Quantification of chemical species using data independent acquisition

Abstract

A mass spectrum dataset including precursor ions and ion fragments is obtained, with each of the precursor ions associated with a location. An abundance of a target ion is quantified by identifying the location of the target ion and analyzing a range including the location to output a set of precursor ions associated with the range. The target ion is a subset of the set of precursor ions. A set of the ion fragments associated with the range is analyzed and a target relationship is determined. The target relationship is a precursor relationship between at least one of the ion fragments and the target ion. An intensity of the at least one of the ion fragments is determined and the target ion is quantified using the intensity of the at least one of the ion fragments and the target relationship.

Description

Attorney Docket No. 18768.0121WOU1 / 2024-23230-P-WOQUANTIFICATION OF CHEMICAL SPECIES USING DATA INDEPENDENT ACQUISITIONCROSS-REFERENCE TO RELATED APPLICATION

[0001] This application is being filed as a PCT International application and claims the benefit of and priority to U.S. Provisional Application No. 63 / 749,412, filed January 24, 2025, the disclosure of which is hereby incorporated by reference in its entirety.BACKGROUND

[0002] Mass spectrometry is an analytical technique which can be used to quantify chemical species by measuring the abundance of ions produced from a sample. In this process, the sample is first ionized to generate charged particles, which are then separated based on their mass-to-charge (m / z) ratio in the mass analyzer. The resulting ion intensities are recorded, providing a mass spectrum that serves as a unique “fingerprint” of the sample. By comparing the ion intensities of the target species to known standards or calibration curves, the concentration of a specific chemical species can be accurately quantified.SUMMARY

[0003] Examples presented herein relate to a method of quantifying an ion species using a mass spectrometer. The method includes obtaining a mass spectrum dataset including one or more precursor ions and one or more fragments, each of the one or more precursor ions associated with a location and quantifying an abundance of a target ion in the mass spectrum dataset by: identifying the location of the target ion; analyzing a range including the location to output a set of the one or more precursor ions associated with the range, wherein the target ion is a subset of the set of the one or more precursor ions; analyzing a set of the one or more ion fragments associated with the range; determining a target relationship, wherein the target relationship is a precursor relationship between at least one of the one or more fragments and the target ion; determining an intensity of the at least one of the one or more fragments; and quantifying the target ion using the intensity of the at least one of the one or more fragments and the target relationship.

[0004] In other examples presented herein, the location of the target ion includes one of a mass of the target ion and an appearance time of the target ion and ion mobility of the target ion. In further examples presented herein, the range is at least one of a mass range and a time range.

[0005] In other examples presented herein, the method further includes determining a confidence measure for the quantifying. In further examples presented herein, determining the confidence measure includes calculating a likelihood of accuracy of the target relationship. In other further examples presented herein, calculating the likelihood of accuracy of the target relationship includes determining a weighted intensity of the one or more fragments. In yet further examples presented herein, the weighted intensity includes applying a weight to each intensity of the one or more fragments based on the target relationship.

[0006] In other further examples presented herein, analyzing the range is performed by scanning a filter window of a fixed width across the range. In still further examples presented herein, scanning the filter window across the mass range includes the filter window being moved across the mass range in a fixed step progression. In yet further examples presented herein, each subsequent filter window in the fixed step progression shares an overlap with at least one preceding filter window. In other further examples presented herein, scanning the filter window across the mass range includes the filter window being moved across the mass range at a dynamic rate.

[0007] In other examples presented herein, analyzing the range is performed by scanning a filter window with a dynamic width across the range. In yet other examples presented herein, data associated with the one or more precursors originates from a first mass spectrometer of a tandem mass spectrometer. In further examples presented herein, the first mass spectrometer is a quadrupole. In other further examples presented herein, data associated with the one or more fragments originates from a second mass spectrometer of the tandem mass spectrometer. In still further examples presented herein, the second mass spectrometer is a time of flight mass spectrometer.

[0008] In other examples presented herein, the method further includes deconvoluting the mass spectrum dataset. In further examples presented herein, deconvoluting the mass spectrum dataset includes deconvoluting the location. In other further examples presented herein, deconvoluting the mass spectrum dataset includes deconvoluting at least one of the one or more fragments.

[0009] Other examples presented herein relate to a method of determining a confidence score when quantifying an ion species using mass spectroscopy. The method includes obtaining a mass spectrum dataset including one or more precursor ions and one or more fragments, each of the one or more precursor ions association with a location; determining the confidence score for quantifying an abundance of a target ion in the mass spectrum dataset by: identifying the location of the target ion to be quantified; analyzing a range including the location to output a set of the one or more precursor ions associated with the range, wherein the target ion is a subset of the set of the one or more precursor ions; analyzing a set of the one or more ion fragments associated with the range; determining a target relationship, wherein the target relationship is a precursor relationship between at least one of the one or more fragments and the target ion; and determining a weighted intensity of the one or more fragments, wherein the weighted intensity comprises applying a weight to each intensity of the one or more fragments based on the target relationship.

[0010] In other examples presented herein, the method further includes quantifying the target ion using the weighted intensity of the at least one of the one or more fragments.

