficiency.

In general mass spectrometry, after a sample to be measured is ionized, various generated ions are sent to a mass spectrometer, and the mass-to-charge ratio m / z, which is the ratio of the mass number m and the valence z of the ions. Every time, the ionic strength is measured. The resulting mass spectrum consists of measured ion intensity peaks (ion peaks) for each mass to charge ratio m / z value. The mass analysis of the sample ionized as described above is called MS ¹ . In a tandem mass spectrometer capable of multistage dissociation, an ion peak having a specific mass-to-charge ratio m / z value is selected from the ion peaks detected by MS ¹ (the selected ion species is the parent). Further, the ions are dissociated and decomposed by collision with gas molecules and the like, and the generated dissociated ion species are subjected to mass spectrometry, and a mass spectrum is similarly obtained. Here, performing n-stage dissociation of the parent ion and mass analyzing the dissociated ion species is referred to as MS ^{n + 1} . In this way, in the tandem mass spectrometer, the parent ions are dissociated into multiple stages (1 stage, 2 stages,..., N stages), and the mass number of the ion species generated at each stage is analyzed (MS ² , MS ³ , ..., MS ^{n + 1} ).

  The above tandem mass spectrometry enables identification of the type of substance contained in the sample and quantitative analysis of the substance contained in the sample.

  In recent years, mass spectrometers have been used for identification / quantitative analysis of proteins, peptides, metabolites, etc. in crude biological samples. In particular, when mass spectrometry is performed on biological samples of multiple specimens, the types and amounts of specific substances are changing in order to discover biomarkers for disease diagnosis, elucidate the metabolic mechanism of drugs, and predict drug efficacy. Analyzing and searching for fluctuation components has begun to be implemented. For example, the following Patent Document 1 describes performing mass spectrometry and comparing analysis results between a patient and a healthy person. In addition, the fluctuation component is also analyzed by comparing before and after administration.

JP 2003-315341 A

  When analyzing and searching for the fluctuation component in another sample compared to the reference data (control data) of multiple samples, there is a large variation in the reference data of multiple samples, and the variation between the data and the true fluctuation component Difficult to distinguish, making it difficult to analyze and search for fluctuation components. There are three main causes of these variations: (1) those generated by sample preparation; (2) those generated during ionization and mass analysis; (3) those generated by data processing and analysis Conceivable. In particular, in order to reduce the causes (1) and (2) of variation, after isotopic labeling between two samples to be compared (for example, between a healthy subject and a patient sample), the two samples are mixed to obtain a mass. Although there is a technique called “labeled quantitative analysis method” for analysis, it is considered unsuitable for the analysis of multi-sample samples because the reagent for isotope labeling is expensive and high skill is required for isotope labeling.

  The present invention has been made based on such a problem, and its purpose is to avoid erroneous determination of fluctuation components due to variations in reference data of a plurality of samples without labeling the samples with isotopes. It is to provide a mass spectrometry system that can be suppressed.

In order to solve the above-mentioned problems, in the present invention, a mass spectrum (MS ¹ ) obtained by mass spectrometry based on any one of the following means (1) to (3) can be rapidly measured within the actual measurement time. The analysis and a plurality of reference data are compared, and the next analysis content is determined.
(1) Statistical processing is performed on a plurality of reference data, and is compared with the acquired mass spectrum data based on the representative values and variance values obtained for each component. To optimize.
(2) A plurality of reference data is grouped based on data similarity, etc., and it is determined which group of data groups the acquired mass spectrum data is close to. The next analysis content is optimized according to the result.
(3) For a plurality of reference data, those having similar data fluctuation characteristics are grouped, and which group of component groups the components detected in the acquired mass spectrum data belong to Judgment is made and the next analysis content is optimized according to the result.

  According to the present invention, it is possible to realize a tandem mass spectrometry system that avoids and suppresses erroneous determination due to variations in reference data.

