Real-time chromatographic data filter for scanning with non-uniform data intervals

Abstract

The invention relates to a real-time chromatographic data filter for scanning with non-uniform data intervals. Systems and methods taught herein enable improved filtering of chromatographic data acquired during a series of scans having non-uniform data sampling intervals (also referred to herein as "scan durations") by using a chromatographic data filter, the chromatographic data filter operates on a shorter time base than any data sampling interval in the series of scans. By employing filters with such time bases, the systems and methods taught herein improve the signal-to-noise ratio (S / N) of the resulting data, and improve the quality of chromatograms in mass spectrum real-time signal processing, resulting in clearer signals, reduced baseline noise, and smoother peaks in the chromatographic data.

Description

[0001] Cross-references to related applications

[0002] This application claims the benefit of priority to U.S. Provisional Patent Application No. 63 / 654,877, filed May 31, 2024, the entire contents of which are incorporated herein by reference. Background Technology

[0003] One way to improve the sensitivity of liquid chromatography-mass spectrometry (LC-MS) scans is to reduce the noise level in the chromatogram. Since noise is inherently high-frequency (compared to chromatographic peaks), it can be removed from the chromatographic distribution through frequency correlation filtering. Summary of the Invention

[0004] In one aspect, this document teaches a method for processing data obtained from scans having non-uniform data sampling intervals to form a chromatogram. The method includes obtaining multiple data points corresponding to multiple scans during sample elution from an injection system. Each scan in the multiple scans occurs within a corresponding data sampling interval. The method further includes applying a chromatographic data filter to at least some of the multiple data points. The filter includes a time base, and the time base is smaller than any of the corresponding data sampling intervals. This document also teaches a non-transitory computer-readable medium containing instructions for causing a computer to perform the method.

[0005] In one aspect, this paper teaches a method for processing data obtained from scans having non-uniform data sampling intervals to form a chromatogram. The method includes acquiring multiple data points corresponding to multiple scans during sample elution from an injection system. Each scan in the multiple scans occurs within a corresponding data sampling interval. The method also includes measuring at least one corresponding data sampling interval. The method further includes dividing the at least one corresponding data sampling interval by an interpolation factor to determine a time base for a chromatographic data filter. The method also includes calculating filter coefficients of the chromatographic data filter based on the time base. The method further includes applying the chromatographic data filter to at least some of the multiple data points. This paper also teaches a non-transitory computer-readable medium containing instructions for causing a computer to perform the method. Attached Figure Description

[0006] The accompanying drawings illustrate various embodiments and are part of the specification. The illustrated embodiments are merely examples and do not limit the scope of this disclosure. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. To facilitate identification of any particular element or action being discussed, one or more of the largest significant digits in the reference numerals refer to the drawing number in which the element is first introduced.

[0007] Figure 1 Examples of conventional filters and filters as taught in this paper are illustrated for the application of experimental data obtained during sample entry into the mass spectrometer.

[0008] Figure 2 An exemplary chromatographic data filter is illustrated using a network formula, which transforms raw chromatographic data into filtered chromatographic data.

[0009] Figure 3A Two graphs are shown, illustrating raw data from different m / z ranges within the same time span from scans separated by non-uniform data sampling intervals.

[0010] Figure 3B An example is given of data obtained using a conventional static filter with a non-uniform data sampling interval. Figure 3A The original data.

[0011] Figure 3C An example is illustrated using a chromatographic data filter applied according to the examples taught herein, with a non-uniform data sampling interval. Figure 3A The original data.

[0012] Figure 4 Examples of time shifts between the original peak and the filtered peak are shown in some implementations of the chromatographic data filters taught in this paper.

[0013] Figure 5 An exemplary method for processing data obtained from scans with non-uniform data sampling intervals to form a chromatogram is illustrated.

[0014] Figure 6 Additional exemplary methods are illustrated for processing data obtained from scans with non-uniform data sampling intervals to form chromatograms.

[0015] Figure 7 Examples of computing devices suitable for controlling a mass spectrometer and for executing computer-readable instructions to perform the methods described herein are illustrated. Detailed Implementation

[0016] The systems and methods taught in this paper enable improved filtering of chromatographic data acquired over a series of scans with non-uniform data sampling intervals (sometimes referred to herein as “scan duration”) by using a chromatographic data filter that operates on a time base shorter than any data sampling interval in the series of scans. Conventionally, mass spectrometer data acquisition systems use low-pass filters to reduce or eliminate high-frequency noise and enhance the signal for the chromatograph. Conventional chromatographic data filters operate on a time base equal to the uniform data sampling interval. When such conventional chromatographic data filters are used to filter data acquired at varying (e.g., non-uniform) data sampling intervals, the filter response can introduce irregularities, making the resulting data unstable and unpredictable. The systems and methods taught in this paper employ chromatographic data filters that operate on a time base shorter than the shortest data sampling interval in a given series of scans. By employing filters with such short time bases, the systems and methods taught in this paper improve the signal-to-noise ratio (S / N) of the resulting data and enhance the quality of chromatograms in real-time mass spectrometry signal processing, thereby producing clearer signals, reduced baseline noise, smoother peaks, and significantly improved stability in the chromatographic data compared to the same data processed using conventional static filters.

