Quantification of substances present in a sample

Abstract

To quantify a substance present in a sample.SOLUTION: A sample is separated by a first separator into a constituent analyte over a time parameter. The constituent analyte is analyzed by a mass spectrometer. The mass spectrometer provides an intensity measurement value for a mass-to-charge ratio of each constituent analyte. A relation of intensity measured by the mass-to-charge ratio to a time parameter for each constituent analyte defines respective peak. A peak quality factor may be determined for each peak and / or a common peak position with respect to the time parameter may be determined for at least some of the peaks. A particular range of the time parameter used to quantify a substance may be based on the peak quality factor (or a plurality of peak quality factors).SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to quantifying substances present in a sample, where the sample is separated into constituent analytes by a first separator (e.g., a chromatographic separator or an ion mobility separator) over a time parameter, and the constituent analytes are then further analyzed by a mass spectrometer. This may be embodied in a method, a computer program, a controller for a mass spectrometry system, and / or a mass spectrometry system. [Background technology]

[0002] Software analysis of mass spectrometry data is becoming increasingly useful in identifying and quantifying substances present in a sample. Analysis of MS1 data is generally performed using MS n While analysis of data from data-independent acquisition (DIA) data is considered simpler than analysis of data from data-independent acquisition (DIA), analysis of DIA data can be more complex. Mass spectrometry may follow an initial separation step using, for example, a chromatographic separator, including gas chromatography-mass spectrometry (GC-MS) or liquid chromatography-mass spectrometry (LC-MS), or an ion mobility separator, commonly known as ion mobility spectrometry-mass spectrometry (IMS-MS). This only increases the complexity of the analytical workflow.

[0003] Traditionally, there are two main approaches to DIA data analysis. The first approach uses database-based search engines, which are commonly used to analyze data-dependent acquisition (DDA) data. The second option is targeted analysis, also known as SWATH-MS (Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectra). These data analysis algorithms primarily focus on sample identification, although quantification is also considered.

[0004] WO 2009 / 146345 discusses matching precursor ions with one or more related product ions. Data sets containing information about precursor ions are obtained from multiple injections and then normalized according to a single retention time. By determining which product ions are within a predetermined retention time window relative to the single retention time, the presence of such product ions allows their relationship to the precursor ion to be established.

[0005] WO 2012 / 035412 relates to the use of multiple product ions to characterize unknown sample compounds. Chromatographic peak retention times can be correlated across product ions to improve identification.

[0006] Typical existing approaches to quantification use a single raw data sample (or single event) basis. For example, "Reproducibility, Specificity, and Precision of Relative Quantification Using Spectral Library-Based Data-Independent Acquisition" by Barkovits, Katalin, et al. (Molecular & Cellular Proteomics 19.1 (2020): 181-197) discusses the selection of appropriate spectral libraries for peptide identification and quantification. Searle, Brian C., et al. (Generating High-Quality Libraries for DIA MS with Empirically Corrected Peptide Prediction) (Nature Communications 11.1 (2020): 1-10) describes library generation using empirical data such as fragmentation and retention time predictions. Demichev, Vadim, et al. (DIA-NN: Neural Networks and Interference Correction Enable Deep Proteome Coverage in High Throughput) (Nature Methods 17.1 (2020): 41-44) describes the removal of interfering product ions by selecting chromatographic product ion peaks that best correlate with their respective product ion partners. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] International Publication No. 2009 / 146345 [Patent Document 2] International Publication No. 2012 / 035412 Summary of the Invention [Problem to be solved by the invention]

[0008] Therefore, it is desirable to improve the analysis of mass spectrometry data to provide more accurate quantification of substances within a sample, particularly when the sample is first separated into its constituent analytes, each of which is then mass analyzed. [Means for solving the problem]

[0009] Against this background there are provided methods for quantifying substances present in a sample according to claims 1 and 9, a computer program according to claim 23, a controller for a mass spectrometry system according to claim 24 and a mass spectrometry system according to claim 25. Preferred and / or optional features are disclosed in the dependent claims.

[0010] The present disclosure relates to the quantification of substances present in a sample. The sample is separated into constituent analytes over a time parameter by a first separator. For example, the first separator may be a chromatographic separator (e.g., GC or LC). In this case, the sample is typically a liquid-phase or gas-phase sample. The time parameter is then related to retention time, and the constituent analytes are components separated from the chromatographic separator at different retention times. In another example, the first separator is an ion mobility separator. In this case, the sample is a mixture of sample ions. In this case, the time parameter is related to drift time or retention time, and the constituent analytes are the constituent ions of the mixture of sample ions.

[0011] Aspects according to the present disclosure may be embodied in software (optionally as a computer program that may be stored on a non-transitory computer-readable medium) in a controller for a mass spectrometry system and / or in the mass spectrometry system. Additionally or alternatively, these aspects may be implemented as a process.

[0012] In either case, the constituent analytes are further analyzed by a mass spectrometer (wherein the first separator is a chromatographic separator and each constituent analyte is first ionized). For example, analysis of the constituent analytes in a mass spectrometer may include processing the ions and mass analyzing the processed ions. In some cases, processing does not involve fragmentation (although it may involve mass filtering or selection and / or cooling), and mass analysis may be of the unfragmented ions. Alternatively, the ions may be precursor ions, and processing of the ions includes fragmenting the precursor ions to produce fragment ions, such that the fragment ions are mass analyzed. Mass analysis of the fragment ions is then performed using Data Independent Acquisition (DIA) MS analysis. n It may also include analysis.

[0013] Measurements of intensity versus mass-to-charge ratio are obtained from the mass spectrometer for each of one or more constituent analytes. Multiple such measurements are made over a time parameter. For each constituent analyte, the relationship of the measured intensity over the time parameter for a selected mass-to-charge ratio (or range of mass-to-charge ratios) defines a peak. Preferably, each peak includes at least a minimum number of intensity measurements, each for a different value of the time parameter (e.g., at least five measurements).

