EP4652623A2 - System for generating gel-lane plots highlighting deconvoluted masses - Google Patents

Abstract

Disclosed herein are scientific instrument support systems, as well as related methods, computing devices, and computer-readable media. For example, in some embodiments, a mass spectrometry instrument support apparatus may include: first logic to receive a plurality of sample data from a queue; second logic to generate, based on the sample data, a gel-lane plot comprising a stacked column of gel spots where the y-axis represents is the mass, and the x-axis is discretized into a single sample or run; third logic to regularize the y-axis to the sample data by employing a clustering technique (e.g., including a high-resolution clustering algorithm and/or a low-resolution version) to mass cluster the sample data; and fourth logic to provide the gel-lane plot for display showing the deconvoluted mass spectra results for samples.

Description

SYSTEM FOR GENERATING GEL-LANE PLOTS HIGHLIGHTING DECONVOLUTED MASSES

Cross-Reference to Related Application

[0001] This application claims priority to U.S. Provisional No. 63/480,059, filed on January 16, 2023, titled “SYSTEM FOR GENERATING GEL-LANE PLOTS HIGHLIGHTING DECONVOLUTED MASSES,” the entire content of which is incorporated herein by reference.

Background

[0002] Chromatography is a technique for the separation of constituents of a sample mixture that utilizes the differing properties of the constituents as they interact with other materials. Mass spectrometry is a technique for detecting, identifying, and quantifying molecules within samples based on their molecular mass-to-charge ratio after ionization.

Brief Description of the Drawings

[0003] Embodiments will be readily understood by the following detailed description in conjunction with the accompanying drawings. To facilitate this description, like reference numerals designate like structural elements. Embodiments are illustrated by way of example, not by way of limitation, in the figures of the accompanying drawings. [0004] FIG. 1 is a block diagram of an example mass spectrometry instrument support module for determining peak locations for a mass spectrometry data set, in accordance with various embodiments.

[0005] FIG. 2 is a flow diagram of an example method to perform support operations, in accordance with various embodiments.

[0006] FIG. 3 is an example of a graphical user interface that may be used in the performance of some or all of the support methods disclosed herein, in accordance with various embodiments.

[0007] FIG. 4 is a block diagram of an example computing device that may perform some or all of the mass spectrometry instrument support methods disclosed herein, in accordance with various embodiments.

[0008] FIG. 5 is a block diagram of an example scientific instrument support system in which some or all of the scientific instrument support methods disclosed herein may be performed, in accordance with various embodiments.

[0009] FIG. 6 illustrates an example gel-lane plot for multiple samples, in accordance with various ones of the embodiments disclosed herein.

[0010] FIG. 7 illustrates an example graphic to indicate the quality and purity of samples, in accordance with various ones of the embodiments disclosed herein.

Detailed Description

[0011] Disclosed herein are scientific instrument support systems, as well as related methods, computing devices, and computer-readable media. For example, in some embodiments, a mass spectrometry instrument support apparatus may include: first logic to receive a plurality of sample data from a queue; second logic to generate, based on the sample data, a gel-lane plot comprising a stacked column of gel spots where the y-axis represents the mass (e.g., has units of mass, mass over charge (m/z), or another mass-related unit), and the x-axis is discretized into a single sample or run; third logic to regularize the y-axis to the sample data by employing a clustering technique (including, e.g., a high-resolution clustering algorithm and/or a low-resolution version) to mass cluster the sample data; and fourth logic to provide the gel-lane plot for display showing the deconvoluted mass spectra results for samples.

[0012] A “Gel-Lane” plot is particularly useful when looking at deconvoluted masses from either a single sample or across many samples. A gel lane generally includes a stacked column of “gel spots” (horizontal lines) where the y-axis is the mass, and the x-axis is discretized into a single sample or run (e.g., so that different regions of the x-axis correspond to different samples or runs). Several gel lanes (e.g., one per sample or run) can be laid out side-by-side horizontally allowing for cross sample comparisons on a single page (or view). In some embodiments, the described system transforms the x-axis for the y-axis to allow for more masses to be visible on a page (less data loss) because there are more pixels available per page. This favors mass over intensity (a strong point of mass spectrometers).