[0017] Filtering can be performed in real time during chromatogram acquisition, based on initial parameters provided by the user or on the determination of initial conditions during the initial acquisition of chromatographic data.

[0018] Figure 1 Examples of conventional filters and filters as taught herein are illustrated for the application of experimental data obtained during the elution of a sample from the injection system and into the mass spectrometer. Examples of injection systems compatible with the systems and methods of the present invention include chromatographic columns, batch injection systems, direct probe injection, or electrophoretic capillary injection systems. The introduction of a sample into the mass spectrometer is illustrated by an elution peak 114 having a peak width of 112. Multiple scans can be performed during the peak width 112 of the elution peak 114, each requiring a specified time to perform. As used herein, a “data sampling interval” is the time between receiving data from adjacent scans of the same scan type within the experimental method. Conventionally, a series of scans 116 (e.g., MS1 scans) are performed with a periodic data interval 108 (i.e., data is obtained from scans at regular intervals) that does not change during the time it takes to elute the analyte in the elution peak 114 into the mass spectrometer. The data obtained from a series of scans are filtered using a conventional static chromatographic filter having a constant time base 104 matched to the periodic data interval 108 of the scans.

[0019] With technological advancements, new experimental methods and scheduling strategies have been introduced that allow for non-uniform (i.e., non-periodic, random, or irregular) data sampling intervals. Users can define data acquisition methods using, for example, a method editor for mass spectrometers. A particular method may include multiple scans, each with a corresponding scan type (e.g., scans within a method can all be of the same type or different types) and a schedule (e.g., a user-defined time window). Different types or the same type of scan may require different amounts of time to complete, depending on the objective of the scan. For example, some scans may cover a wider range of m / z values ​​and therefore may take longer to complete than a target scan within a narrow m / z window. Other scans may employ automatic gain control, where the ion accumulation time before the scan is completed is different for different target ions. Additionally, different scan types can be mixed on a single elution peak, and each of these different scan types may have different associated times to complete the scan and provide output data. Furthermore, the schedules of different scans may overlap, so the sampling rate for a particular scan type may be non-uniform or inconsistent between scans. The chromatographic data filter taught in this paper operates on a time base of 106, which is shorter than the shortest data sampling interval in the scan sequence, to ensure that data from each scan is correctly sampled and correctly incorporated into the filter.

[0020] In various examples, scans that generate chromatographic data capable of being processed using the chromatographic data filters taught herein may include full-scan MS1 ​​data acquisition (mixed or quantitative), adaptive gain control (AGC), selective reaction monitoring (SRM), selected ion monitoring (SIM), tandem mass analysis (such as MS2, MS3, up to MSn), data-independent acquisition (DIA), product ion scanning, neutral loss scanning, data-correlated acquisition (DDA) including full-scan, adaptive retention time (RT) methods, or any combination of these scan types within one method. In some examples, the chromatographic data filter applied to data obtained using one scan type may be different from the chromatographic data filter applied to data obtained using different scan types (e.g., it may be user-specified as different). In some embodiments, data obtained at data sampling interval 110 may include, for example, peak intensities of one or more specific analytes or all measured analytes at a given value of m / z measured during the scan. These data may be acquired from multiple scans over time and assembled into a chromatogram (e.g., abundance or intensity measured over time by detector response).

[0021] For example, Figure 1Examples of time points for a series of overlapping scans are illustrated, including automatic gain control (AGC) scans 118, data correlation (DD) scans 120, and multi-experiment scans 122. In an AGC scan, the mass spectrometer can adjust experimental conditions based on feedback, for example, from the detector, to increase or decrease the number of ions obtained within a given m / z range. This can be achieved, for example, by applying various injection times based on signal intensity. Therefore, the data sampling interval 110 for scans in a series of AGC scans 118 can be varied from a relatively long time between scans to a shorter time. Similarly, Figure 1 A series of data correlation scans, also known as DD scans 120, are illustrated. In data correlation scans, a mixture of full-spectrum scans and target m / z scans can be performed, where different scans can be performed using different data sampling intervals 110, depending on the signal strength. Finally, Figure 1 An example of a multi-experiment scan sequence 122 is illustrated, in which a mixture of different scan types is used. In some cases, scans in the multi-experiment scan 122 can overlap in time. For example, one scan type can be interrupted to perform a different scan type, thereby obtaining data. Then, for the remainder of the planned time period, the experiment resumes to the initial scan type. In some multi-experiment scans 122, scans can be added or expired (removed) throughout the elution time according to a predefined window. Different scan types can return data at different rates within a single scan type or when different scan experiments are completed.