FIG. 2 shows the overall configuration of the mass spectrometry system according to the present invention. The mass spectrometry system 19 includes a mass spectrometer 40 and a control unit 50. The sample to be analyzed is pretreated by a pretreatment system 11 such as liquid chromatography (LC). For example, in the case of a protein as an original sample, it is decomposed into a polypeptide size by a digestive enzyme in the pretreatment system 11, and separated and fractionated by gas chromatography (GC) or liquid chromatography (LC). The Hereinafter, an example in which LC is employed as the separation / fractionation system in the pretreatment system 11 will be described.

  After sample separation / fractionation, the sample is ionized by the ionization unit 12 and separated by the mass analysis unit 13 according to the mass-to-charge ratio m / z of ions. Here, m is the ion mass, and z is the charge valence of the ion. The separated ions are detected by the ion detection unit 14, and the data processing unit (CPU) 15 organizes and processes the data, and the mass analysis data as the analysis result is displayed on the display unit 16.

  The control unit 17 controls the entire series of mass analysis processes--sample ionization, transport and incidence of the sample ion beam to the mass analysis unit 13, mass separation process, ion detection, and data processing. In the control unit 17, data from the user input unit 18 is input, and data is extracted from the reference database (DB) 10 and automatically stored.

In the present invention, since the above-described tandem mass spectrometry is used as a mass spectrometry method, parent ion dissociation and mass spectrometry are performed in multiple stages. Hereinafter, in the tandem mass spectrometry, n-1 times of the n-stage mass spectrometry after the dissociation represented as MS ^n.

In this analysis method, the mass analysis distribution of the substance in the original sample is measured as mass spectral data (MS ¹ ), then a parent ion having a certain m / z value is selected, dissociated, and the resulting dissociation is obtained. After measuring the mass spectrometry data (MS ² ) of ions, dissociate the selected precursor ions in the MS ² data further, and measure the mass analysis data (MS ³ ) of the obtained dissociated ions.・ Mass analysis is performed in multiple stages (MS ⁿ (n ≧ 3)). At each dissociation stage, information on the molecular structure of the precursor ion that is in the state before dissociation is obtained, which is very effective for estimating the structure of the precursor ion. As the structure information of these precursors becomes more detailed, the estimation accuracy in estimating the parent ion structure that is the original structure is improved.

In the present embodiment, as a precursor ion dissociation method, first, a case where a collision dissociation method in which a precursor gas collides with a buffer gas such as helium is used will be described. Since neutral gas such as helium gas is required for collision dissociation, a collision cell 13A for collision dissociation is provided separately from the mass analyzer 13 as shown in FIG. In some cases, the mass analyzer 13 may be filled with a neutral gas, and the mass analyzer 13 may be subjected to collisional dissociation. In that case, the collision cell 13A becomes unnecessary. Further, as a dissociation means, electron capture dissociation in which target ions are dissociated by irradiating low energy electrons and allowing the parent ions to capture a large amount of low energy electrons may be employed.

  By the tandem mass spectrometry, it is possible to identify the type of substance contained in the sample (sample) and to quantitatively analyze the substance contained in the sample. In recent years, mass spectrometers are particularly used for identification and quantitative analysis of proteins, peptides, metabolites, etc. in crude biological samples. In particular, when mass spectrometry is performed on biological samples of multiple specimens, for the purpose of discovering biomarkers for diagnosing diseases, elucidating the metabolic mechanism of drugs, predicting drug efficacy, etc., for example, comparison between patients and healthy subjects Analyzing and searching for a variable component in which the type and amount of a specific substance are changing by comparison between before and after administration has begun to be implemented.

  FIG. 3 shows an outline of the analysis of the fluctuation component. In FIG. 3, the mass spectrum of the peptide kind of a healthy person (upper figure) and a patient (lower figure) is shown. By comparing the data between this patient and a healthy person, a component in which a specific protein is lost or expressed, or a component whose expression level (intensity and area) is greatly different is analyzed and searched.