[0014] In some cases, the ions of the substance to be quantified have one of the selected mass-to-charge ratios, which may enable the disclosed techniques to be applied to MS1 full scan analysis, typically to the analysis of multiple ions within a single scan (rather than quantification of a single peak). More generally, each selected mass-to-charge ratio is associated with a respective fragment of the ions of the substance to be quantified. Quantification may include identifying the substance and / or identifying the chemical composition corresponding to one or more peaks (such that a selected mass-to-charge ratio or range of one or more peaks corresponds to the identified chemical composition).

[0015] In the first embodiment, there may be a single peak (i.e., only a single mass-to-charge ratio or range of data is provided over the time parameter), but more typically, multiple peaks are obtained. A peak quality is established for each peak, which is used to determine a specific range for the time parameter. The specific range determined for the time parameter can then be used to quantify the substance. It is particularly noted that the peak quality factor depends on the range of the time parameter used to establish the peak quality factor.

[0016] A flatness detection algorithm may also be used (eg, as one of the algorithms for determining the peak quality factor) to determine a particular range for the time parameter.

[0017] The specific range of the time parameter can be determined iteratively. For example, a first range of the time parameter can be used to establish a first peak quality factor for each peak. A second range of the time parameter is then identified, which can be narrower or wider than the first range of the time parameter. For example, the second range can be based on a predetermined increase or decrease from the first range of the time parameter (at one or both ends of the range). Optionally, the second range can be based on the first peak quality factor(s), for example, by comparison with a criterion(s), e.g., one or more thresholds. The identified second range of the time parameter can be used to establish a second peak quality factor for each peak. Thus, the specific range for the time parameter can be based on the first peak quality factor(s) and the second peak quality factor(s). This procedure can be continued until the peak quality factor(s) meet the criterion(s). For example, the range of the time parameter can be gradually widened until the criterion(s) is / are met.

[0018] The initially evaluated measurement of intensity versus mass-to-charge ratio may be for a first range of time parameters. If a second range of time parameters is broader than the first range, additional measurements of intensity versus mass-to-charge ratio may be evaluated for the constituent analyte(s). In this case, the initial and additional intensity measurements may both cover the second range of time parameters. Thus, the second peak quality factor(s) may be based on the initial and additional intensity measurements.

[0019] The substance is advantageously quantified based on the intensity measurements for each of one or more peaks that fall within the determined specific range. The determined specific range for the time parameter can be used not only for quantification of the measured sample, but also for quantification of the same substance from different samples. Alternatively, parallel evaluation of the specific range for the time parameter for each of multiple samples can be performed. In this case, the specific range for the time parameter can be established for the evaluated samples.

[0020] In a second aspect, a plurality of peaks of intensity measurements over a time parameter are obtained (each peak associated with a respective mass-to-charge ratio or range). A respective peak quality factor may be established for each peak (the peak quality factor being dependent on the range of the time parameter) and / or a common peak position may be determined with respect to the time parameter for at least some of the peaks. A subset of the peaks is then selected for substance quantification based on the determined peak quality factors and / or the determined common peak positions.

[0021] In one approach, the subset of peaks may be selected by evaluating the peak position of each of the peaks relative to the determined common peak position, for example, only peaks having peak positions within a predetermined amount of the determined common peak position may be selected for the subset.

[0022] In another approach (which may be used in conjunction with the approach described above), a subset of peaks may be selected by evaluating a respective peak quality factor for each of the peaks against a criterion (e.g., greater than a threshold, at least equal to a threshold, less than or equal to a threshold, or less than a threshold). The subset of peaks may then be selected based on whether the criterion is met for each peak (i.e., the selected peaks may be those that meet the criterion). Optionally, there may be multiple criteria.

[0023] Each of the selected subset of peaks can then be quantified. The substance can then be quantified based on the quantification of the selected subset of peaks.

[0024] The process according to the present disclosure does not require the use of peak intensity correlation between product ions, nor correlation with precursor mass.

[0025] It should be noted that multiple aspects of the present disclosure may be combined. According to any aspect, the mass spectrometer may be controlled to perform mass analysis of each of the constituent analytes and provide intensity measurements versus mass-to-charge ratio for each of the multiple components.

[0026] The present disclosure may be put into practice in many ways and preferred embodiments may be described below, by way of example only, and with reference to the accompanying drawings, in which: [Brief explanation of the drawings]

[0027] [Figure 1] 1 shows a schematic representation of a mass spectrometry system for use in accordance with the present disclosure. [Figure 2] FIG. 1 is a plot of measured intensity versus time peak for three exemplary mass-to-charge ratio ranges. [Figure 3] 1 shows a block diagram of a first procedure according to the present disclosure. [Figure 4] 1 shows a block diagram of a second procedure according to the present disclosure. [Figure 5a]10A-10C each show a plot of measured intensity versus time peak, illustrating the effect of a procedure according to the present disclosure. [Figure 5b] 10A-10C each show a plot of measured intensity versus time peak, illustrating the effect of a procedure according to the present disclosure. [Figure 5c] 10A-10C each show a plot of measured intensity versus time peak, illustrating the effect of a procedure according to the present disclosure. [Figure 5d] 10A-10C each show a plot of measured intensity versus time peak, illustrating the effect of a procedure according to the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0028] Referring initially to Figure 1, a mass spectrometry system for use in accordance with the present disclosure is depicted schematically. The mass spectrometry system 10 receives a sample 5 and comprises a first separator 20, a mass analyzer 30, and a controller 40. The mass analyzer 30 comprises at least one ion-optical device 32 (e.g., an ion guide, ion trap, and / or ion selector or filter), a collision cell 34, a mass analyzer 36, and a detector 38. Optionally, the mass analyzer 36 and detector 38 may be combined into a single device.

[0029] The first separator 20 separates the sample 5 into its constituent analytes. This separation occurs over time, with different constituent analytes being output from the first separator 20 at different times. Thus, there is a time parameter associated with the first separator 20, and each constituent analyte has a different corresponding value (or range) for the time parameter.

[0030] Preferably, the first separator 20 is a chromatographic separator, such as a gas chromatography (GC) or liquid chromatography (LC) device, such that the time parameter may be retention time (RT). The mass spectrometry system 10 may then be a GC-MS or LC-MS system. In such cases (and optionally when other types of separators are used), the mass spectrometer 30 advantageously further comprises an ion source 31 configured to receive the separated analytes (effluent or eluate) from the first separator 20 and to generate ions from the received separated analytes.