[0022] On a scan sequence with varying data sampling intervals 110, conventional filters using a constant time base 104 matched to a static or initial periodic data interval 108 will produce unreliable and unpredictable results. The chromatographic data filter taught herein can use a time base 106 shorter than the shortest data sampling interval 110 in the scan sequence. For example, a graphical representation of time base 106 illustrates that the filter samples data at a rate (i.e., closer time points due to the smaller time base) faster than the fastest scan acquisition or sampling rate (i.e., the closest data sampling interval 110) of any of the AGC scan 118, DD scan 120, or multi-experiment scan 122. Chromatographic data filters advantageously reduce baseline noise, produce smoother peaks, improve repeatability (e.g., avoid shifts or peak shape changes during repeated scans), and enhance signal clarity in these scans.

[0023] In some examples, time base 106 operates by applying interpolation to ensure adequate sampling of the filter. Time base 106 can be a fine, constant time interval, which improves the stability and performance of the filter. In other embodiments, time base 106 can vary over the time period of elution peak 114. For example, in response to a real-time modification of the method to introduce a new, faster scan type, the time base 106 of the chromatographic data filter can be reduced to keep it smaller than the minimum data sampling interval 110 in the modified experiment.

[0024] As shown below Figure 6 In more detail, the chromatographic data filter can be initialized with input parameters derived from the user, stored in memory, or derived in real time based on the analysis of raw data generated by the mass spectrometer. In some examples, the time base 106 is determined in real time by analyzing data from the mass spectrometer. For example, a computing device communicating with the mass spectrometer can receive two raw data points from two scans. The computing device can determine the time difference between receiving these two data points, corresponding to the data sampling interval 110 of the first scan. The computing device can then divide the determined data sampling interval 110 by an interpolation factor (e.g., an integer) to determine the time base 106. The interpolation factor can be selected as a balancing factor. For example, a larger interpolation factor divides the data sampling interval 110 into smaller segments and increases the smoothness of the resulting filter. However, computational overhead increases. In various examples, the interpolation factor is in the range of 2 to 20, in the range of 2 to 10, or an integer equal to five. In some examples, the interpolation factor is not an integer and can take values ​​such as 1.5. In some examples, the interpolation factor is in the range of 1.5 to 1000, 1.5 to 500, 1.5 to 100, or 1.5 to 50.

[0025] In some implementations, the time base 106 determined from the initial scan in a series of scans can be applied to a chromatographic data filter for all scans of a given elution peak 114. However, some sequences of multiple experimental scans 122 may include dynamic additions or expirations of scans, which could reduce the data sampling interval 110 to a level comparable to the existing time base 106 initially determined by measuring the initial scan. In some examples, the computational system can monitor the data sampling interval 110 and take action to adjust future data sampling intervals 110 to be longer and / or adjust the time base 106 to be shorter, such that the time base 106 does not become larger than the dynamically updated data sampling interval 110 during a series of scans.

[0026] In some examples, a complete series of scans and associated data sampling intervals 110 are specified (e.g., in a method editor) before the analyte begins elution into the mass spectrometer. For example, the specified scans may be stored in a list or database. As an alternative to or supplement to the real-time measurement of the data sampling intervals 110 as described above, in some examples, a computing device configured to perform a chromatographic data filter can review the specified scans to determine or predict the shortest data sampling interval 110 in the scan series. The computing device can then determine the time base 106 of the chromatographic data filter by dividing the shortest data sampling interval 110 by an interpolation factor (e.g., an integer) as described above.

[0027] By increasing the sampling rate of the chromatographic data filter (i.e., increasing the interpolation factor or decreasing the time base 106), additional data operations will be performed per unit time. As the time base 106 decreases, peak shape may improve, but computational overhead may increase. Therefore, when determining the appropriate time base 106 for the filter, some specific implementations of the chromatographic data filter may take into account available computational resources (i.e., processing power, available memory, and / or input / output speed). In some examples, the computing device may select the time base 106 to balance data quality and available computational resources.

[0028] When applied to data obtained from scans with non-uniform data sampling intervals, the chromatographic data filter taught in this paper can outperform conventional data filters operating at a constant time base of 10⁴ for several reasons.

[0029] Non-constant scan duration: In mass spectrometry, scans with non-constant scan durations exist. For example, in scans involving automatic gain control (AGC) or data correlation (DD) scans, the scan time varies based on the signal strength. Similarly, multiple scan events with scan windows or overlapping scans in a method can lead to varying scan durations. Classical IIR filters that rely on a constant time base may not effectively handle these variations.

[0030] Irregularities in filter response: Conventional filters assume a constant time interval between two sampled data points. When the time intervals between samples are inconsistent, it can introduce irregularities into the filter response. This can lead to unstable or unpredictable behavior, resulting in suboptimal noise reduction and signal smoothing.

[0031] Limited adaptability: Conventional filters have limited adaptability in handling dynamic changes in data. In mass spectrometry, filters may not be able to effectively adapt to changing conditions where signal characteristics can change significantly, leading to performance degradation.