[0011] Other examples presented herein relate to a method of determining a confidence score when quantifying an ion species using mass spectroscopy. The method includes identifying a location of a target ion to be quantified; filtering across a mass range including the location to output one or more precursor ions, wherein the target ion is a subset of the set of the one or more precursor ions; fragmenting at least one of the one or more precursor ions to output one or more ion fragments; measuring an intensity of one or more ion fragments; determining a target relationship, wherein the target relationship is a precursor relationship between at least one of the one or more fragments and the target ion; determining a weighted intensity of the one or more fragments, wherein the weighted intensity comprises applying a weight to each intensity of the one or more fragments based on the target relationship; and calculating the confidence score using the weighted intensity and the target relationship.

[0012] Still other examples presented herein relate to a system for quantifying an ion species using a mass spectrometer. The system includes a tandem mass spectrometer including: a first mass spectrometer configured for filtering across a mass range including a location of the ion species to output one or more precursor ions; a second mass spectrometer configured for measuring an intensity of one or more ion fragmentsresulting from the one or more precursor ions; and a computing device, in communication with the tandem mass spectrometer, configured for: defining a target relationship, wherein the target relationship is a precursor relationship between at least one of the one or more fragments and the target ion; calculating a likelihood of accuracy of the target relationship; and quantifying the target ion using a weighted intensity of the one or more fragments and the target relationship.

[0013] Yet other examples presented herein relate to a method of quantifying an ion species using a mass spectrometer. The method includes identifying a location of a target ion to be quantified; analyzing a range including the location to output one or more precursor ions, wherein the target ion is a subset of the one or more precursor ions; fragmenting the one or more precursor ions to output one or more ion fragments; measuring an intensity of each of the one or more ion fragments; and determining a precursor relationship between at least one of the one or more fragments and the target ion; quantifying the target ion using the intensity of the at least one of the one or more fragments.

[0014] A variety of additional inventive aspects will be set forth in the description that follows. The inventive aspects can relate to individual features and to combinations of features. It is to be understood that both the forgoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the broad inventive concepts upon which the embodiments disclosed herein are based.BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings, which are incorporated in and constitute a part of the description, illustrate several aspects of the present disclosure. A brief description of the drawings is as follows:

[0016] FIG. 1 is an example of data independent acquisition of data suitable for application of the methods disclosed herein.

[0017] FIG. 2A is an example of a quantification process according to embodiments of the present disclosure.

[0018] FIG. 2B is an example of a quantification process including deconvolution according to embodiments of the present disclosure.

[0019] FIG. 3 is a block diagram of an example mass spectrometry system, which embodiments of the present disclosure may be implemented upon or in association with.

[0020] FIG. 4 is block diagram of an example data processing system for processing and quantifying mass spectrum data.

[0021] FIG. 5 is a flowchart of an example method of quantifying an ion species using a mass spectrometer shown.

[0022] FIG. 6 is a flowchart of an example method of determining a confidence score when quantifying an ion species using mass spectroscopy.

[0023] FIG. 7 is a flowchart of another example method of determining a confidence score when quantifying an ion species using mass spectroscopy.

[0024] FIG. 8 illustrates an example block diagram of a virtual or physical computing system.DETAILED DESCRIPTION

[0025] Disclosed herein are improved methods and systems for quantification of particles using mass spectrometry. Further disclosed herein are methods and systems for determining and applying a confidence score related to quantification. Embodiments of the present disclosure may particularly relate to the use of data independent acquisition methods which acquire a full tandem mass spectrometry (also referred to in the art as MS / MS or MS2) spectra for all precursor ions within a predefined m / z range in a sequential window, identifying fragment ions that could be missed using conventional targeted techniques. This comprehensive approach allows for the detection and quantification of multiple compounds simultaneously across complex samples.

[0026] Quantification using MS typically involves monitoring specific fragment ions (daughter ions) resulting from the fragmentation of a precursor ion (parent ion). The choice of product ion to monitor in tandem mass spectrometry (MS / MS) experiments can affect the sensitivity and specificity of the analysis. Sometimes, less abundant but more specific ions may be better for quantification, but not every sample will such a specific ion that can be easily identified. In complex samples, the presence of co-eluting species with similar mass-to-charge (m / z) ratios can cause convolution, leading to inaccurate quantification. Even with high-resolution instruments, overlapping peaks may require careful deconvolution, which can complicate quantification. For example, a convolved species may be isomeric and inseparable in observed dimensions and therefore deconvolution requires a dimension of the data.

[0027] MS generates complex data, particularly in high-resolution tandem MS experiments. The interpretation of spectra to determine the identity and concentration of chemical species requires knowledge of the chemical structure and fragmentation behavior. Modem instruments are able to collect > 300 thousand MS2 spectra per hour in DDA mode while the numbers in DIA mode are even higher (as many as le6 MSMS spectra can be generated in one hour in DIA modes). Despite the data acquisition capabilities of modem MS systems, quantification using current strategies often requires careful experimental design, method validation, and sometimes sample preparation techniques to ensure accurate and reproducible quantification.

[0028] Methods and processes for quantification and validation provided herein overcome these and other limitations of existing quantification standards. Embodiments of the present disclosure provide a novel method of quantifying an ion species using a mass spectrometer. In some preferred embodiments, the present disclosure is applied using mass spectra data acquired using a data independent acquisition (DIA) method, such as scanning sequential acquisition of all theoretical mass spectra.

[0029] FIG. 1 is an example of DIA data suitable for application of the methods disclosed herein. These types of data acquisition generate data in multiple dimensions. Processing of the data to leverage these dimensions against one another enables novel analysis and output by the system.