[0031] Alternatively, the first separator 20 may be an ion mobility spectrometer (IMS), such that the time parameter may be drift time (e.g., in the case of drift tube-type or traveling wave ion mobility separation) or retention time (e.g., in the case of trapped ion mobility separation (TIMS)). The mass spectrometry system 10 may then be an IMS-MS system. The first separator 20 may then include an ion source (not shown), in which case the output of the first separator 20 includes ions. Therefore, the mass spectrometer 30 does not need to include an ion source 31, and therefore, the ion source 31 is shown as optional in FIG. 1 .

[0032] The controller 40 is configured to control the operation of the first separator 20 and the mass analyzer 30. Additionally, the controller 40 receives mass spectral data from the detector 38. Optionally, the controller 40 may also receive data from the first separator 20. Thus, the controller may cause the mass analysis system 10 to perform an experiment and then receive the results of the experiment for analysis. The analysis may be performed by the controller or by an external processor or processing system (not shown). The controller 40 is typically a single device, but may comprise multiple components that typically operate together.

[0033] As described above, the method according to the present disclosure is a DIA MS n (typically MS 2) experiment. In this case (and when controlled by the controller 40), the mass spectrometry system 10 is operated to separate the sample 5 into one or more constituent analytes, each having an associated range of time parameters. Thus, a single constituent analyte may be output from the first separator 20 over a range of time parameters, thus resulting in multiple outputs of constituent analytes from the first separator 20. Each output of the constituent analytes with its associated time parameter is then provided to the mass spectrometer 30, fragmented in the collision cell 34, analyzed by the mass analyzer 36, and the mass spectral data detected by the detector 38. The mass spectral data is then communicated to the controller 40. Each mass analysis typically exhibits multiple fragments, each of which has a different mass-to-charge ratio (m / z) and a corresponding detection intensity. This is referred to as an MS n As a result, the controller 40 can generate multiple MS n Receive mass spectra and analyze each MS n The mass spectrum relates to one or more output constituent analytes (and therefore has associated time parameters) from the first separator 20. Typically, multiple MS n A mass spectrum is obtained for each single output component analyte. In other words, multiple MS n Mass spectra are obtained in the output for each constituent analyte.

[0034] Optionally, multiple MS1 mass spectra can also be obtained for each single output constituent analyte, ie, multiple MS1 mass spectra can be obtained between the outputs of each constituent analyte.

[0035] Quantification is typically performed by first performing an initial identification of the constituent analyte compound(s) using DIA identification tools on the mass spectrum. Each compound identification provides the time parameter points (e.g., retention time points) at which the compound was detected, and a list of the detected product (i.e., fragment) ions. This list may be exhaustive or may simply be a selection of the most intense or accurate detected product (fragment) ions.

[0036] Next, MS n Peak recovery from an analysis is possible by targeting specific m / z and time parameter values ​​of a set of product (fragment) ions. For example, intensities can be obtained for a set of product (fragment) ions at their specific m / z values ​​(optionally, subject to a user-defined or automatically estimated tolerance) relative to the time parameter determined by the DIA identification tool. The intensity for the same m / z value (again, optionally, subject to a user-defined or automatically estimated tolerance) can then be searched for spectra at adjacent values ​​of the time parameter. This search process can then be repeated until a minimum number min_s of spectra (typically, min_s=5) is reached. In this way, it is possible to correlate or match intensity measurements for the same fragment across the time parameter (based on m / z value or range).

[0037] This data may also be represented graphically. Referring to Figure 2, the measured intensity peaks are plotted against time for three exemplary fragments (each corresponding to a respective m / z range) from a DIA analysis. The first peak 61, corresponding to the first fragment, is relatively low (intensity approximately 3500) and has a peak position of approximately 31.58 on the time axis. The second peak 62, corresponding to the second fragment, is relatively high (intensity approximately 32000) and has a peak position of approximately 31.57 on the time axis. The third peak 63, corresponding to the third fragment, has an intermediate intensity (approximately 18000) and has a peak position of approximately 31.64 on the time axis. All three peaks are present in approximately the same range of retention times.

[0038] It is desirable to use information from these three peaks to quantify the substance from which the three fragments are likely derived. Quantification may be possible by summing the peak intensities of the identified product ions over a particular range of time parameters. The same range is beneficially used for all peaks. Identification refers to a relatively arbitrary point on the time parameter range (e.g., a particular time of compound elution), which may not be peak retention or may not represent a suitable range.

[0039] Referring again to FIG. 2 , a range 65 is shown selected from the time parameter of approximately 31.53 to approximately 31.62. Data points from the first peak 61, the second peak 62, and the third peak 63 that fall within the selected range 65 are highlighted. Therefore, it is desirable to improve the selection of the range 65. The second peak 62 begins slightly earlier than the first peak 61. The third peak 63 begins significantly later than the first peak 61 and the second peak 62. It can also be seen that the peak position of the third peak 63 is slightly different from the peak positions of the first peak 61 and the second peak 62 (i.e., the third peak 63 is offset relative to the other two). Therefore, it is unclear whether the fragment corresponding to the third peak 63 originates from the same substance (parent ion or precursor ion) as the fragments corresponding to the first peak 61 and the second peak 62.

[0040] It has been recognized that mathematical techniques can be used to address these issues. In particular, peak quality factor (PQF) algorithms can be used to objectively and quantitatively assess the quality of each peak over a selected range of time parameters. More typically, multiple PQF algorithms can be used, as discussed, for example, in "MetaClean: a machine learning-based classifier for reduced false positive peak detection in untargeted LC-MS metabolomics data," Chetnik et al., Metabolomics 16 (2020):1-13. Therefore, peak and substance quantification can be improved by selecting a range of time parameters that maximizes the results of the PQF algorithm.