[0032] The chromatographic data filter taught in this paper addresses some of these problems by applying interpolation during sampling to inform the filter parameters of the chromatographic data filter. By doing so, the chromatographic data filter can utilize a fine time base, even in the presence of non-constant or non-uniform scan durations. Using a fine time base for interpolation improves the stability and performance of the filter, allowing it to efficiently handle mass spectrometry scans with varying time intervals between data points while maintaining filter strength.

[0033] The preceding text has already taught an example of using chromatographic data filters to filter raw data in real time (i.e., filtering data from scans within a series of scans while still performing additional scans within the series). However, it is conceivable that the chromatographic data filters taught in this paper could also be applied in a post-processing step to data acquired after all scans in the experiment have been completed.

[0034] Figure 2 The chromatographic data filter 202 taught herein is illustrated using a network representation, which transforms raw chromatographic data into filtered chromatographic data. The chromatographic data filter can be defined or determined based on filter parameters, which may include, but are not limited to, filter coefficients and filter bandwidth. The chromatographic data filter 202 is an example of a second-order infinite impulse response (IIR) filter. As shown, the chromatographic data filter 202 acts as a low-pass filter, effectively removing high-frequency baseline noise and smoothing data jitter on chromatographic peaks. In some examples, the chromatographic data filter 202 can improve overall performance by at least two times. The chromatographic data filter 202 can be a feedback or recursive filter. The transfer function of the chromatographic data filter 202 can be described as Y... n =b0×X n +b1×X n-1 +b2×X n-2 +a1×Y n +a2×Y n-1 Where the filter coefficients b0...b i and a0...a i The cutoff frequency can be defined according to the following relationship: f cutoff = 0.5 × time base ÷ bandwidth. The bandwidth filter parameter can be a user-specified parameter or it can be determined based on the peak width of 112. In some examples, the bandwidth can be equal to the peak width ÷ 4.

[0035] The chromatographic data filters taught in this paper can use low-pass filters to eliminate high-frequency noise. These filters (which can be implemented using analog, digital, or a combination of analog and digital components) operate both in the time domain and in the chromatographic time domain, corresponding to the mass-to-charge ratio of the acquired spectrum. Therefore, multidimensional filters eliminate high-frequency noise in the chromatographic peak distribution that is irrelevant to the true analytical signal. The filters can be applied to the ion signal in real time during data acquisition. The signal-to-noise ratio improvement can range from 2X to 5X. Furthermore, peak integration is more reliable, thus providing an improved limit of quantitation, without affecting the linearity of the assay.

[0036] In some examples, the chromatographic data filters taught herein can be implemented via instructions (e.g., stored in a non-transitory computer-readable medium) executed by a computing device that communicates with or is part of the chromatographic and mass spectrometry system. For example, the instructions can be executed by a digital signal processor (DSP) within the mass spectrometry system. The chromatographic data filters can be applied to data (e.g., ion signals) in real time. Some parameters can be specified by the user, such as the expected baseline width of the chromatographic peaks in the determination. The computing device, DSP, or other processor can calculate appropriate bandwidths based on the input peak widths and apply them to the data.

[0037] In some examples, the bandwidth parameter is set by the user or by the computational system based on checks of actual chromatographic data in the analysis (e.g., actual raw data acquired in the same series of scans or previously obtained series of scans). If the bandwidth is set too low, high-frequency noise may reappear in the baseline and peak distribution. In extreme cases, the filter may have little effect, and the filtered signal may look the same as when the filter is off. If the bandwidth parameter is set too high, the chromatographic peak distribution may become significantly broadened (i.e., the peaks may become shorter and thicker). Note that even when the bandwidth parameter is set too high, the peak area remains correct.

[0038] In some implementations, the actual peak width of 112 can deviate significantly from the expected bandwidth setting (i.e., the bandwidth filter parameter determined based on previous data review or provided by the user) without adversely affecting the quality of the results. As noted, a longer bandwidth can widen the peak and reduce its height, but can preserve the peak area. In some examples, the user can set the bandwidth to the highest value that will not result in significant peak widening.

[0039] If some chromatographic peaks in an analysis exhibit significantly different peak shape characteristics (i.e., broad peaks, tailing peaks, etc.), the system can use a procedure with a time window to adjust the bandwidth parameter. If a chromatographic peak begins to tail significantly in subsequent runs of analysis, such as when the column or other injection system begins to degrade, it may be necessary to update or change the filter bandwidth. In this case, the signal-to-noise ratio may decrease, and automatic peak integration may lose some peaks or integrate irrelevant baseline noise. To avoid this effect, the systems and methods taught in this paper can monitor peak shape and automatically adjust the bandwidth parameter, or notify the user that the bandwidth parameter should be updated if a change in peak shape is detected.

[0040] In some systems, the computing devices associated with the mass spectrometer can obtain input from the user to define filter parameters, such as bandwidth, for the chromatographic data filters. This can be done, for example, through the mass spectrometer's graphical user interface. In some examples, the user can define different bandwidths to be used for different subsets of scans in a series of scans.

[0041] Figure 2 The chromatographic data filter 202 in the example is illustrated by a network formula, but other forms of data filtering using a time base smaller than the minimum data sampling interval are also envisioned within this disclosure.