  Here, when analyzing and searching for the fluctuation component in another sample compared to the reference data (control data) of multiple samples, there is a large variation in the reference data of multiple samples, and the data variation and the true fluctuation There is a problem that it is difficult to distinguish from the components, and it is difficult to analyze and search the fluctuation components in practice. In order to reduce such variation, the present invention uses a mass spectrometry system provided with control means described in the following embodiments. Hereinafter, each example will be described in order.

  FIG. 1 is a flowchart in the mass spectrometry system of the present embodiment, and mass analysis data 1 in FIG. 1 is data measured by the mass spectrometer 40 in FIG.

In this mass spectrometry system, after mass spectrometry data (MS ⁿ data) 1 is acquired, peak determination (total number of peaks N _p ) 2, isotope peak determination (number of peaks without isotope N _pi ) 3, comparison with reference database 4 is carried out.

In comparison 4 with the reference database, first, for each of the detected peaks (components) _Npi , characteristic information of each peak (each component) i (mass number m of ion species, liquid before the mass spectrometer) Derivation of retention time τ, detection intensity, area (quantity) in mass chromatogram, etc. in liquid chromatography or gas chromatography when chromatography or gas chromatography is installed 4-1 LC retention Acquisition of the time information 4-2 is performed. And the information of the same component as this component is searched 4-3 in the reference database (DB) 10.

The specific contents of the reference database 10 in this embodiment are shown in FIG. FIG. 4 (A) shows the characteristic data (mass number m) of the derived components (peptide, protein, metabolite, etc.) as a result of analyzing information of already acquired MS ¹ mass spectrum data for a plurality of samples. , Valence number z, mass-to-charge ratio m / z, detection intensity I, LC retention time τ, area (quantity) S in mass chromatograph, analysis conditions). Here, the “representative value” is defined as a point having a large distribution for characteristic data of a plurality of samples such as an average value, a mode value, and a median value.

On the other hand, FIG. 4B shows the result of analyzing the already acquired MS ¹ mass spectrum data for a plurality of samples. As a result, the characteristic data (mass number m, The valence z, the mass-to-charge ratio m / z, the detection intensity I, the LC retention time τ, the area (quantity) S in the mass chromatograph, and the dispersion value Δi of the analysis conditions are shown. The “dispersion value” here refers to a value that can be used to evaluate the variation of values for each sample of a plurality of sample characteristic data. Thus, the reference database 10 stores representative values and variance values for the characteristic information of each component.

Then, after the search 4-3 of FIG. 1, the peak difference [Delta] x _i calculated 4-4 with between the representative value of the reference data and current measurement data, stored in the reference database and the difference [Delta] x _i (component) Comparison 4-5 with I dispersion value Δi is performed.

A conceptual diagram of the comparison 4-5 is shown in FIG. In FIG. 5, showing the left view is a difference [Delta] x _i of the measurement data, the data of the dispersion value Δi in the right view reference DB. Here, by performing a comparison between a difference [Delta] x _i and variance values .DELTA.i.

As a result of comparison 4-5 in FIG. 1, when Δx _i ≦ Δi, that is, when the difference between the measured value and the representative value is less than or equal to the variance value, Δx _i is considered to be within the range of variation and the next normal analysis Alternatively, the process proceeds to measurement end 6.

On the other hand, if Δx _i > Δi, that is, if the difference between the measured value and the representative value is larger than the variance value, the next analysis content is specially set on the assumption that Δx _i may indicate a fluctuation amount. In FIG. 1, the process proceeds to the next analysis content determination 9.

  The series of processing shown here is performed at high speed within the preparation time for the next analysis, and is performed within 10 milliseconds in this embodiment.

Here, in the comparison 4-5 of the dispersion value Δi of the peak (component) i in which the difference Δx _i is stored in the reference database, Δx _i ≦ Δi × FCT, Δx _i > Δi × FCT, and so on. The value may be compared with a value (Δi × FCT) obtained by multiplying the variance value Δi by a factor. Moreover, as an example of the stored value of the reference data, as shown in FIG. 6, the characteristic information (holding time τ, intensity) at the peak top in the mass chromatograph for each of the same components of each sample data already acquired is used. The amount (area) of characteristic information may be statistically processed as the area (shaded portion) of each peak of the mass chromatograph. On the other hand, FIG. 7 shows a method for deriving the value of the characteristic information in the current measurement data. In the current measurement data, a mass chromatograph is created for each component in real time, and the components whose peak top of the mass chromatograph was found at that time are compared with the reference data. Not subject to comparison with data.