[0041] Only data from a limited range of time parameters may be initially provided to the quantification algorithm. Thus, the algorithm can desirably retrieve ion product intensities from mass spectra at adjacent time parameter points. The PQF algorithm can also signal the direction (up and / or down with respect to the time parameter) in which to retrieve additional data and when to stop retrieval. This process may be performed simultaneously across all identifications of the same compound in all samples of an experiment, ensuring that the same set of product ions is used across all samples. This allows product ions to be discarded from all samples if the output of the PQF algorithm determines that the peaks for the product ions are not of sufficient (user-defined) quality in any of the samples. This also allows a fixed range (or at least width) of the time parameter to be defined for all samples, if desired by the user (i.e., the same width or range used for multiple samples).

[0042] Referring now to Figure 3, there is shown a block diagram of a first procedure according to the present disclosure. This procedure is specifically for selecting a range of time parameters for the purpose of substance quantification. In a first step 100, the mass spectrometer provides (or the controller retrieves from the mass spectrometer) data including intensity measurements versus mass-to-charge ratio for each of one or more constituent analytes. As discussed above, the relationship between the measured intensity at each selected mass-to-charge ratio and the time parameters for each constituent analyte defines a respective peak (as shown in Figure 2). Typically, the data is obtained from a DIA experiment and includes multiple MS 2 Spectra are acquired as a function of a time parameter, e.g., retention time (RT) in GC-MS or LC-MS. As a result, there are typically multiple peaks (each for a different m / z value or range), each corresponding to a specific fragment of one of the constituent analytes.

[0043] Advantageously, an optional identification step 105 is performed first. This uses a (known) identification algorithm to process the received data in order to determine the identity of the compounds in the data. Each identification may preferably include a list of m / z ratios of multiple (n) product or fragment ions of the identified parent ion. The known algorithm typically performs an MS 2 This allows for one (but usually only one) MS to be used. 2 The spectrum does not necessarily correspond to the apex of an intensity peak over time. Typically, the identification is performed by determining the MS peak at an arbitrarily chosen value of a time parameter, which can be called the base time t0. 2 This is done on the spectrum, and therefore the identified parent ion (and its corresponding original compound) is assumed to include all fragments identified at that value of the time parameter.

[0044] In the PQF step 110, one or more PQF algorithms are run on the retrieved data aggregated over a selected range of time parameters to determine a PQF result. The selected range desirably includes a minimum number of data points, typically at least five data points. To accomplish this, the selected range is typically set to include a base time t0. The two data points before the base time t0, i.e., t -1 and t -2 and two data points after reference time t0, i.e., data points at t1 and t2. Any peaks whose intensity is below a predetermined threshold for these first minimum number of data points (e.g., 5) are preferably discarded, since a minimum number of data points is generally required to evaluate peak characteristics for a fragment.

[0045] Next, in a verification step 120, the PQF results are compared to at least one PQF criterion. Thus, one or more PQF algorithms may determine whether each peak shape is sufficiently good or whether product ions do not produce good peaks for quantification. A flatness detector algorithm may form part of the PQF algorithm to determine when peak boundaries in either or both directions are reached. Thus, at least one PQF criterion may include determining whether a threshold minimum number min_peaks of sufficient quality (according to the PQF results) are available for quantification. This threshold may be user-defined or automatically defined. Another criterion may relate to optimizing (e.g., maximizing) the PQF results.

[0046] If at least one PQF criterion is not met, then the range modification path 124 is taken to the range modification step 130. In the range modification step 130, it is determined how to modify the selected range of the time parameter. For example, the selected range of the time parameter may be extended at one or both ends of the range (e.g., t-3 and / or t3), may be narrowed at one or both ends of the range, or expanded at one end and narrowed at the other. The use of multiple PQF algorithms may allow such a determination to be made. The selected range of the time parameter is updated accordingly. As noted above, a minimum number of data points are required to evaluate peak characteristics for a fragment. Thus, if a change in the selected range results in a fragment with insufficient data points above the threshold level to meet the minimum, the fragment is preferably ignored.

[0047] Based on the updated selection range of the time parameter, additional data may be retrieved. This is done in search step 135. It will be appreciated that this is not always required and therefore this step is optional (indicated by the dashed outline).

[0048] The process then continues by repeating PQF step 110, but now with the updated selected range of the time parameter. It will be appreciated that this loop may be repeated multiple times if at least one PQF criterion considered in verification step 120 is not met. It is anticipated that the selected range may be adjusted both forward and backward in time relative to the reference time t0.

[0049] If at least one PQF criterion considered in validation step 120 is met (e.g., the PQF result is optimized and / or any other criterion or criteria are met), quantification path 126 is taken. In quantification step 140, the material is quantified based on a selected range of the time parameter (as updated, if appropriate, in the immediately preceding range modification step 130). This may be achieved by summing the intensities of the remaining fragments between the boundaries defined by the updated selected time range.

[0050] The above approach focuses on determining the range of time parameters to be used in quantification. The fragments selected for inclusion in quantification are also taken into consideration. However, this is not the main focus of this approach. In another approach, preferably combined with the above approach, the main focus is which fragments to include in quantification.

[0051] Generally, a method for quantifying substances present in a sample is contemplated. The sample is separated into constituent analytes over a time parameter by a first separator. The constituent analytes are then further analyzed by a mass spectrometer. In practice, one constituent analyte may be provided (output) from the first separator over a range of time parameters (over a time range). Thus, the mass spectrometer may provide multiple mass spectra for each constituent analyte.

[0052] In one example, the sample comprises (or is) a liquid-phase or gas-phase sample. The first separator may then be a chromatographic separator, and the time parameter relates to retention time. In this case, the constituent analytes are components separated from the chromatographic separator at different retention times, and the constituent analytes are further analyzed by a mass spectrometer by ionizing each analyte to provide ions. The constituent analytes that are ionized to provide ions are then analyzed in the mass spectrometer by processing the ions, particularly by fragmentation, and by mass analyzing the processed (fragmented) ions.

[0053] Alternatively, the sample may include (or be) a mixture of sample ions, and the first separator may be an ion mobility separator. The time parameter may then relate to drift time or retention time, and the constituent analytes may be constituent ions of the mixture of sample ions. These may also be processed (e.g., by fragmentation), and the processed (fragmented) ions may then be mass analyzed.