[0042] Figure 3A Two graphs are shown illustrating raw data from different m / z ranges within the same time span from scans separated by non-uniform data sampling intervals. The raw data includes significant jitter and fluctuations due to factors such as ion statistical noise caused by low ion signals.

[0043] Figure 3B An example is given of data obtained using a conventional static filter with a non-uniform data sampling interval. Figure 3A The raw data. The resulting peaks are unstable and may include artifacts such as shoulders 302. Because the constant time base 104 of a conventional static filter can be longer than the data sampling interval, multiple scans can occur within the filter's sampling period, or potentially, no scans can occur within the sampling period. This can lead to the erroneous amplification or reduction of the effects of past data points in the filter's operation, which may change unpredictably depending on how close the data points are to the filter's sampling time. Examples of this erroneous behavior can be found in... Figure 3B In the inversion of 304, we can see that... Figure 3A The relative intensities of the two peaks at approximately 0.66 minutes and 0.76 minutes in the raw data are... Figure 3B The middle part was incorrectly reversed.

[0044] Figure 3CAn example is illustrated using a chromatographic data filter applied according to the examples taught herein, with a non-uniform data sampling interval. Figure 3A The original data. Figure 3C chromatographic peak ratio Figure 3A The data are significantly smoother and exhibit reduced baseline noise. Furthermore, the amplitude of high-frequency noise associated with individual ion events is reduced, while all areas associated with ion signal detection are preserved. The attenuation of high frequencies from the baseline and peak distribution can improve the chromatographic signal-to-noise ratio by approximately 2 to 3 times compared to standard data acquisition conditions.

[0045] A smoother peak distribution helps to make peak integrals more consistent, which can improve accuracy and provide a lower limit of quantitation (LOQ) in quantitative assays. Unlike traditional post-acquisition smoothing algorithms, which blur peaks and include adjacent baseline noise, the chromatographic data filter taught in this paper preserves chromatographic peak shape and does not cause artificial peak tailing.

[0046] The performance and stability of the chromatographic data filter taught in this paper were explored by evaluating the relative standard deviation of peak areas in repeated scans. For three peaks of different intensities, full scans were obtained, and the %RSD of peak areas was measured for n = 6 scans. As shown in Table 1, the chromatographic data filter taught in this paper significantly improves the standard deviation of peak areas in data obtained using non-uniform data sampling intervals.

[0047]

[0048] In some examples, the application of chromatographic data filters can improve spectral stability. Multidimensional filtering can be performed on the distribution data, which is then passed to the centroid algorithm. Therefore, the centroid has a more stable signal to operate from scan to scan. The benefits are evident when the system scans over a wide mass range, where peak height and width are more stable. This allows for low bandwidth with fast scans. Chromatographic bias is reduced by allowing all masses associated with component elution to be maximized simultaneously. In SRM analyses where the scan window is typically less than 1 Dalton, the benefits to the centroid may not be very significant. However, the low bandwidth relative to scans per second can improve reconstructed ion chromatograms in SRM analyses.

[0049] Figure 4The illustration shows the time shift between the original peak and the filtered peak in some embodiments of the chromatographic data filter taught herein. The original data peak 402 precedes the uniform data filtered peak 404 (i.e., data filtered using a conventional data filter where the time base equals the static data sampling interval) and the non-uniform data filtered peak 406 (i.e., data filtered using a chromatographic data filter as taught herein, adapted to use a time base 106 shorter than the shortest dynamic (e.g., non-uniform or varying) data sampling interval 110 in a series of scans). Because the time base 106 and adjusted bandwidth of the data filter of the present invention operate at a higher sampling rate than the constant time base 104 of a conventional data filter, the chromatographic data filter taught herein can utilize a new set of filter coefficients that reduce the time lag of the non-uniform data filtered peak 406 compared to the lag of the uniform data filtered peak 404.

[0050] Due to the recursive properties of some specific implementations of chromatographic data filters (such as the infinite impulse response formula), an artificial time delay can be introduced into the peak when enough data points are obtained to feed back into the chromatographic data filter (e.g., chromatographic data filter 202). In some examples, the time delay is equivalent to approximately one or two data points. This delay can have an impact on acquisition or processing algorithms that rely on precise timing or peak detection. Using a chromatographic data filter as taught herein reduces the time lag between the raw and filtered data compared to conventional filters. In some embodiments, the chromatographic data filter may include compensation techniques that take the delay into account. For example, the chromatographic data filter may adjust the timing or incorporate a predictive algorithm to align the filtered signal with the original unfiltered signal. Such compensation can reduce or minimize any adverse effects on peak detection or peak analysis.

[0051] Figure 5 An exemplary method for processing data obtained from scans with non-uniform data sampling intervals to form a chromatogram is illustrated. Although the exemplary routine depicts a particular sequence of operations, that sequence may be modified without departing from the scope of this disclosure. For example, some of the operations depicted may be performed in parallel or in different sequences that do not substantially affect the functionality of the routine. In other examples, different components of the exemplary device or system implementing the routine may perform functions substantially simultaneously or in a particular sequence.