After the next analysis content determination 9 in FIG. 1, the peak (component) i satisfying Δx _i > Δi is selected as a precursor ion for MS ^{n + 1} analysis because there is a possibility of fluctuation component. Based on this, the next MS ^{n + 1} analysis condition setting 7 is performed, and the MS ^{n + 1} analysis 8 is performed.

A conceptual diagram of a specific example of implementation is shown in FIG. In the MS ¹ data of FIG. 8, when an ion species (component species) whose difference from the reference data exceeds the variation range of the reference data is derived, the next analysis is to select the ion species as a precursor ion. Analyze MS ² data. When there are a plurality of peaks (components) i satisfying Δx _i > Δi, the peak (component) having the largest difference Δx _i is set as the object of the next analysis.

As described above, in this embodiment, the measurement data of MS ^{n and} the data in the reference database are compared to determine whether or not the fluctuation amount of each peak component is within the range of variation for each sample. Based on this, the measurement target of MS ^{n + 1} is selected and the measurement conditions are determined.

According to the present embodiment, when a component that may be a variable component is extracted in real time, it is possible to identify the component by performing MS ² analysis on a component that may be a variable component. As a result, it can be determined whether the fluctuation component is a quantity that has really fluctuated, or whether the fluctuation has occurred because the noise peaks coincided by chance. Therefore, according to the present embodiment, it is possible to suppress erroneous determination of fluctuation components, which is effective for improving the accuracy of fluctuation analysis.

  Next, a second embodiment of the present invention will be described with reference to FIGS.

  FIG. 9 is a flowchart in the mass spectrometry system of the present embodiment, and the processing in the next analysis content determination 9 is different from that in FIG. Others are the same as those in FIG.

In FIG. 9, in analysis content determination 9 after it is determined that there is a possibility of a fluctuation component, the transition to MS ^{n + 1} is prohibited as the next analysis, and the continuation of MS ⁿ analysis is determined 20. ¹ Continue analysis 21.

A conceptual diagram of this measurement flow is shown in FIG. While the ion species (component species) whose difference from the reference data exceeds the range of the variation value of the reference data continues to be derived as in the MS ¹ data shown in the upper and middle figures, the next analysis is MS ² Prohibit analysis and continue MS ¹ analysis. Then, as in the MS ¹ data shown in the lower diagram of FIG. 10, after the ion species whose difference from the reference data exceeds the variation range of the reference data disappears, the process proceeds to the next analysis. As described above, when a component having a possibility of a fluctuation component is derived, in order to increase the fluctuation amount with high accuracy, the amount (area value or strength) of the component is reduced by continuing to perform MS ^1. More accurately derived. That is, according to the present embodiment, it is possible to analyze the quantity fluctuation with higher accuracy for a component that may be a fluctuation component.

  Next, a third embodiment of the present invention will be described with reference to FIGS. The present embodiment is characterized in that in addition to the configuration of the first embodiment, an automatic creation tool shown in FIG. 11 is provided. Here, as a method of creating a reference database, a tool that allows users to specify multiple samples of data that have already been acquired, automatically perform statistical processing on those data, and create a reference database. I have. In this case, there is no need for the user to perform statistical processing, which is effective in improving efficiency.

  Moreover, FIG. 12 is a flowchart in the mass spectrometry system of a present Example. Compared to FIG. 1, after measurement of a sample under analysis is completed, the data after completion of measurement is automatically added as reference data, statistically processed, and stored. Since these processes are the same as those in FIG. 1, the description thereof is omitted. In this case, since the reference data is accumulated without the user being aware, the number of reference data increases one after another, and the accuracy of the reference data can be improved.