[0054] In any event, each of the peaks typically corresponds to a DIA MS analysis of the constituent analytes. n (e.g., MS 2 ) may correspond to the respective fragment ions from the analysis.

[0055] In a method according to a first aspect, intensity measurements versus mass-to-charge ratios for each of one or more constituent analytes are received from a mass spectrometer. The relationship between the measured intensity at each of one or more selected mass-to-charge ratios and a time parameter for each constituent analyte defines a respective peak. In embodiments, the selected mass-to-charge ratio (which may be a range of mass-to-charge ratios) may be determined based on the fragments. A specific range for the time parameter used to quantify the substance is then determined based on a respective peak quality factor for each of the one or more peaks, where the peak quality factor depends on the range for the time parameter. Typically, multiple peak quality factors may be used, each of which may provide a statistical measure of the peak, for example, with respect to peak definition, symmetry, or other shape characteristics.

[0056] Preferably, a substance and / or chemical composition corresponding to at least one peak (typically each peak) is identified (after receiving the measurement data). In the latter case, a selected mass-to-charge ratio(s) of the at least one peak may correspond to the identified chemical composition. Identification of the peaks and / or substances may assist in determining the starting point and / or initial range of time parameters for each peak.

[0057] Advantageously, each peak comprises at least a predetermined number of intensity measurements, typically at least 5 intensity measurements (but optionally 7, 9 or 11). Peaks with fewer than the predetermined number of intensity measurements may be ignored.

[0058] Optionally, a particular range for the time parameter may be further determined using a flatness detection algorithm, which may allow a determination as to whether the full range of each peak is captured by the selected range for the time parameter.

[0059] In some implementations, determining the specific range for the time parameter includes establishing a respective first peak quality factor for each of the one or more peaks for a first range of the time parameter and establishing a respective second peak quality factor for each of the one or more peaks for a second range of the time parameter, where the second range of the time parameter is narrower or wider than the first range of the time parameter. A specific range for the time parameter used to quantify the substance can then be determined based on the one or more first peak quality factors and the one or more second peak quality factors. For example, a change between the one or more second peak quality factors and the one or more first peak quality factors can indicate whether the specific range for the time parameter should be the first range of the time parameter, the second range of the time parameter, lower than the first range of the time parameter, higher than the second range of the time parameter, or between the first range of the time parameter and the second range of the time parameter.

[0060] Advantageously, the second range of the time parameters may be selected based on one or more first peak quality factors (e.g., increasing the second range of the time parameters compared to the first range of the time parameters if the one or more first peak quality factors are too low) and / or based on a predetermined derivative (e.g., a stepwise increase or decrease of the second range of the time parameters compared to the first range of the time parameters).

[0061] Not all data necessary to determine one or more second peak quality factors is initially evaluated. For example, the received intensity measurements for the mass-to-charge ratio for each of the one or more constituent analytes may be initial intensity measurements for a first range of time parameters. Then, if the second range of time parameters is broader than the first range of time parameters, additional intensity measurements for the mass-to-charge ratio of the one or more constituent analytes may be evaluated. In this case, both the initial and additional intensity measurements may cover the second range of time parameters. Then, a respective second peak quality factor for each of the one or more peaks may be established based on the initial and additional intensity measurements.

[0062] In a preferred embodiment, the particular range for the time parameter is iteratively determined by repeating the step of establishing a respective second peak quality factor for each of the one or more peaks in relation to a second range of the time parameter, preferably with each second range of the time parameter being wider and wider (thus the range of the time parameter is iteratively increased until a peak quality factor is found that satisfies one or more set criteria).

[0063] The particular range for the time parameter may be determined by evaluating the respective peak quality factor for each of the one or more peaks against a criterion (or criteria). The particular range for the time parameter may be determined based on which criterion is met.

[0064] Preferably, the substance is quantified based on (summing up) intensity measurements for each of one or more peaks that fall within a determined specific range.

[0065] Optionally, the particular range determined for the time parameter may be used for quantification of the same substance from different samples.

[0066] Referring now to FIG. 4, there is shown a block diagram of a second procedure along these lines, specifically for determining which fragments should be included for purposes of substance quantification. In a first step 200, the mass spectrometer provides (or the controller retrieves from the mass spectrometer) data including intensity measurements versus mass-to-charge ratio for each of one or more constituent analytes. In this case, there will necessarily be multiple peaks (each for a different m / z value or range). This will typically involve identifying fragments (e.g., DIA MS) of one of the constituent analytes. 2 While this occurs when multiple peaks (of different origins) are considered, there may be other situations where multiple peaks are considered for the quantification of a substance.

[0067] Advantageously, an optional identification step 205 is performed first, which has been described above with reference to identification step 105 of Figure 3 and will not be repeated here for the sake of brevity. Based on the initial step 200, or on the optional identification step 205, an initial set of peaks is identified for quantification.

[0068] In evaluation step 210, an evaluation of the identified peaks for quantification is performed. There are two options for this evaluation. The first option is to run one or more PQF algorithms on the retrieved data aggregated over a range of time parameters. The second option is to determine a common peak location. This can be established by determining a statistical measure, for example, a mean, which can include the mean, median, or mode of the peak locations. Both options can be used together.

[0069] Next, in a verification step 220, the evaluation results are compared to at least one criterion. For example, the results of the PQF algorithm (or algorithms) for each peak can be compared to a threshold. Additionally or alternatively, the peak position of each of the peaks can be compared to a determined common peak position. The threshold can be predetermined for the distance between the peak position and the determined common peak position. For example, one of the peaks can be an interfering peak from another parent ion. Separation in the time parameter domain can be sufficient to recognize that the peak should be excluded from quantification.

[0070] If at least one criterion is not met, the peak reselection path 224 proceeds to a peak removal step 230. In the peak removal step 230, at least one peak from the peaks previously identified for quantification is selected to be ignored. This is typically determined based on the evaluation step 210. For example, if a peak does not meet a PQF-based criterion (threshold) and / or has a peak position that is at least a threshold (or more) away from a determined common peak position, then that peak is selected to be ignored from the set of peaks identified for quantification.