[0052] According to some examples, the method includes obtaining multiple data points at box 502 during sample elution from the injection system, corresponding to multiple scans, each of which occurs within a corresponding data sampling interval.

[0053] According to some examples, the method includes applying a chromatographic data filter at box 504 to multiple data points, the filter including a time base smaller than any data sampling interval in the corresponding data sampling interval.

[0054] Figure 6 An exemplary method for processing data obtained from scans with non-uniform data sampling intervals to form a chromatogram is illustrated. Although the exemplary routine depicts a particular sequence of operations, that sequence may be modified without departing from the scope of this disclosure. For example, some of the operations depicted may be performed in parallel or in different sequences that do not substantially affect the functionality of the routine. In other examples, different components of the exemplary device or system implementing the routine may perform functions substantially simultaneously or in a particular sequence.

[0055] According to some examples, the method includes obtaining multiple data points at box 604 during sample elution from the injection system, corresponding to multiple scans, each of which occurs within a corresponding data sampling interval.

[0056] According to some examples, the method includes measuring the data sampling interval (scan duration) of the first scan at box 606.

[0057] According to some examples, the method includes dividing the data sampling interval by an interpolation factor at box 608 to determine the time base of the chromatographic data filter.

[0058] According to some examples, the method includes calculating the filter coefficients of the chromatographic data filter based on the time base at box 610.

[0059] According to some examples, the method includes applying a chromatographic data filter at box 612 to at least some of the data points among a plurality of data points, the number of applications being equal to the interpolation factor.

[0060] According to some examples, the method includes combining (e.g., integrating) the results of multiple filter operations at box 614 to produce output filtered data points.

[0061] In some examples, a computer program product embodied in a non-transitory computer-readable storage medium may be provided. In such examples, the non-transitory computer-readable storage medium may store computer-readable instructions in accordance with the principles described herein. When executed by a processor of a computing device, the instructions may instruct the processor and / or the computing device to perform one or more operations, including one or more operations described herein. Such instructions may be stored and / or transmitted using any computer-readable medium of a variety of known computer-readable media.

[0062] As used herein, non-transitory computer-readable media can include any non-transitory storage medium that contributes to providing data (e.g., instructions) that can be read and / or executed by a computing device (e.g., by the processor of the computing device). For example, non-transitory computer-readable media can include, but is not limited to, any combination of non-volatile storage media and / or volatile storage media. Exemplary non-volatile storage media include, but are not limited to, read-only memory, flash memory, solid-state drives, magnetic storage devices (e.g., hard disks, floppy disks, magnetic tapes, etc.), ferroelectric random access memory (“RAM”), and optical discs (e.g., compact discs, digital video discs, Blu-ray discs, etc.). Exemplary volatile storage media include, but are not limited to, RAM (e.g., dynamic RAM).

[0063] Figure 7 An exemplary computing device 700 is shown, which can be specifically configured to perform one or more of the operations, methods, and processes described herein. Any of the systems, computing devices, and / or other components described herein can be implemented by computing device 700.

[0064] like Figure 7 As shown, computing device 700 may include a communication interface 706, a processor 708, a storage device 710, and an input / output (“I / O”) module 712 that are communicatively connected to each other via communication infrastructure 720. Although Figure 7 An exemplary computing device 700 is shown, but Figure 7 The components shown are not intended to be limiting. In some examples, the computing device 700 may be operatively connected to or embedded in a mass spectrometer. In other embodiments, additional or alternative components may be used. A more detailed description will now follow. Figure 7 The components of the computing device 700 shown.

[0065] Communication interface 706 can be configured to communicate with one or more computing devices. Examples of communication interface 706 include, but are not limited to, wired network interfaces (such as network interface cards), wireless network interfaces (such as wireless network interface cards), modems, audio / video connections, and any other suitable interfaces.

[0066] Processor 708 generally refers to any type or form of processing unit capable of processing data and / or interpreting, executing, and / or directing one or more of the instructions, procedures, and / or operations described herein. Processor 708 may perform operations by executing computer-executable instructions 722 (e.g., application programs, software, code, and / or other executable data instances) stored in storage device 710.

[0067] Storage device 710 may include one or more data storage media, devices, or configurations, and may employ any type, form, and combination of data storage media and / or devices. For example, storage device 710 may include, but is not limited to, any combination of non-volatile media and / or volatile media described herein. Electronic data including the data described herein may be stored temporarily and / or permanently in storage device 710. For example, data representing computer-executable instructions 722 configured to boot processor 708 to perform any of the operations described herein may be stored within storage device 710. In some examples, data may be arranged in one or more databases residing within storage device 710.