  Next, a fourth embodiment of the present invention will be described with reference to FIGS.

  FIG. 13 is a flowchart in the mass spectrometry system of the present embodiment. Compared with FIG. 1, this flow differs from the group 22 reference database in the steps after the comparison 22. Since these processes are the same as those in FIG. 1, the description thereof is omitted.

In comparison with a reference database that grouped 22, with respect to the detected peak (component) N _pi number, the mass number m and the characteristic information (the ion species of the peaks (components) i, in front of the mass spectrometer Derivation 22-1, LC retention time information of retention time τ, detection intensity, area in mass chromatogram, etc.) in liquid chromatography or gas chromatography when liquid chromatography or gas chromatography is installed Acquisition 22-2 is performed, similarity analysis between information based on the measurement data and each group in the reference database (DB) 10 is performed, and a similarity score Scj is calculated 22-3. Here, the “similarity score Scj” is a value obtained by evaluating the similarity of the peak appearance profiles.

  The configuration of the reference database (DB) 10 in this embodiment is shown in FIG. As reference data, reference data is divided into a plurality of groups (reference data group A, reference data group B) based on the similarity of data with respect to data of a plurality of samples already measured (sample No. 1 to sample No. 4). It is classified into. As a classification method in this case, it is possible to specify a component of interest as a marker and group the data based on the similarity of the profile of the data. Alternatively, a classification method as shown in FIG. 15 may be used. In FIG. 15, the vertical axis and the horizontal axis are different factors, and are classified into a reference data group A and a reference data group B by cluster analysis.

  FIG. 16 shows an example of specific contents of the reference database 10 in FIG. As shown in FIG. 16, the information in the reference database is classified into reference data groups A, B,. Moreover, it is good also as the information which performed the statistical process in each reference data group. In this case, each of the reference data groups A, B,... Has information on (A) representative values and (B) variance values, as in the first embodiment.

  Using the reference database 10 as described above, the similarity analysis of the peak appearance profile with respect to the reference data group is performed in FIG. Then, the group having the highest similarity score Scj with the measurement data is selected 22-4, and comparison 22-5 with the selected group is performed.

  Thereafter, as in the normal analysis, the process proceeds to the next analysis content determination 9 based on the comparison result.

  As in this embodiment, when the reference data varies, similarity classification reduces variation, and comparison with the nearest data group is possible. Therefore, it is considered effective for increasing the accuracy of variation component determination. In addition, the classification content of each data group is known in advance such that the group classification of the reference data is, for example, a patient data group, a healthy person data group, a medicinal data group, or a non-human data group. In this case, by evaluating which group it is close to, in the real time of the measurement, or immediately after the measurement is finished, which group the measured sample belongs to (patient or healthy person, or Presence / absence) can be determined.

  Next, a fifth embodiment of the present invention will be described with reference to FIGS.

  FIG. 17 is a flowchart in the mass spectrometry system of the present embodiment. This flow differs from FIG. 1 in the process of comparison 24 with the grouped component group. Since these processes are the same as those in FIG. 1, the description thereof is omitted.

In comparison 24 steps the grouped component group, with respect to the detected peak (component) N _pi number, the mass number m and the characteristic information (the ion species of the peaks (components) i, of the mass spectrometer Derivation 24-1, LC retention time of retention time τ, detection intensity, area in mass chromatogram, etc. in liquid chromatography or gas chromatography when liquid chromatography or gas chromatography is installed in the previous stage Information acquisition 24-2 is performed, and derivation 24-3 of each component group to which each peak of the current measurement data belongs is executed. In the reference database 10, component groups are classified for each component in the reference data. A conceptual diagram of this classification is shown in FIG.

  In FIG. 18, grouping is performed on the acquired reference data (sample No. 1 to sample No. 4) as component groups A, B, and C based on the similarity to the behavior of fluctuation. That is, for each peak (component) of the sample, the similarity to the movement of the fluctuation is evaluated, and grouping is performed for each peak (component) group. Then, the representative value and the variance value are obtained for each group as in the first embodiment.