[0071] The process then continues by repeating evaluation step 210, but now using an updated set of identified peaks for quantification. It will be appreciated that this loop may be repeated multiple times if at least one criterion considered in validation step 220 is not met.

[0072] If at least one criterion considered in verification step 220 is met (e.g., all peaks have sufficient PQF and / or the peak positions of all peaks are equal to or less than a threshold from a determined common peak position), quantification path 226 is taken. In quantification step 240, the substance is quantified based on the set of peaks identified for quantification, which is updated during the process. This may be achieved, inter alia, by summing the intensities of fragments within the set of peaks identified for quantification between boundaries defined by a selected time range.

[0073] Advantageously, both processes can be performed simultaneously or sequentially, so that both a selected time range and a selected set of peaks can be determined for quantification purposes.

[0074] In either or both approaches, the results (selected time range and / or selected set of peaks) used for quantification of one sample can be beneficially used to quantitate the same substance in another sample. For example, this can be applied when multiple sample replicates are processed in multiple experimental runs. This can ensure consistent quantification between runs.

[0075] Returning to the general terms set forth above, another embodiment (which may be combined with any other embodiment disclosed herein) may be considered, which is a method for quantifying a substance present in a sample. The same considerations as above may apply to this embodiment.

[0076] In this method, intensity measurements versus mass-to-charge ratio for each of one or more constituent analytes are received from a mass spectrometer. The relationship of the time parameter of the analyte to the time parameter of the measured intensity at each of a plurality of selected mass-to-charge ratios defines a respective peak. In other words, peaks for a plurality of selected mass-to-charge ratios are received. For example, each of these may be (e.g., DIA MS nIn experiments, they may represent fragments from the same substance.

[0077] A respective peak quality factor may be determined for each of the peaks. The peak quality factor depends on the range of the time parameter. Preferably, multiple peak quality factors may be determined for each peak. Further details regarding optional aspects and / or implementations of peak quality factor determination are described above and apply here as well. Additionally or alternatively, a common peak position with respect to the time parameter is determined for at least some of the peaks. A subset of the peaks is then selected for substance quantification based on the determined peak quality factors and / or the determined common peak position.

[0078] In this way, the peaks selected for substance quantification are determined based on their characteristics, specifically peak quality and / or whether the peaks are aligned by a common (maximum) position. The common peak position may be determined statistically, for example, by averaging, weighted averaging, or a heuristic algorithm. Low-quality peaks and / or offset peaks may indicate interference, and ignoring such peaks in substance quantification may improve accuracy.

[0079] Optionally, selecting the subset of peaks may include evaluating a peak position of each of the peaks relative to the determined common peak position (e.g., determining an offset), and the subset of peaks is then advantageously selected based on the evaluation (e.g., by ignoring any peaks having peak positions that are at least a threshold away from the determined common peak position).

[0080] Advantageously, selecting the subset of peaks includes evaluating a respective peak quality factor (or multiple peak quality factors) for each of the peaks against a criterion (e.g., whether one or more thresholds are met or exceeded, e.g., each threshold may be applied to a respective peak quality factor). The subset of peaks may then be selected based on whether the criterion is met for each peak. There may be multiple criteria, each of which may be applied to a respective peak quality factor.

[0081] Each of the selected subset of peaks is preferably quantified (by summing the measured intensities over a selected range for the time parameter). The substance may then be quantified based on the quantification of the selected subset of peaks (e.g., summing them).

[0082] Preferably, the material and / or chemical composition corresponding to at least one peak (typically each peak) is identified (after receiving the measurement data), which may further assist in determining the set of peaks from which a subset should be selected.

[0083] As noted above, each peak advantageously comprises at least a predetermined number of intensity measurements, typically at least 5 intensity measurements (but optionally 7, 9, or 11). Peaks with fewer than the predetermined number of intensity measurements may be ignored.

[0084] Referring now to Figures 5a-5d, these respectively show plots of measured intensity versus time peak, illustrating the effect of different PQF algorithms as the time range of those algorithms is changed. These use the same data shown in Figure 2, with three peaks, as described above. Three exemplary PQF algorithms are used: ZigZagId (smaller numbers are considered better); Symmetry (-1 is optimal, closer to this value is better); and trigPeakSim (1 is optimal, closer to this value is better).

[0085] A brief description of these exemplary PQF algorithms is provided here for completeness (more complete details are detailed in "MetaClean: a machine learning-based classifier for reduced false positive peak detection in untargeted LC-MS metabolomics data," Chetnik et al., supra). ZigZagId is the Zig-Zag. The Zig-Zag Index (ZZ) captures shape quality by measuring the normalized variance between a point and its immediate neighbors on either side. The normalized average of all Zig-Zag Index values ​​(Zig-Zag Index values ​​can be calculated for all points in a peak except for the two extremes) is the value used as the quality factor for the peak. Here, ZZ is the Zig-Zag Index of the peak, and I n is the nth intensity measurement, there are N measurements in the peak. ZZ1=ZZ2 ZZ1=sum((2I n -I n-1 -I n+1 ) 2 ), n=2 to n=n-1. ZZ2=N*EPI 2 and EPI=I A -avg(I1+I2+I N-1 +I N ) where I A is the maximum intensity value.

[0086] Symmetry (SY) measures the correlation between the left and right halves of a peak, which can be expressed mathematically as: SY=cor([I1,...,IN / 2],[IN / 2,...,IN]), range:[-1,1].

[0087] TrigPeakSim (TPASR) is the abbreviation for Triangular Peak Area Symmetry or Similarity Ratio. This peak quality factor estimates shape quality by comparing the peak area to the area of ​​the triangle formed by the vertices and boundary. It can be expressed mathematically as: TPASR=abs(triangle_area−AUC) / max(triangle_area,AUC), where AUC is the area under the curve of the peak (or simply the peak area).