[0030] For example, FIG. 1 presents a first dimension, called the quad or QI dimension 10, which identifies a precursor m / z or an m / z of a parent ion. The QI dimension is generally associated with a first mass spectrometer in a tandem mass spectrometer, which may generally be a quadrupole. In some DIA methods, the QI dimension is further associated with a number of “windows” 20 which can be overlapping as shown in the example of FIG. 1 or fully discrete. The inclusion and arrangement of windows 20 can inform the relationship between the QI dimension and other dimensions of the obtained data, as will be discussed in further detail below.

[0031] A second dimension, called an MS2 dimension 30, identifies a fragment m / z or an m / z of fragments resulting from a fragmentation device. The MS2 dimension is generally associated with a second mass spectrometer in a tandem mass spectrometer. Other dimensions include intensity, seen in FIG. 1 as the height of the bars in each of Q 1 dimension 10 and MS2 dimension 30, and time. A time or separation dimension may beincorporated, for example, as a retention time by incorporating a liquid chromatography column in series with the tandem mass spectrometer.

[0032] FIG. 2A is an example of a quantification system process according to embodiments of the present disclosure. The example process of FIG. 2A presents three dimensions of data arranged in a graph 50 to depict their relevant relationship to one another. QI dimension 10 or precursor m / z is arranged on one axis, with a separation dimension 40 or retention time arranged on a perpendicular axis. MS2 dimension 30 or fragment m / z is arranged on a third axis perpendicular to each of the first and second axis. The example of FIG. 2 A is shown in three dimensions for clarity of discussion, but those of skill in the art will understand that further dimensionality of the data is both possible and to be expected.

[0033] As will be discussed in further detail below, the present disclosure relates to the quantification of a target ion or chemical species by processing mass spectrometry data. In embodiments, the mass spectrometry data is acquired using a DIA method. The target is defined by a location within the data, with the location defining the target based on the dimensions to be analyzed. For example, the target may be a particular precursor ion defined using one or both a precursor m / z, in the QI dimension, and a retention time, in the separation dimension. Example location 52 is shown on the graph 50, which may be defined by one or both of a precursor m / z 54 and a retention time 56.

[0034] In many instances, a target to quantify may not be readily located in a sample due to, for example, convolution and other complexities in the data, as discussed in greater detail above. It is therefore frequently impractical to directly search for a location, such as location 52, of the target. Instead, the present disclosure provides that a range 58, which is configured to include the location 52, is searched and analyzed to identify the location 52 and determine with certainty the presence and abundance of the target.

[0035] Range 58 may generally be defined in terms of the same dimensions which are used to define the target location 52, e.g., precursor m / z and retention time. In embodiments incorporating QI windows, such as the windows 20 of FIG. 1, range 58 may be defined using one or more windows. Using range 58 and the established relationships among the dimensions of the data, a corresponding definition 60 can be established in the fragment m / z dimension, providing a set of output fragments to be analyzed. Using the set of output fragments, one or more parent ions to the set of output fragments are identified, establishing precursor relationships between the parents andtheir daughter fragments. If the target is among the one or more parent ions, the precursor relationship to the target is characterized as a target relationship and the fragments associated with the target relationship are used to quantify the target.

[0036] FIG. 2B is an example of a quantification process including deconvolution according to embodiments of the present disclosure. Deconvolution refers to the process of extracting and resolving complex signals from the raw data. The particular aim of deconvolution is to resolve overlapping or closely spaced peaks in order to effectively identify the different components present in the sample, as such overlaps may obscure or distort the identifying characteristics, e.g., m / z ratio, of compounds and ions.

[0037] The example of FIG. 2B presents three dimensions of data arranged in a graph 51 to depict their relevant relationship to one another. Graph 51 repeats the features of graph 50 of FIG. 2A, with the addition of convolution 62 distorting target location 52.

[0038] As discussed above, location 52 is defined based on characteristics or parameters of a target ion or compound to be quantified. Convolution 62 is an example of another ion or compound, other than the target, which shares some portion or characteristic of the location with the target. This may be attributable, for example, to the resolution of the data, or may result from the complexity of the sample. For instance, when isomers are present in a sample, the mass spectrometer may not resolve the individual contributions of each isomer, leading to a combined signal. In this case, the resulting spectrum will show a broad or ambiguous peak, where the contributions from different isomers are convoluted. As can be seen in the example graph 51, in some cases, a convolution 62 may fall fully within the range 58, and prevent an accurate quantitation of target location 52 unless deconvolution is performed.

[0039] In some cases, deconvolution can be accomplished by enhancing the resolution of the MS data, and / or by manual inspection of the data, particularly in the precursor m / z dimension. Deconvolution may also be performed using mathematical techniques such as a Fourier transform or clustering, such as using non-negative least squares or principal component variable grouping.

[0040] FIG. 3 is a block diagram of an example mass spectrometry system 100, which embodiments of the present disclosure may be implemented upon or in association with. In embodiments, other systems for determining compound structure and identity may be integrated with a mass spectrometry system or, in other embodiments, may be independent of the mass spectrometry system. Example system 100 includes an ionsource 110, a first mass separator or mass filter 120, a fragmentation device 130, a second mass separator or a mass analyzer 140, and a computing system 150.