[0013] Mass spectra (m/z vs intensity) have a m/z axis (mass/charge) rather than a simple mass axis. In some embodiments, a mass axis may be more consumable because the mass is the chemical property that connects the analyte measurement to the actual compound analyte. A typical deconvoluted mass spectra (mass versus intensity) consumes a full, or partial page, and is not amenable for visually comparing across or between samples. Comparing multiple spectra at once is a historical problem and often done by either stacking up the plots vertically, one above another on a page, or a waterfall arrangement where spectra are offset diagonally and placed on top of each other.

[0014] Moreover, stacking up the plots, one above each other, places the mass axis on the horizontal axis which generally has less pixels per page than the vertical axis. This compresses a high-resolution axis of masses into a smaller number of pixels resulting in data loss. This is particularly bad for large intact molecules where the masses can range from 50-1 ,000,000 Da or more. This happens if there are multiple plots stacked or a single figure. To decrease x-axis compression, mass spectra are often printed in landscape mode. Overlapping spectra in a waterfall plot scenario works if the data is simple but quickly get noisy as the number of features increases. Noisy data that oscillated from run to run also led to excessively cluttered plots with little benefit.

[0015] In some embodiments, intensity information is displayed by coloring the “gel spot” to represent the abundance associated with the spot. The term “intensity,” as used herein, may refer to the height of a peak in a m/z spectrum, the actual amount of an analyte as represented by its deconvoluted mass (sometimes referred to as abundance, and which may be derived from the sum of the intensities of multiple m/z peaks in the same spectrum), a relative peak height or analyte abundance (e.g., as shown in the example of FIG. 6), or any related quantity indicative of the magnitude of an indicator of a present analyte. In this scenario, darker is more abundant and the colors range from dark or light. In other scenarios, a larger range of colors can be used if multiple colors are used (e.g., green to red). To aid in the consumption, a blocked legend can be used representing, for example, four shades of color indicating four different ranges of intensities. Intensities can be plotted directly in a compressed form (e.g., log form or Iog10 form etc.)

[0016] Generating these plots requires that the data be mass clustered together to regularizing the y-axis to all of the sample data and making sure the pixels for data spots is not lost during pixel reduction. High- and low-resolution mass spectra may employ different algorithms. Accordingly, the system may employ a high-resolution clustering algorithm and/or a low-resolution version to improve performance. Any suitable clustering algorithms may be used for clustering; examples may include k-means clustering or k-nearest neighbors clustering.

[0017] By plotting the gel lanes horizontally across the page, the masses of interest can be highlighted by drawing a highlight line (e.g., yellow) or a box around a given mass. This method allowed for the display of theoretical masses in a directed experiment where theoretical masses and experimental masses are compared.

[0018] Accordingly, the described system provides for displaying deconvoluted mass spectra results in a compact, easy to consume method that resembles electrophoresis gels and allows for unprecedented resolution and expanded dynamic range of intensities Typical gel-electrophoresis display masses with thousands of Daltons accuracy while mass spectrometers can accurately measure down to sub-Dalton accuracy for highly resolved data and up to tens of Daltons for poorly resolved data. The dynamic range of detectable intensities is far improved with the mass spectrometer. In addition to the gel lanes, the system includes graphics to indicate instrument performance (QC) and overall samples quality and purity (red/yellow, green stoplight). This provides all the high level, actionable data in one figure. The gel-lane plots disclosed herein are more readily comprehensible by scientists who are not experts in mass spectrometry, improving the ease of use and accurate interpretation of data for mass spectrometry systems and thereby accelerating scientific analysis. The gel-lane plots disclosed herein may be particularly valuable in applications in which many samples are screened, such as drug binding or other molecular binding studies. For example, in molecular binding studies, the gel-lane plots disclosed herein may visually represent molecular binding between 2 or more compounds or elements by depicting the drug bound to the protein and the unbound drug and/or unbound protein as 2 or 3 gel lines.

[0019] In the following detailed description, reference is made to the accompanying drawings that form a part hereof wherein like numerals designate like parts throughout, and in which is shown, by way of illustration, embodiments that may be practiced. It is to be understood that other embodiments may be utilized, and structural or logical changes may be made, without departing from the scope of the present disclosure. Therefore, the following detailed description is not to be taken in a limiting sense.

[0020] Various operations may be described as multiple discrete actions or operations in turn, in a manner that is most helpful in understanding the subject matter disclosed herein. However, the order of description should not be construed as to imply that these operations are necessarily order dependent. In particular, these operations may not be performed in the order of presentation. Operations described may be performed in a different order from the described embodiment. Various additional operations may be performed, and/or described operations may be omitted in additional embodiments.