[0088] In Figure 5a, five data points are selected for highlighting; in Figure 5b, the time range is extended to seven data points; Figure 5c uses nine data points; and Figure 5d selects eleven data points. For both the first peak (with the lowest peak intensity) and the second peak (with the highest peak intensity), the ZigZagId and trigPeakSim values ​​can be seen to decrease as the number of data points increases. The Symmetry values ​​for the first and second peaks change, but not significantly. For the third peak (with an intermediate peak intensity and a slightly shifted peak position compared to the other two peaks), the ZigZagId value decreases as the number of data points increases. However, the Symmetry value remains inconsistent until the number of data points reaches eleven. In contrast, the trigPeakSim value appears to be optimal when the number of data points is five, seven, or nine, but decreases when the number of data points reaches eleven.

[0089] It will therefore be appreciated that a combination of PQF algorithms may be beneficially used to evaluate peaks and determine the number of data points (selected range of time parameters).

[0090] Returning to the general terms set forth above (in any embodiment), it can be understood that the mass spectrometer can be controlled to perform mass analysis of each of the constituent analytes and provide intensity measurements versus mass-to-charge ratio for each of the plurality of components.

[0091] Aspects according to the present disclosure may be embodied as a computer program (optionally on a computer-readable medium, which may be non-transitory), as a controller (in hardware and / or software) for a mass spectrometry system, or as a mass spectrometry system comprising such a controller. It will be understood that such a mass spectrometry system may further comprise a first separator configured to separate the sample into constituent analytes over a time parameter, and a mass spectrometer configured to receive and analyze the constituent analytes.

[0092] A process, method, or implementation according to the present disclosure may consume minimal RAM memory because the minimum number of intensities that may be necessary or desired to have reliable quantification is retrieved. Such a process may be performed simultaneously on multiple samples. This may allow for consistency of the product ion set utilized for quantification and control of similar peak boundaries for all samples.

[0093] Separating DIA identification and DIA quantification can enable a second validation step, improving quantification and even discarding unreliable compound quantification (if all product ions from the common set of product ions in a sample fail to produce any reliable peaks). It can also provide more consistent quantification, since it can be used. Furthermore, if any product ion fails to produce a reliable peak, the product ion can be removed from the common product ion set for all samples. Separating identification from quantification can, in particular, provide an opportunity to evaluate the best and most common product ion set for each identified compound across all samples involved.

[0094] Although embodiments according to the present disclosure have been described with reference to particular types of devices and applications (particularly mass spectrometers), and the embodiments have particular advantages in such cases, as discussed herein, the approaches according to the present disclosure may be applied to other types of devices and / or applications. In particular, devices according to the present disclosure may be used in other applications. Specific structural, arrangement, and operational details (e.g., parameters) of processes, while potentially advantageous (especially in view of known configurations and capabilities), may be significantly modified to arrive at operational modes with similar or identical performance. Other types of separations may be contemplated from those disclosed herein. Certain features may be omitted or substituted, for example, as shown herein. Each feature disclosed herein may be replaced by an alternative feature serving the same, equivalent, or similar purpose, unless otherwise specified. Thus, unless otherwise specified, each disclosed feature is merely an example of a generic series of equivalent or similar features.

[0095] It has been suggested above that a retention time range (or equivalently, a drift or other suitable time range) may be determined based on measurements of one sample and then used for another sample, particularly when multiple sample replicates are processed in multiple experimental runs. Alternative approaches are possible. For example, parallel evaluation of retention time ranges may be performed for all (or at least multiple) samples. This may allow a consensus (which may be a common or statistically determined, e.g., average or weighted average) retention time range for the evaluated samples to be determined. When parallel analysis of multiple samples is used, peaks with fewer than a predetermined number of intensity measurements need not be ignored but may be integrated into the quantification measurements. The determined time range may then be used for quantification of all samples (possibly including other samples not used to determine the range).

[0096] A variation of the above method is to apply the same algorithm to a full MS1 scan and search only for the expected (precursor) mass for each identified compound. In this case, the term fragment used above may be replaced by the identified compound, and the process may be used similarly.

[0097] In the general terms mentioned above, the ions of the substance to be quantified can optionally be considered to have one of the selected mass-to-charge ratios, and quantification of the peaks can then correspond to quantification of the substance.

[0098] In this detailed description of various embodiments, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the disclosed embodiments. However, those skilled in the art will understand that these various embodiments may be practiced without or with these specific details. Furthermore, those skilled in the art will readily understand that the specific order in which the methods are presented and performed is illustrative, and it is contemplated that the order may be changed and still remain within the scope of the various embodiments disclosed herein.

[0099] As used herein, including in the claims, singular forms of terms herein are construed to include plural forms, and vice versa, unless the context indicates otherwise. For example, in the claims, references to singular forms, including "a" or "an" (e.g., an ion multipole device), mean "one or more" (e.g., one or more ion multipole devices), unless the context indicates otherwise. Throughout the specification and claims of this disclosure, words such as "comprise," "including," "having," and "contain," as well as variations of words such as "comprising" and "comprises," or the like, mean "including, but not limited to," and are not intended to exclude other elements. Additionally, the use of "or" is inclusive, so that the phrase "A or B" applies when "A" is true, when "B" is true, or when both "A" and "B" are true.

[0100] The use of any and all examples or exemplary language (such as "for instance," "such as," "for example," and similar language) provided herein is intended merely to better illustrate the invention and does not pose a limitation on the scope of the disclosure unless specifically claimed. No language in the specification should be construed as indicating any element not claimed as essential to the practice of the disclosure.

[0101] The terms "first" and "second" may be reversed without changing the scope of the invention. That is, an element referred to as a "first" element may instead be referred to as a "second" element, and an element referred to as a "second" element may instead be considered a "first" element.

[0102] Any steps described herein may be performed in any order, or simultaneously, unless otherwise stated or otherwise required by context. Furthermore, if a step is described as being performed after another step, this does not exclude intervening steps from being performed.

[0103] Furthermore, unless otherwise understood or stated, implicitly or explicitly, it is understood that for any given component or embodiment described herein, any of the possible candidates or alternatives listed for that component may be used generally, either individually or in combination with one another. Furthermore, unless otherwise understood or stated, implicitly or explicitly, it is understood that any listing of such candidates or alternatives is merely exemplary and not limiting.

[0104] All literature and similar materials cited in this application, including but not limited to patents, patent applications, articles, books, papers, and Internet web pages, are expressly incorporated by reference in their entirety for any purpose. Unless otherwise defined, all technical and scientific terms used herein have the meaning commonly understood by one of ordinary skill in the art to which the various embodiments described herein belong.