[0041] In embodiments, system 100 further includes a sample introduction device 160. Sample introduction device 160 introduces one or more compounds of interest from a sample to ion source 110 over time. Sample introduction device 160 performs techniques that include, but are not limited to, direct injection, liquid chromatography, gas chromatography, capillary electrophoresis, or ion mobility.

[0042] Mass filter 120 and fragmentation device 130 are shown as different stages of a quadrupole and mass analyzer 140 is shown as a time-of-flight (TOF) device. Those of ordinary skill in the art will appreciate that either of mass filter 120 and mass analyzer 140 may include other types of mass separator and analysis devices including, but not limited to, ion traps, orbitraps, ion mobility devices, time-of-flight (TOF) devices, or Fourier transform ion cyclotron resonance (FT-ICR) devices. In embodiments, mass filter 120 and mass analyzer 140 are respective examples of a first and a second mass separator, arranged in a series. A system may be configured according to the present disclosure with a quadrupole for the first mass separator, or mass filter 120, and a TOF device for the second mass separator, or mass analyzer 140. Each mass separator is configured to receive a set of ions, perform a detection of the set of ions, and generate a set of detection signals corresponding to detection of the set of ions.

[0043] Ion source device 110 transforms a sample or compounds of interest from a sample into an ion beam. Ion source device 110 can perform ionization techniques that include, but are not limited to, matrix assisted laser desorption / ionization (MALDI) or electrospray ionization (ESI).

[0044] Mass filter 120 receives the ion beam. In embodiments, mass filter 120 is configured by a user for a particular precursor ion transmission window based on the experimental goals for the sample being run. The precursor ion transmission window, as discussed herein, refers to the range of precursor or parent ions that are allowed to pass through a specific selection step and into the subsequent stages of mass analysis or fragmentation. In many tandem mass spectrometry (MS / MS) experiments, the precursor ions are first filtered based on their m / z (mass-to-charge ratio) in order to isolate a specific ion or group of ions of interest for further analysis or fragmentation. The precursor ion selection process employs a mass filter or a specific set of voltages thatallow only ions within a certain m / z range (the precursor ion transmission window) to pass through to the next stage.

[0045] Fragmentation device 130 of tandem mass spectrometer 102 fragments or transmits the precursor ions transmitted at each overlapping step by mass filter 120. In examples related to scanning DIA, one or more resulting product ions are produced for each overlapping window of the series. Fragmentation device 130 fragments the precursor ions when a collision energy high enough to fragment ions is used. Fragmentation device 130 transmits the precursor ions when a collision energy low enough not to fragment ions is used. As a result, the resulting product ions can include precursor ions.

[0046] In mass spectrometry, dissociation mechanisms are techniques used to fragment molecules into smaller pieces to facilitate their analysis and identification. For example, collision energy is used to influence the fragmentation of ions during collision-induced dissociation (CID) or collision-induced fragmentation (CIF). This process is commonly used in MS / MS to provide structural information about a molecule by inducing the dissociation of parent or precursor ions into fragment ions. The setting of the collision energy impacts the resulting fragmentation pattern and may influence how meaningful any acquired data is. Some other examples of dissociation mechanisms include electron transfer dissociation, electrospray ionization, matrix-assisted laser desorption / ionization, infrared multiphoton dissociation, and sustained off-resonance irradiation. Each dissociation method offers varying advantages depending on the type of analysis being performed and the nature of the sample. The choice of dissociation technique may impact the type of information obtained from mass spectrometric analysis.

[0047] Mass analyzer 140 of tandem mass spectrometer 102 detects intensities or counts for each of the one or more resulting product ions for each overlapping window of the series that form mass spectrum data for each overlapping window of the series.

[0048] Computing system 150 can be, but is not limited to, a computer, a microprocessor, the computing system of FIG. 8, or any device capable of sending and receiving control signals and data from a tandem mass spectrometer and processing data. Computing system 150 is in communication with ion source device 110, mass filter 120, fragmentation device 130, and mass analyzer 140. Computing system 150 is shown as a separate device but can be a processor or controller of tandem mass spectrometer 102 or another device. Computing system 150 may store in a memory device (not shown) massspectrum data for each precursor ion window analysis is performed for, including for each overlapping window of the series in examples performing scanning DIA.

[0049] In embodiments, computing system 150 instead performs an encoding and storing step, and encodes and stores each unique product ion detected by mass analyzer 140 in real-time during data acquisition. Prior to storing mass spectrum data, computing system 150 performs one or more processing steps on the raw mass spectrum data received to prepare the data for viewing, analysis, and storage. Raw mass spectrum data includes the counts or intensities of product ions at different m / z ratios over time. Computing system 150 may be further configured to retrieve stored mass spectrum data for subsequent, additional processing and analysis, and / or transmission to additional, remote, or otherwise separate computing systems.

[0050] FIG. 4 is block diagram of an example data processing system 200 for processing and quantifying mass spectrum data. Data processing system 200 is implemented, in embodiments, by computing system 150. Data processing system 200 may be among multiple subsystems or software executed by computing system 150 in operating mass spectrometer 102 and handling of data output by the mass spectrometer. The present disclosure is directed to data processing for quantification and analysis, but those of skill in the art will readily understand that other subsystems and / or modules may exist within and be executed by computing system 150. Computing system 150 is presented in examples herein as a single device, but in embodiments may be one or more processing devices networked or otherwise in communication. Functions may be divided among individual devices or shared across the collective processing capability of the one or more processing devices. In embodiments, data processing system 200 forms part of or serves as a controller. The controller may be configured to transmit operation commands to the mass spectrometer and / or to receive unprocessed mass data from second mass separator including the set of detection signals and perform one more data processing actions on the unprocessed mass data. In embodiments, data processing system 200 may be fully remote from and independent of the mass spectrometry system 100.