  FIG. 19 specifically shows the contents of the reference database 10 of FIG. The data is classified into component groups A, B,..., And representative values and variance values for each characteristic information of each component are stored as a result of statistical processing for each component included in each component group.

Using such a reference database 10, in FIG. 17, the measured values are compared with the grouped component groups of the reference database 10, and each component group to which each peak of the current measurement data belongs is derived 24-3, peak i. The derivation 24-4 of the difference between the component group representative values and the reference data component group representative value difference ΔX _i and the reference data variance value Δi of the peak i are compared 24-5. here,
When ΔX _i ≦ Δi, the process proceeds to the next normal analysis or measurement end 6, and when ΔX _i is larger than Δi, it is considered that there is a possibility of a fluctuation component, and thereafter, as in FIG. The processing flow is the next analysis content determination 9.

  Therefore, as in this embodiment, when the reference data varies, the variation is reduced by classifying the components based on the similarity of the fluctuation behavior, and the comparison with the nearest data group is possible. This is considered effective for improving the accuracy of judgment.

It is the schematic of the flow of the automatic determination process of a mass spectrometry flow by 1st Example of this invention. 1 is a schematic view of an entire mass spectrometry system according to the present invention. It is a conceptual diagram of the fluctuation | variation analysis in the mass spectrometry system which concerns on this invention. It is the content of the internal reference database held by the first embodiment of the present invention. It is a conceptual diagram of the comparison with the reference database by 1st Example of this invention. It is a conceptual diagram of the characteristic data extraction method of each component used as the origin of a reference database by 1st Example of this invention. It is a conceptual diagram of the characteristic data extraction method of each component detected from the present measurement data according to the first embodiment of the present invention. It is a conceptual diagram of the process of 1st Example of this invention. It is the schematic of the flow of the automatic determination process of a mass spectrometry flow by the 2nd Example of this invention. It is a conceptual diagram of the process of 2nd Example of invention. It is a conceptual diagram of the creation tool of the internal reference database of the third embodiment of the invention. It is the schematic of the flow of the automatic determination process of a mass spectrometry flow by the 3rd Example of this invention. It is the schematic of the flow of the automatic determination process of a mass spectrometry flow by 4th Example of this invention. It is a conceptual diagram of the group classification method of the reference data in 4th Example of this invention. It is a conceptual diagram of the group classification method of the reference data in 4th Example of this invention. It is the content of the reference database held internally by the 4th example of the present invention. It is the schematic of the flow of the automatic determination process of a mass spectrometry flow by 5th Example of this invention. It is a conceptual diagram of the group classification method of the reference data in the fifth embodiment of the present invention. It is the content of the reference database held internally by the 5th example of the present invention.

Explanation of symbols

1 Mass spectrometry data (MS ⁿ data)
2 Peak judgment (total number of peaks N _p )
3 Isotope peak determination (number of peaks without isotope N _pi )
4 Comparison with reference database 5 Select peak (component) i as precursor ion for MS ^{n + 1} analysis 6 Next normal analysis or measurement end 7 MS ^{n + 1} analysis condition setting 8 MS ^{n + 1} analysis 9 Next analysis Decision 10 Reference database (DB)
11 Pretreatment system 12 Ionization unit 13 Mass analysis unit 14 Ion detection unit 15 Data processing unit (CPU)
16 Display unit 17 Control unit 18 User input unit 19 Mass analysis system 20 MS ⁿ (n ≧ 2) is prohibited and MS ¹ analysis is determined 21 MS ¹ analysis 22 Comparison with grouped reference database 24 Grouped components Comparison with group 25 Automatic creation tool 40 Mass spectrometer 50 Control means

Claims (14)