Claims

1. 1. A method for quantifying a substance present in a sample, wherein the sample is separated into constituent analytes by a first separator over a time parameter, and the constituent analytes are then further analyzed by a mass spectrometer, the method comprising: receiving from the mass spectrometer intensity measurements versus mass-to-charge ratio for each of one or more constituent analytes, wherein the relationship of the intensity measurements at each of one or more selected mass-to-charge ratios over the time parameter for each constituent analyte defines a respective peak; determining a particular range for the time parameter to be used to quantify the substance based on a respective peak quality factor for each of the one or more peaks, the peak quality factor being dependent on the range for the time parameter; A method comprising:

2. The method of claim 1 , wherein the particular range of the time parameter is further determined using a flatness detection algorithm.

3. The step of determining the particular range for the time parameter comprises: establishing a respective first peak quality factor for each of the one or more peaks for a first range of the time parameter; establishing a respective second peak quality factor for each of the one or more peaks for a second range of the time parameter, the second range of the time parameter being narrower or wider than the first range of the time parameter; Including, 2. The method of claim 1, wherein the particular range of the time parameter used to quantify the substance is determined based on the one or more first peak quality factors and the one or more second peak quality factors.

4. The method of claim 3 , wherein the second range of the time parameter is selected based on the one or more first peak quality factors and / or a predetermined derivative.

5. the intensity measurements for mass to charge ratio for each of the one or more constituent analytes are initial intensity measurements for the first range of the time parameter, the second range of the time parameter being greater than the first range of the time parameter, and the method further comprising: receiving additional intensity measurements for the mass-to-charge ratios of the one or more constituent analytes, the initial intensity measurements and the additional intensity measurements together covering the second range of the time parameter; The method of claim 3 , wherein the respective second peak quality factor for each of the one or more peaks is established based on the initial intensity measurement and the additional intensity measurement.

6. 4. The method of claim 3, wherein the particular range of the time parameter is determined iteratively by repeating the step of establishing a respective second peak quality factor for each of the one or more peaks for second ranges of the time parameter, each second range of the time parameter being increasingly wider.

7. using said determined specific range for said time parameter for the quantification of the same substance from different samples; and / or quantifying the substance based on the intensity measurements for each of the one or more peaks that fall within the determined particular range; The method of claim 1 further comprising:

8. determining the particular range for the time parameter, evaluating the respective peak quality factor for each of the one or more peaks against a criterion, the particular range for the time parameter being determined based on the criterion being met; and The method of claim 1 , comprising:

9. 1. A method for quantifying a substance present in a sample, wherein the sample is separated into constituent analytes by a first separator over a time parameter, and the constituent analytes are then further analyzed by a mass spectrometer, the method comprising: receiving from the mass spectrometer intensity measurements versus mass-to-charge ratio for each of one or more constituent analytes, wherein the relationship of the intensity measurements at each of a plurality of selected mass-to-charge ratios over the time parameter for each constituent analyte defines a respective peak; determining a respective peak quality factor for each of said peaks, said peak quality factor being dependent on a range for said time parameter; and / or determining a common peak position with respect to said time parameter for at least some of said peaks. selecting a subset of the peaks for quantification of the substance based on the determined peak quality factors and / or the determined common peak positions; A method comprising:

10. The step of selecting the subset of peaks comprises:

10. The method of claim 9, comprising: evaluating a peak position for each of the peaks against the determined common peak position, wherein the subset of peaks is selected based on said evaluating.

11. The step of selecting the subset of peaks comprises: and evaluating the respective peak quality factor for each of the peaks against a criterion, wherein the subset of peaks is selected based on whether the criterion is met for each peak.

12. quantitating each of the selected subset of peaks; quantitating the substance based on the quantification of the selected subset of peaks; 10. The method of claim 9, comprising:

13. The method of claim 9 further comprising the method of claim 1.

14. 10. The method of claim 1 or 9, wherein the ions of the substance to be quantified have one of the selected mass to charge ratios.

15. 10. The method of claim 1 or 9, wherein the constituent analytes are analyzed by processing the ions as ions in the mass spectrometer and mass analyzing the processed ions.

16. 16. The method of claim 15, wherein the sample is a liquid phase sample or a gas phase sample, the first separator is a chromatographic separator, the time parameter relates to retention time, the constituent analytes are components separated from the chromatographic separator at different retention times, and the constituent analytes are further analyzed by the mass spectrometer by ionizing each analyte to provide the ions.

17. 16. The method of claim 15, wherein the sample is a mixture of sample ions, the first separator is an ion mobility separator, the time parameter is related to drift time or retention time, and the constituent analytes are constituent ions of the mixture of sample ions.

18. 16. The method of claim 15, wherein the ions are precursor ions, and the processing of the ions comprises fragmenting the precursor ions to produce fragment ions, and the fragment ions are mass analyzed.

19. Each of the peaks is analyzed by data independent acquisition (DIA) MS analysis of the constituent analytes. n 20. The method of claim 18, corresponding to each fragment ion from the analysis.

20. identifying the substance, and / or identifying a chemical composition corresponding to at least one peak, wherein the selected one or more mass-to-charge ratios of the at least one peak correspond to the identified chemical composition; 10. The method of claim 1 or 9, further comprising:

21. The method of claim 1 or 9, wherein each peak comprises at least a predetermined number of intensity measurements.

22. controlling the mass spectrometer to perform mass analysis of each of the constituent analytes and to provide intensity measurements of mass to charge ratio for each of the one or more constituent analytes; 10. The method of claim 1 or 9, further comprising:

23. A computer program adapted to perform the method according to claim 1 or 9 when run by a processor.

24. A controller for a mass spectrometer system, the controller being configured to control the mass spectrometer system to perform the method of claim 1 or 9.

25. 1. A mass spectrometer system comprising: a first separator configured to separate the sample into constituent analytes over a time parameter; a mass spectrometer configured to receive and analyze the constituent analytes; A controller according to claim 24; 1. A mass spectrometer system comprising:

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