[0051] In the example of FIG. 4, data processing system 200 includes storage 204 and quantifier 210, which further includes target locator 212, relationship identifier 214, confidence measurer 216, and display 250. Data, including mass spectrometry data 202 and derivative processing outputs of mass spectrometry data 202, may be passed freelyamong the components of data processing system 200. Various outputs of the analysis and processing components may be stored in storage 204, or pass to display 250.

[0052] Storage 204 receives mass spectrometry data 202 from mass spectrometer 102 for storage. In embodiments, mass spectrometry data 202 may instead be received from a computing system, such as another computing system 150, and undergo processing and / or preprocessing before being received by storage 204. Mass spectrometry data 202 may be processed and encoded, including being compressed, prior to being received and stored at storage 204.

[0053] Quantifier 210 may receive mass spectrometry data 202 from storage 204, or from mass spectrometer 102 or another computing system, and quantify a target within the data. Quantifier 210 may further include target locator 212, relationship identifier 214, and confidence measurer 216 to perform operations as part of the quantification process. Quantifier 210 may further process quantification analysis and results for display on display 250 to provide a user visualization of the quantification analysis and results.

[0054] Target locator 212 defines a target location in terms of the dimensions of the mass spectrometry data 202. Target locator 212 further defines a range for analysis including the target location, including defining the range in terms of the MS2 dimension.

[0055] Relationship identifier 214 defines precursor relationship between fragments in the MS2 dimension and precursor ions in the QI dimensions. Relationship identifier further characterizes a precursor relationship as a target relationship when the precursor ions of the relationship coincides with the target location.

[0056] Confidence measurer 216 generates a confidence measure of a likelihood of accuracy of quantifications calculated. Confidence measurer 216 further determines and applies weights to fragment intensities based on their likelihood of association with the target location. Confidence measurer 216 may have one or more modules for different confidence measures.

[0057] Referring now to FIG. 5, a flowchart of an example method 300 of quantifying an ion species using a mass spectrometer is shown. Method 300 may be executed by a computing device 150 or may be executed by a separate or integrated processing system independent of computing device 150.

[0058] At operation 302, a mass spectrum dataset including one or more precursor ions and one or more fragments is obtained. In embodiments, each of the one or more precursor ions is associated with a location. As discussed herein, a location refers to oneor more coordinates defining that target is relation to one or more dimensions of the data. In examples, the location is a mass of a target ion, an appearance time of the target ion, or an ion mobility of the target ion.

[0059] In embodiments, the mass spectrum data set is obtained using a tandem mass spectrometer. In examples, data associated with the one or more precursors originates from a first mass spectrometer of the tandem mass spectrometer. For example, the first mass spectrometer is a quadrupole. In further examples, data associated with the one or more fragments originates from a second mass spectrometer of the tandem mass spectrometer. For example, the second mass spectrometer is a time of flight mass spectrometer.

[0060] At operation 304, an abundance of the target ion in the mass spectrum dataset is quantified. In example method 300, the quantification of the target includes the operations 306-316.

[0061] At operation 306, a target is identified by location. The target may generally refer to a particular target ion of the species to be quantified. At operation 308, a range, including the location, is analyzed to output a set of the one or more precursor ions associated with the range. As discussed herein, a range refers to a defined portion of one or more dimensions of the mass spectra data including a target’s location. In embodiments, the range is a mass range or a time range. In embodiments, the target is a subset of the set of the one or more precursor ions associated with the range.

[0062] Analyzing the range may be performed by scanning a filter window with a dynamic width across the range. In embodiments, analyzing the range is performed by scanning a filter window of a fixed width across the range. Scanning the filter window across the mass range may be executed with the filter window being moved across the mass range in a fixed step progression. In embodiments, each subsequent filter window in the fixed step progression shares an overlap with at least one preceding filter window. Scanning the filter window across the mass range may include the filter window being moved across the mass range at a dynamic rate. Scanning the filter window may refer to how the data is obtained and / or data processing performed on data post-acquisition.

[0063] At operation 310, a set of the one or more ion fragments associated with the range is analyzed. In embodiments, analysis of the ion fragments includes correlating each or a subset of the fragments with a parent ion in a precursor relationship such that the subset of the ion fragments are defined as daughter ions to an associated parent ions. Atoperation 312, a target relationship is determined to exist in association with at least one of the one or more ion fragments. In embodiments, the target relationship is a precursor relationship between at least one of the one or more fragments and the target.

[0064] At operation 314, an intensity of the at least one of the one or more fragments is determined. At operation 316, the target is quantified using the intensity of the at least one of the one or more fragments and the target relationship. At operation 318, a confidence measure is determined for the quantifying. In embodiments, the confidence measure may be excluded from the process. As discussed herein, the confidence measure refers to a likelihood of accuracy of the target relationship. In embodiments, calculating the likelihood of accuracy of the target relationship includes determining a weighted intensity of the one or more fragments. In some cases, the weighted intensity is executed by applying a weight to each intensity of the one or more fragments based on the target relationship.