A tandem mass spectrometer that dissociates the substance to be measured in multiple stages and measures the mass spectrum of the ion species generated in each dissociation stage;
A control means having a database storing characteristic information of a plurality of ion species, and a mass spectrometry system,
The control means is n (n is an integer of 1 or more) measured by the tandem mass spectrometer.
Based on the information of the measurement results of the stage and the information of the database, the measurement target and measurement conditions of the n + 1 stage of the tandem mass spectrometer are determined,
The ionic species characteristic information, <br/> saw including information subjected to statistical processing on the measured values of a plurality of samples,
The information subjected to the statistical processing is
A representative value that is one of an average value, a mode value, and a median value of the measured values of the plurality of samples;
And a standard deviation of the measured values of the plurality of samples,
The measured values of the plurality of samples have information on retention time in liquid chromatography or gas chromatography . The measured values of the plurality of samples are
Information on at least one of mass number of ion species, detection intensity, area in mass chromatogram
The mass spectrometry system according to claim 1 . The control means obtains the difference between the ion species information obtained from the n-th measurement result and the representative value of the corresponding ion species selected from the database,
If the difference value exceeds the standard deviation of the corresponding ion species selected from the database,
The mass spectrometry system according to claim 1 , wherein the ion species is an object to be measured at the (n + 1) th stage of the tandem mass spectrometer. The processing by the control means is
Performed within the preparation time for shifting to the n + 1 stage measurement,
The mass spectrometry system according to claim 1 , wherein the mass spectrometry system is performed within 10 msec. The control means has an automatic creation tool,
The mass spectrometry system according to claim 1, wherein the automatic creation tool automatically performs statistical processing on the acquired measurement values of the plurality of samples and stores the statistical values in the database. The database is
The mass spectrometry system according to claim 1, wherein measured values of a plurality of samples are classified into a plurality of groups by similarity evaluation. The information subjected to the statistical processing is
The mass spectrometry system according to claim 6 , including a representative value that is one of an average value, a mode value, and a median value of the measurement values for each group, and a standard deviation of the measurement values for each group. The mass spectrometry system according to claim 6 , wherein the group classification is performed by evaluating the similarity of profile tendency of measurement information of a plurality of samples. The mass spectrometry system according to claim 6 , wherein the group classification is performed by selecting one or more ion species and evaluating similarity of measurement information of the ion species. The control means includes
Selecting a group having the highest similarity to the measurement result information of the n-th stage from a plurality of groups in the database;
The mass spectrometry according to claim 6 , wherein the measurement target and measurement conditions of the (n + 1) th stage of the tandem mass spectrometer are determined based on a comparison between the information of the selected group and the information of the measurement result of the nth stage. system. The database is
The mass spectrometry system according to claim 1, wherein measured values of a plurality of ion species are classified into a plurality of groups by similarity evaluation. A tandem mass spectrometer that dissociates the substance to be measured in multiple stages and measures the mass spectrum of the ion species generated in each dissociation stage;
A control means having a database storing characteristic information of a plurality of ion species, and a mass spectrometry system,
The control means is n (n is an integer of 1 or more) measured by the tandem mass spectrometer.
Based on the information of the measurement result of the stage and the information of the database, it is determined whether to move the tandem mass spectrometer to the measurement of the n + 1 stage,
The ionic species characteristic information, <br/> saw including information subjected to statistical processing on the measured values of a plurality of samples,
The information subjected to the statistical processing is
A representative value that is one of an average value, a mode value, and a median value of the measured values of the plurality of samples;
And the standard deviation of the measured values of the plurality of samples,
The measured values of the plurality of samples have information on retention time in liquid chromatography or gas chromatography . The measured values of the plurality of samples are
The mass spectrometry system according to claim 12 , comprising at least information related to any one of a mass number of ion species, a detection intensity, and an area in a mass chromatogram . The control means obtains a difference between the ion species information obtained from the n-th measurement result and the representative value of the corresponding ion species selected from the database,
Until the value of the difference is less than or equal to the standard deviation of the corresponding ion species selected from the database,
The mass spectrometry system according to claim 12 , wherein the measurement of the nth stage is continued without shifting to the measurement of the (n + 1) th stage of the tandem mass spectrometer.

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