[0021] For the purposes of the present disclosure, the phrases “A and/or B” and “A or B” mean (A), (B), or (A and B). For the purposes of the present disclosure, the phrases "A, B, and/or C” and "A, B, or C” mean (A), (B), (C), (A and B), (A and C), (B and C), or (A, B, and C). Although some elements may be referred to in the singular (e.g., "a processing device”), any appropriate elements may be represented by multiple instances of that element, and vice versa. For example, a set of operations described as performed by a processing device may be implemented with different ones of the operations performed by different processing devices

[0022] The description uses the phrases "an embodiment,” “various embodiments,” and “some embodiments,” each of which may refer to one or more of the same or different embodiments. Furthermore, the terms “comprising,” “including,” “having,” and the like, as used with respect to embodiments of the present disclosure, are synonymous. When used to describe a range of dimensions, the phrase “between X and Y” represents a range that includes X and Y. As used herein, an “apparatus” may refer to any individual device, collection of devices, part of a device, or collections of parts of devices. The drawings are not necessarily to scale.

[0023] FIG. 1 is a block diagram of a mass spectrometry instrument support module 1000 to display of theoretical masses in a directed experiment where theoretical masses and experimental masses are compared. The mass spectrometry instrument support module 1000 may be implemented by circuitry (e.g., including electrical and/or optical components), such as a programmed computing device. The logic of the mass spectrometry instrument support module 1000 may be included in a single computing device or may be distributed across multiple computing devices that are in communication with each other as appropriate. Examples of computing devices that may, singly or in combination, implement the mass spectrometry instrument support module 1000 are discussed herein with reference to the computing device 4000 of FIG. 4, and examples of systems of interconnected computing devices, in which the mass spectrometry instrument support module 1000 may be implemented across one or more of the computing devices, is discussed herein with reference to the mass spectrometry instrument support system 5000 of FIG. 5. The mass spectrometry instrument support module 1000 may include sample receiving logic 1002, gel-lane plot generating logic 1004, regularizing logic 1006, and displaying logic 1008.

[0024] As used herein, the term “logic” may include an apparatus that is to perform a set of operations associated with the logic. For example, any of the logic elements included in the support module 1000 may be implemented by one or more computing devices programmed with instructions to cause one or more processing devices of the computing devices to perform the associated set of operations. In a particular embodiment, a logic element may include one or more non-transitory computer-readable media having instructions thereon that, when executed by one or more processing devices of one or more computing devices, cause the one or more computing devices to perform the associated set of operations. As used herein, the term “module” may refer to a collection of one or more logic elements that, together, perform one or more functions associated with the module. Different ones of the logic elements in a module may take the same form or may take different forms. For example, some logic in a module may be implemented by a programmed general-purpose processing device, while other logic in a module may be implemented by an application-specific integrated circuit (ASIC). In another example, different ones of the logic elements in a module may be associated with different sets of instructions executed by one or more processing devices. A module may not include all of the logic elements depicted in the associated drawing; for example, a module may include a subset of the logic elements depicted in the associated drawing when that module is to perform a subset of the operations discussed herein with reference to that module.

[0025] The sample receiving logic 1002 may be configured to receive a sample or number of samples from a queue. The sample receiving logic 1002 may receive samples on a regular chronological schedule (e.g., a set number of seconds or minutes), after a certain number of samples accumulate in the queue (e.g., 20), in accordance with any other suitable schedule, or at the command of a user (e.g., received via a GUI, such as the GUI 3000 of FIG. 3).

[0026] The gel-lane plot generating logic 1004 may be configured to generate, based on the sample data, a gel-lane plot comprising a stacked column of gel spots where the y-axis represents the mass, and the x-axis is discretized into a single sample or run.

[0027] The regularizing logic 1006 may be configured to regularize the y-axis to the sample data by employing a clustering technique (including, e.g., a high-resolution clustering algorithm and/or a low-resolution version) to mass cluster the sample data. In some examples, intensity information from the sample data is highlighted by applying a color to the gel spots. In some embodiments, regularizing the y-axis to the sample data ensures that the pixels for data spots are not lost during pixel reduction

[0028] The displaying logic 1008 may provide to a user, through a GUI (such as the GUI 3000 of FIG. 3), the gellane plot showing the deconvoluted mass spectra results for samples or select a sample from the queue for the sample receiving logic 1002. In some cases, the gel-lane plot shows cross sample comparisons on a single page or view. In some cases, displaying the gel-lane plot increasing the number of available page pixels and decrease data loss. In some cases, graphics to indicate instrument performance (QC) and an overall quality and purity of the samples are also provide to the user through the GUI. In some cases, display of the gel-lane plot allows the user to compare to theoretical masses and experimental masses of the samples.