[0065] Referring now to FIG. 6, a flowchart of an example method 400 of determining a confidence score when quantifying an ion species using mass spectroscopy is shown. Method 400 may be executed by a computing device 150 or may be executed by a separate or integrated processing system independent of computing device 150. In examples, the method 400 coincides with operation 318 of method 300 of FIG. 5. In embodiments, method 400 is executed either in sequence, in parallel, or independently of the quantification method 300.

[0066] At operation 402, a mass spectrum dataset including one or more precursor ions and one or more fragments is obtained. In embodiments, each of the one or more precursor ions is associated with a location. At operation 404, the confidence score for quantifying an abundance of a target ion in the mass spectrum dataset is determined. In example method 404, the quantification of the target includes the operations 406-414.

[0067] At operation 406, a target is identified by location. The target may generally refer to a particular target ion of the species to be quantified. As discussed herein, a location refers to one or more coordinates defining that target is relation to one or more dimensions of the data. In examples, the location is a mass of a target ion, an appearance time of the target ion, or an ion mobility of the target ion. At operation 408, a range including the location is analyzed to output a set of the one or more precursor ions associated with the range. In embodiments, the target is a subset of the set of the one or more precursor ions.

[0068] At operation 410, a set of the one or more ion fragments associated with the range is analyzed. At operation 412, a target relationship is determined to exist in association with at least one of the one or more ion fragments. In embodiments, the target relationship is a precursor relationship between at least one of the one or more fragments and the target. At operation 414, a weighted intensity of the one or more fragments is determined by applying a weight to each intensity of the one or more fragments based on the target relationship. At operation 416, the method optionally extends to quantifying the target ion using the weighted intensity of the at least one of the one or more fragments.

[0069] Referring now to FIG. 7, a flowchart of another example method 500 of determining a confidence score when quantifying an ion species using mass spectroscopy is shown. In embodiments, the method 500 may preferably be executed is direct sequence with obtaining a mass spectrum data set using a mass spectrometer. For example, method 500 may be performed in real-time on a mass spectroscopy systems, such as system 100 of FIG. 3

[0070] As operation 502, a target is identified by location. The target may generally refer to a particular target ion of the species to be quantified. As discussed herein, a location refers to one or more coordinates defining that target is relation to one or more dimensions of the data. In examples, the location is a mass of a target ion, an appearance time of the target ion, or an ion mobility of the target ion. At operation 504, a mass range including the location is filtered to output one or more precursor ions. In embodiments, the target ion is a subset of the set of the one or more precursor ions. At operation 506, at least one of the one or more precursor ions is fragmented to output one or more ion fragments. At operation 508, an intensity of one or more ion fragments is measured.

[0071] At operation 510, a target relationship is determined to exist in association with at least one of the one or more ion fragments. In embodiments, the target relationship is a precursor relationship between at least one of the one or more fragments and the target. At operation 512, a weighted intensify of the one or more fragments is determined by applying a weight to each intensity of the one or more fragments based on the target relationship. At operation 514, the confidence measure is determined using the weighted intensify and the target relationship.

[0072] Referring now to FIG. 8, the example computing system 150 includes one or more processors 152, a system memory 158, and a system bus 172 that couples the system memory 158 to the one or more processors 152. The system memory 158 includes RAM(Random Access Memory) 161 and ROM (Read-Only Memory) 162. A basic input / output system that contains the basic routines that help to transfer information between elements within the computing system 150, such as during startup, is stored in the ROM 162. The computing system 150 further includes a mass storage device 164. The mass storage device 164 is able to store software instructions and data. Mass storage device 164 may correspond to storage 204 of FIG. 4. The one or more processors 152 can be one or more central processing units or other processors.

[0073] The mass storage device 164 is connected to the one or more processors 152 through a mass storage controller (not shown) connected to the system bus 172. The mass storage device 164 and its associated computer-readable data storage media provide nonvolatile, non-transitory storage for the computing system 150. Although the description of computer-readable data storage media contained herein refers to a mass storage device, such as a hard disk or solid state disk, it should be appreciated by those skilled in the art that computer-readable data storage media can be any available non-transitory, physical device or article of manufacture from which the central display station can read data and / or instructions.

[0074] Computer-readable data storage media include volatile and non-volatile, removable, and non-removable media implemented in any method or technology for storage of information such as computer-readable software instructions, data structures, program modules, or other data. Example types of computer-readable data storage media include, but are not limited to, RAM, ROM, EPROM, EEPROM, flash memory or other solid state memory technology, CD-ROMs, DVD (Digital Versatile Discs), other optical storage media, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by the computing system 150.

[0075] According to various embodiments of the invention, the computing system 150 may operate in a networked environment using logical connections to remote network devices through the network 148. The network 148 is a computer network, such as an enterprise intranet and / or the Internet. The network 148 can include a LAN, a Wide Area Network (WAN), the Internet, wireless transmission mediums, wired transmission mediums, other networks, and combinations thereof. The computing system 150 may connect to the network 148 through a network interface unit 154 connected to the system bus 172. It should be appreciated that the network interface unit 154 may also be utilizedto connect to other types of networks and remote computing systems. The computing system 150 also includes an input / output controller 156 for receiving and processing input from a number of other devices, including a touch user interface display screen, or another type of input device. Similarly, the input / output controller 156 may provide output to a touch user interface display screen or other type of output device.