[0068] I / O module 712 may include one or more I / O modules configured to receive user input and provide user output. One or more I / O modules can be used to receive input for a single virtual experience. I / O module 712 may include any hardware, firmware, software, or a combination thereof that supports input and output capabilities. For example, I / O module 712 may include hardware and / or software for capturing user input, including but not limited to a keyboard or keypad, a touchscreen component (e.g., a touchscreen display), a receiver (e.g., an RF or infrared receiver), a motion sensor, and / or one or more input buttons.

[0069] I / O module 712 may include one or more devices for presenting output to a user, including but not limited to a graphics engine, a display (e.g., a screen), one or more output drivers (e.g., display drivers), one or more audio speakers, and one or more audio drivers. In some embodiments, I / O module 712 is configured to provide graphical data to the display for presentation to the user. The graphical data may represent one or more graphical user interfaces and / or any other graphical content that may serve a particular implementation.

[0070] The advantages and features of this disclosure can be further described by the following enumerated aspects:

[0071] Aspect 1: A method for processing data obtained from scans having non-uniform data sampling intervals to form a chromatogram, the method comprising: obtaining a plurality of data points corresponding to multiple scans during elution of a sample from an injection system, each of the multiple scans occurring within a corresponding data sampling interval; and applying a chromatographic data filter to at least some of the plurality of data points, the filter including a time base, wherein the time base is smaller than any of the corresponding data sampling intervals.

[0072] Aspect 2: According to the method of aspect 1, the method further includes: determining a first data sampling interval among the plurality of corresponding data sampling intervals; setting the time base to be equal to the first data sampling interval divided by an interpolation factor; and using the time base to adjust the filter parameters of the chromatographic data filter.

[0073] Aspect 3: According to the method of aspect 1, the method further includes: determining the shortest data sampling interval among the corresponding data sampling intervals; setting the time base to be equal to the shortest data sampling interval divided by an interpolation factor; and using the time base to adjust the filter parameters of the chromatographic data filter.

[0074] Aspect 4: The method according to aspect 2 or 3, wherein the interpolation factor is five.

[0075] Aspect 5: The method according to any one of Aspects 1 to 4, wherein at least two of the corresponding data sampling intervals are not equal.

[0076] Aspect 6: The method according to aspect 2 or 3, wherein the interpolation factor is selected to balance data quality and available computing resources.

[0077] Aspect 7: The method according to any one of Aspects 1 to 6, the method further comprising: adjusting the timing of the plurality of data points to align the filtered signal with the original unfiltered signal.

[0078] Aspect 8: The method according to any one of Aspects 1 to 7, the method further comprising: monitoring the peak shape generated from filtered data points among the plurality of data points; and adjusting the filter bandwidth of the chromatographic data filter in response to identifying a change in the peak shape.

[0079] Aspect 9: The method according to any one of Aspects 1 to 8, the method further comprising: monitoring a data sampling interval during the elution of the sample; and adjusting the time base of the chromatographic data filter such that the time base does not become greater than the data sampling interval during the multiple scans.

[0080] Aspect 10: A non-transitory computer-readable storage medium including instructions that, when processed by a computing device, configure the computing device to: acquire a plurality of data points corresponding to multiple scans during sample elution from an injection system, each of the multiple scans occurring within a corresponding data sampling interval; and apply a chromatographic data filter to at least some of the plurality of data points, the filter including a time base, wherein the time base is smaller than any of the corresponding data sampling intervals.

[0081] Aspect 11: A method for processing data obtained from scans having non-uniform data sampling intervals to form a chromatogram, the method comprising: obtaining a plurality of data points corresponding to multiple scans during elution of a sample from an injection system, each of the multiple scans occurring within a corresponding data sampling interval; measuring at least one corresponding data sampling interval; dividing the at least one corresponding data sampling interval by an interpolation factor to determine a time base for a chromatographic data filter; calculating filter coefficients of the chromatographic data filter based on the time base; and applying the chromatographic data filter to at least some of the plurality of data points.

[0082] Aspect 12: According to the method of aspect 11, wherein the at least one corresponding data sampling interval is used for the first scan in the multiple scans.

[0083] Aspect 13: According to the method of aspect 11, wherein the at least one corresponding data sampling interval is used for the shortest scan in the multiple scans.

[0084] Aspect 14: The method according to any one of aspects 11 to 13, the method further comprising applying the chromatographic data filter to the data points, the number of applications being equal to the interpolation factor.

[0085] Aspect 15: According to the method of aspect 14, the method further includes combining the results of multiple applications of filters to generate output filtered data points.

[0086] Aspect 16: The method according to any one of aspects 11 to 15, the method further comprising: monitoring the peak shape generated from filtered data points among the plurality of data points; and adjusting the filter bandwidth of the chromatographic data filter in response to identifying a change in the peak shape.

[0087] Aspect 17: The method according to any one of Aspects 11 to 16, the method further comprising: adjusting the timing of the plurality of data points to align the filtered signal with the original unfiltered signal.

[0088] Aspect 18: The method according to any one of Aspects 11 to 17, the method further comprising: monitoring a data sampling interval during the elution of the sample; and adjusting the time base of the chromatographic data filter such that the time base does not become greater than the data sampling interval during the multiple scans.