[0029] FIG. 6 illustrates an example gel-lane plot for multiple samples, in accordance with various ones of the embodiments disclosed herein. In the example of FIG. 6, different shades of gray are used to indicate intensity, but as noted above, different colors may be used analogously. In the example of FIG. 6, a highlight box or line is shown around a particular mass (466 kDa) to enable comparison of theoretical masses and experimental masses. As illustrated in the gel-lane plot of FIG 6, “white space" is present along the y-axis between the observed masses, analogous to the result in a chemical gel experiment. Many conventional ways of depicting mass spectrometry results represents “compressed” plots in which only the detected masses are listed or otherwise identified. The unconventional presence of the white space in the gel-lane plots disclosed herein may aid the user, who may not be an expert in mass spectrometry, in quickly understanding and interpreting mass spectrometry results. FIG. 7 illustrates an example graphic to indicate the quality and purity of the samples; the coloring of the graphic of FIG. 7 could take the form of a red, yellow, green stoplight system, or another form as suitable.

[0030] FIG. 2 is a flow diagram of a method 2000 of performing support operations, in accordance with various embodiments. Although the operations of the method 2000 may be illustrated with reference to particular embodiments disclosed herein (e.g., the scientific instrument support modules 1000 discussed herein with reference to FIG. 1 , the GUI 3000 discussed herein with reference to FIG. 3, the computing devices 4000 discussed herein with reference to FIG. 4, and/or the scientific instrument support system 5000 discussed herein with reference to FIG. 5), the method 2000 may be used in any suitable setting to perform any suitable support operations. Operations are illustrated once each and in a particular order in FIG. 2, but the operations may be reordered and/or repeated as desired and appropriate (e.g., different operations performed may be performed in parallel, as suitable).

[0031] At 2002, first operations may be performed. For example, the sample receiving logic 1002 of the support module 1000 may perform the operations of 2002. The first operations may include receiving a plurality of sample data from a queue.

[0032] At 2004, second operations may be performed. For example, method and gel-lane plot generating logic 1004 of the support module 1000 may perform the operations of 2004. The second operations may include generating, based on the sample data, a gel-lane plot comprising a stacked column of gel spots where the y-axis represents the mass, and the x-axis is discretized into a single sample or run.

[0033] At 2006, third operations may be performed For example, the regularizing logic 1006 of the support module 1000 may perform the operations of 2006. The third operations may include processing the sample by regularizing the y-axis to the sample data by employing a clustering technique (e.g., including a high-resolution clustering algorithm and/or a low-resolution version) to mass cluster the sample data.

[0034] At 2008, fourth operations may be performed. For example, the displaying logic 1008 of the support module 1000 may perform the operations of 2008. The fourth operations may include providing the gel-lane plot for display showing the deconvoluted mass spectra results for samples.

[0035] The scientific instrument support methods disclosed herein may include interactions with a human user (e.g., via the user local computing device 5020 discussed herein with reference to FIG. 5). These interactions may include providing information to the user (e.g., information regarding the operation of a scientific instrument such as the scientific instrument 5010 of FIG. 5, information regarding a sample being analyzed or other test or measurement performed by a scientific instrument, information retrieved from a local or remote database, or other information) or providing an option for a user to input commands (e.g., to control the operation of a scientific instrument such as the scientific instrument 5010 of FIG. 5, or to control the analysis of data generated by a scientific instrument), queries (e.g., to a local or remote database), or other information. In some embodiments, these interactions may be performed through a graphical user interface (GUI) that includes a visual display on a display device (e.g., the display device 4010 discussed herein with reference to FIG. 4) that provides outputs to the user and/or prompts the user to provide inputs (e.g., via one or more input devices, such as a keyboard, mouse, trackpad, or touchscreen, included in the other I/O devices 4012 discussed herein with reference to FIG. 4). The scientific instrument support systems disclosed herein may include any suitable GUIs for interaction with a user. [0036] FIG. 3 depicts an example GUI 3000 that may be used in the performance of some or all of the support methods disclosed herein, in accordance with various embodiments. As noted above, the GUI 3000 may be provided on a display device (e.g., the display device 4010 discussed herein with reference to FIG. 4) of a computing device (e.g., the computing device 4000 discussed herein with reference to FIG. 4) of a scientific instrument support system (e.g., the scientific instrument support system 5000 discussed herein with reference to FIG. 5), and a user may interact with the GUI 3000 using any suitable input device (e.g., any of the input devices included in the other I/O devices 4012 discussed herein with reference to FIG. 4) and input technique (e.g., movement of a cursor, motion capture, facial recognition, gesture detection, voice recognition, actuation of buttons, etc.).