[0076] As mentioned briefly above, the mass storage device 164 and the RAM 161 of the computing system 150 can store software instructions and data. The software instructions include an operating system 168 suitable for controlling the operation of the computing system 150. The mass storage device 164 and / or the RAM 161 also store software instructions, that when executed by the one or more processors 152, cause one or more of the systems, devices, or components described herein to provide functionality described herein. For example, the mass storage device 164 and / or the RAM 161 can store software instructions that, when executed by the one or more processors 152, cause the computing system 150 to receive and execute managing network access control and build system processes.

[0077] The software instructions further include one or more software applications 166. Software applications may include dedicated systems and algorithms for performing specific tasks or actions or providing specific interfaces. One or more of data processing system 200 and / or one or more component of data processing system 200 may be encompassed by software applications 166.

[0078] Illustrative examples of the systems and methods described herein are provided below. An embodiment of the system or method described herein may include any one or more, and any combination of, the clauses described below.

[0079] Aspect 1. A method of quantifying an ion species using a mass spectrometer, the method including: obtaining a mass spectrum dataset including one or more precursor ions and one or more fragments, each of the one or more precursor ions associated with a location; quantifying an abundance of a target ion in the mass spectrum dataset by: identifying the location of the target ion; analyzing a range including the location to output a set of the one or more precursor ions associated with the range, wherein the target ion is a subset of the set of the one or more precursor ions; analyzing a set of the one or more ion fragments associated with the range; determining a target relationship, wherein the target relationship is a precursor relationship between at least one of the one or more fragments and the target ion; determining an intensity of the at least one of theone or more fragments; and quantifying the target ion using the intensity of the at least one of the one or more fragments and the target relationship.

[0080] Aspect 2. The method of aspect 1, wherein the location of the target ion includes one of a mass of the target ion and an appearance time of the target ion and ion mobility of the target ion.

[0081] Aspect 3. The method of aspect 2, wherein the range is at least one of a mass range and a time range.

[0082] Aspect 4. The method of aspect 1, further including determining a confidence measure for the quantifying.

[0083] Aspect 5. The method of aspect 4, wherein determining the confidence measure includes calculating a likelihood of accuracy of the target relationship.

[0084] Aspect 6. The method of aspect 5, wherein calculating the likelihood of accuracy of the target relationship includes determining a weighted intensity of the one or more fragments.

[0085] Aspect 7. The method of aspect 6, wherein the weighted intensity includes applying a weight to each intensity of the one or more fragments based on the target relationship.

[0086] Aspect 8. The method of aspect 3, wherein analyzing the range is performed by scanning a filter window of a fixed width across the range.

[0087] Aspect 9. The method of aspect 8, wherein scanning the filter window across the mass range includes the filter window being moved across the mass range in a fixed step progression.

[0088] Aspect 10. The method of aspect 9, wherein each subsequent filter window in the fixed step progression shares an overlap with at least one preceding filter window.

[0089] Aspect 11. The method of aspect 8, wherein scanning the filter window across the mass range comprises the filter window being moved across the mass range at a dynamic rate.

[0090] Aspect 12. The method of aspect 1, wherein analyzing the range is performed by scanning a filter window with a dynamic width across the range.

[0091] Aspect 13. The method of aspect 1, wherein data associated with the one or more precursors originates from a first mass spectrometer of a tandem mass spectrometer.

[0092] Aspect 14. The method of aspect 13, wherein the first mass spectrometer is a quadrupole.

[0093] Aspect 15. The method of aspect 13 , wherein data associated with the one or more fragments originates from a second mass spectrometer of the tandem mass spectrometer.

[0094] Aspect 16. The method of aspect 15, wherein the second mass spectrometer is a time of flight mass spectrometer.

[0095] Aspect 17. The method of aspect 1, further including deconvoluting the mass spectrum dataset.

[0096] Aspect 18. The method of aspect 17, wherein deconvoluting the mass spectrum dataset includes deconvoluting the location.

[0097] Aspect 19. The method of claim 17, wherein deconvoluting the mass spectrum dataset includes deconvoluting at least one of the one or more fragments.

[0098] Aspect 20. A method of determining a confidence score when quantifying an ion species using mass spectroscopy, the method including: obtaining a mass spectrum dataset including one or more precursor ions and one or more fragments, each of the one or more precursor ions association with a location; determining the confidence score for quantifying an abundance of a target ion in the mass spectrum dataset by: identifying the location of the target ion to be quantified; analyzing a range including the location to output a set of the one or more precursor ions associated with the range, wherein the target ion is a subset of the set of the one or more precursor ions; analyzing a set of the one or more ion fragments associated with the range; determining a target relationship, wherein the target relationship is a precursor relationship between at least one of the one or more fragments and the target ion; and determining a weighted intensity of the one or more fragments, wherein the weighted intensity comprises applying a weight to each intensity of the one or more fragments based on the target relationship.

[0099] Aspect 21. The method of aspect 20, further including quantifying the target ion using the weighted intensity of the at least one of the one or more fragments.