[0089] Aspect 19: A non-transitory computer-readable storage medium comprising instructions that, when processed by a computing device, configure the computing device to: acquire a plurality of data points corresponding to multiple scans during sample elution from an injection system, each of the multiple scans occurring within a corresponding data sampling interval; measure at least one corresponding data sampling interval; divide the at least one corresponding data sampling interval by an interpolation factor to determine a time base for a chromatographic data filter; calculate filter coefficients of the chromatographic data filter based on the time base; and apply the chromatographic data filter to at least some of the plurality of data points.

[0090] Aspect 20: According to the method of aspect 19, the method further includes applying the chromatographic data filter to the data points, the number of applications being equal to the interpolation factor.

[0091] In the preceding description, various exemplary embodiments have been described with reference to the accompanying drawings. However, it will be apparent that various modifications and alterations may be made thereto, and additional embodiments may be implemented, without departing from the scope of the invention as set forth in the appended claims. For example, certain features of one embodiment described herein may be combined with or substituted for features of another embodiment described herein. Therefore, this description and the accompanying drawings should be considered illustrative rather than restrictive.

Claims

1. A method for processing data obtained from a scan having non-uniform data sampling intervals to form a chromatogram, the method comprising: During sample elution from the injection system, multiple data points corresponding to multiple scans are obtained, each of which occurs within a corresponding data sampling interval. as well as A chromatographic data filter is applied to at least some of the plurality of data points, the filter including a time base. The time base is less than any data sampling interval in the corresponding data sampling interval.

2. The method according to claim 1, further comprising: Determine the first data sampling interval among the plurality of corresponding data sampling intervals; Set the time base to be equal to the first data sampling interval divided by the interpolation factor; as well as The time base is used to adjust the filter parameters of the chromatographic data filter.

3. The method according to claim 1, wherein the method further comprises: Determine the shortest data sampling interval among the corresponding data sampling intervals; Set the time base to be equal to the shortest data sampling interval divided by the interpolation factor; as well as The time base is used to adjust the filter parameters of the chromatographic data filter.

4. The method according to claim 2, wherein, The interpolation factor is five.

5. The method according to claim 2, the method further comprising applying the chromatographic data filter to the data points, the number of applications being equal to the interpolation factor.

6. The method of claim 5, further comprising combining the results of multiple filter applications to generate output filtered data points.

7. The method according to claim 2, wherein, The interpolation factor was selected to balance data quality with available computing resources.

8. The method according to claim 1, wherein, At least two of the corresponding data sampling intervals are not equal.

9. The method according to claim 1, wherein the method further comprises: Adjust the timing of the multiple data points to align the filtered signal with the original unfiltered signal.

10. The method according to claim 1, wherein the method further comprises: Monitor the peak shape generated from the filtered data points among the plurality of data points; as well as The filter bandwidth of the chromatographic data filter is adjusted in response to the identification of changes in the peak shape.

11. The method according to claim 1, wherein the method further comprises: The data sampling interval during the elution of the sample is monitored; as well as The time base of the chromatographic data filter is adjusted so that it does not become larger than the data sampling interval during the multiple scans.

12. A non-transitory computer-readable storage medium comprising instructions that, when processed by a computing device, configure the computing device to: During sample elution from the injection system, multiple data points corresponding to multiple scans are acquired, each of which occurs within a corresponding data sampling interval; and A chromatographic data filter is applied to at least some of the plurality of data points, the filter including a time base. The time base is less than any data sampling interval in the corresponding data sampling interval.

13. A method for processing data obtained from a scan having non-uniform data sampling intervals to form a chromatogram, the method comprising: During sample elution from the injection system, multiple data points corresponding to multiple scans are obtained, each of which occurs within a corresponding data sampling interval. Measure at least one corresponding data sampling interval; Divide the at least one corresponding data sampling interval by the interpolation factor to determine the time base of the chromatographic data filter; The filter coefficients of the chromatographic data filter are calculated based on the time base; as well as The chromatographic data filter is applied to at least some of the plurality of data points.

14. The method according to claim 13, wherein, The at least one corresponding data sampling interval is used for the first scan in the multiple scans.

15. The method according to claim 13, wherein, The at least one corresponding data sampling interval is used for the shortest scan in the multiple scans.

16. The method of claim 13, further comprising applying the chromatographic data filter to the data points, the number of applications being equal to the interpolation factor.

17. The method of claim 16, further comprising combining the results of multiple applications of the filter to generate output filtered data points.

18. The method of claim 13, further comprising: Monitor the peak shape generated from the filtered data points among the plurality of data points; as well as The filter bandwidth of the chromatographic data filter is adjusted in response to the identification of changes in the peak shape.

19. The method of claim 13, further comprising: Adjust the timing of the multiple data points to align the filtered signal with the original unfiltered signal.

20. The method of claim 13, further comprising: The data sampling interval during the elution of the sample is monitored; as well as The time base of the chromatographic data filter is adjusted so that it does not become larger than the data sampling interval during the multiple scans.

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