[0100] Aspect 22. A method of determining a confidence score when quantifying an ion species using mass spectroscopy, the method including: identifying a location of a target ion to be quantified; filtering across a mass range including the location to output one or more precursor ions, wherein the target ion is a subset of the set of the one or more precursor ions; fragmenting at least one of the one or more precursor ions to output one or more ion fragments; measuring an intensity of one or more ion fragments; determining a target relationship, wherein the target relationship is a precursor relationship between at least one of the one or more fragments and the target ion; determining a weightedintensity of the one or more fragments, wherein the weighted intensity includes applying a weight to each intensity of the one or more fragments based on the target relationship; and calculating the confidence score using the weighted intensity and the target relationship.

[0101] Aspect 23. A system for quantifying an ion species using a mass spectrometer, the system including: a tandem mass spectrometer including: a first mass spectrometer configured for filtering across a mass range including a location of the ion species to output one or more precursor ions; a second mass spectrometer configured for measuring an intensity of one or more ion fragments resulting from the one or more precursor ions; and a computing device, in communication with the tandem mass spectrometer, configured for: defining a target relationship, wherein the target relationship is a precursor relationship between at least one of the one or more fragments and the target ion; calculating a likelihood of accuracy of the target relationship; and quantifying the target ion using a weighted intensity of the one or more fragments and the target relationship.

[0102] Aspect 24. A method of quantifying an ion species using a mass spectrometer, the method including: identifying a location of a target ion to be quantified; analyzing a range including the location to output one or more precursor ions, wherein the target ion is a subset of the one or more precursor ions; fragmenting the one or more precursor ions to output one or more ion fragments; measuring an intensity of each of the one or more ion fragments; and determining a precursor relationship between at least one of the one or more fragments and the target ion; quantifying the target ion using the intensity of the at least one of the one or more fragments.

[0103] Having described the preferred aspects and implementations of the present disclosure, modifications and equivalents of the disclosed concepts may readily occur to one skilled in the art. However, it is intended that such modifications and equivalents be included within the scope of the claims which are appended hereto.

Claims

1. What is claimed is:

1. A method of quantifying an ion species using a mass spectrometer, the method comprising:obtaining a mass spectrum dataset including one or more precursor ions and one or more fragments, each of the one or more precursor ions associated with a location;quantifying an abundance of a target ion in the mass spectrum dataset by:identifying the location of the target ion;analyzing a range including the location to output a set of the one or more precursor ions associated with the range, wherein the target ion is a subset of the set of the one or more precursor ions;analyzing a set of the one or more ion fragments associated with the range; determining a target relationship, wherein the target relationship is a precursor relationship between at least one of the one or more fragments and the target ion;determining an intensity of the at least one of the one or more fragments; andquantifying the target ion using the intensity of the at least one of the one or more fragments and the target relationship.

2. The method of claim 1, wherein the location of the target ion comprises one of a mass of the target ion and an appearance time of the target ion and ion mobility of the target ion.

3. The method of claim 2, wherein the range is at least one of a mass range and a time range.

4. The method of claim 1 , further comprising determining a confidence measure for the quantifying.

5. The method of claim 4, wherein determining the confidence measure comprises calculating a likelihood of accuracy of the target relationship.

6. The method of claim 5, wherein calculating the likelihood of accuracy of the target relationship includes determining a weighted intensity of the one or more fragments.

7. The method of claim 6, wherein the weighted intensity comprises applying a weight to each intensity of the one or more fragments based on the target relationship.

8. The method of claim 3, wherein analyzing the range is performed by scanning a filter window of a fixed width across the range.

9. The method of claim 8, wherein scanning the filter window across the mass range comprises the filter window being moved across the mass range in a fixed step progression.

10. The method of claim 9, wherein each subsequent filter window in the fixed step progression shares an overlap with at least one preceding filter window.

11. The method of claim 8, wherein scanning the filter window across the mass range comprises the filter window being moved across the mass range at a dynamic rate.

12. The method of claim 1, wherein analyzing the range is performed by scanning a filter window with a dynamic width across the range.

13. The method of claim 1, wherein data associated with the one or more precursors originates from a first mass spectrometer of a tandem mass spectrometer.

14. The method of claim 13, wherein data associated with the one or more fragments originates from a second mass spectrometer of the tandem mass spectrometer.

15. The method of claim 14, wherein the first mass spectrometer is a quadrupole and the second mass spectrometer is a time of flight mass spectrometer.

16. The method of claim 1, further comprising deconvoluting the mass spectrum dataset.

17. The method of claim 16, wherein deconvoluting the mass spectrum dataset comprises deconvoluting the location.

18. The method of claim 16, wherein deconvoluting the mass spectrum dataset comprises deconvoluting at least one of the one or more fragments.

19. A method of determining a confidence score when quantifying an ion species using mass spectroscopy, the method comprising:obtaining a mass spectrum dataset including one or more precursor ions and one or more fragments, each of the one or more precursor ions association with a location;determining the confidence score for quantifying an abundance of a target ion in the mass spectrum dataset by:identifying the location of the target ion to be quantified; analyzing a range including the location to output a set of the one or more precursor ions associated with the range, wherein the target ion is a subset of the set of the one or more precursor ions;analyzing a set of the one or more ion fragments associated with the range; determining a target relationship, wherein the target relationship is a precursor relationship between at least one of the one or more fragments and the target ion; anddetermining a weighted intensity of the one or more fragments, wherein the weighted intensity comprises applying a weight to each intensity of the one or more fragments based on the target relationship.

20. The method of claim 19, further comprising quantifying the target ion using the weighted intensify of the at least one of the one or more fragments.

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