[0037] The GUI 3000 may include a data display region 3002, a data analysis region 3004, a scientific instrument control region 3006, and a settings region 3008. The particular number and arrangement of regions depicted in FIG. 3 is simply illustrative, and any number and arrangement of regions, including any desired features, may be included in a GUI 3000.

[0038] The data display region 3002 may display data generated by a scientific instrument (e.g., the scientific instrument 5010 discussed herein with reference to FIG. 5). The data analysis region 3004 may display the results of data analysis (e.g., the results of analyzing the data illustrated in the data display region 3002 and/or other data). For example, the resulting gel-lane plot of the regularizing logic 1006 of the support module 1000 may be provide to a user. In some embodiments, the data display region 3002 and the data analysis region 3004 may be combined in the GUI 3000 (e.g., to include data output from a scientific instrument, and some analysis of the data, in a common graph or region).

[0039] The scientific instrument control region 3006 may include options that allow the user to control a scientific instrument (e.g., the scientific instrument 5010 discussed herein with reference to FIG. 5). For example, the data display region 3002 may provide to a user an option to select sample data from a queue for the receiving logic 1002 of the support module 1000.

[0040] The settings region 3008 may include options that allow the user to control the features and functions of the GUI 3000 (and/or other GUIs) and/or perform common computing operations with respect to the data display region 3002 and data analysis region 3004 (e.g., saving data on a storage device, such as the storage device 4004 discussed herein with reference to FIG. 4, sending data to another user, labeling data, and the like).

[0041] As noted above, the scientific instrument support module 1000 may be implemented by one or more computing devices. FIG. 5 is a block diagram of a computing device 4000 that may perform some or all of the scientific instrument support methods disclosed herein, in accordance with various embodiments. In some embodiments, the scientific instrument support module 1000 may be implemented by a single computing device 4000 or by multiple computing devices 4000 Further, as discussed below, a computing device 4000 (or multiple computing devices 4000) that implements the scientific instrument support module 1000 may be part of one or more of the scientific instrument 5010, the user local computing device 5020, the service local computing device 5030, or the remote computing device 5040 of FIG. 5.

[0042] The computing device 4000 of FIG. 4 is illustrated as having a number of components, but any one or more of these components may be omitted or duplicated, as suitable for the application and setting. In some embodiments, some or all of the components included in the computing device 4000 may be attached to one or more motherboards and enclosed in a housing (e.g. , including plastic, metal, and/or other materials). In some embodiments, some these components may be fabricated onto a single system-on-a-chip (SoC) (e.g., an SoC may include one or more processing devices 4002 and one or more storage devices 4004) Additionally, in various embodiments, the computing device 4000 may not include one or more of the components illustrated in FIG. 4, but may include interface circuitry (not shown) for coupling to the one or more components using any suitable interface (e.g., a Universal Serial Bus (USB) interface, a High-Definition Multimedia Interface (HDMI) interface, a Controller Area Network (CAN) interface, a Serial Peripheral Interface (SPI) interface, an Ethernet interface, a wireless interface, or any other appropriate interface) . For example, the computing device 4000 may not include a display device 4010, but may include display device interface circuitry (e.g., a connector and driver circuitry) to which a display device 4010 may be coupled.

[0043] The computing device 4000 may include a processing device 4002 (e.g., one or more processing devices). As used herein, the term "processing device" may refer to any device or portion of a device that processes electronic data from registers and/or memory to transform that electronic data into other electronic data that may be stored in registers and/or memory. The processing device 4002 may include one or more digital signal processors (DSPs), application-specific integrated circuits (ASICs), central processing units (CPUs), graphics processing units (GPUs), cryptoprocessors (specialized processors that execute cryptographic algorithms within hardware), server processors, or any other suitable processing devices.

[0044] The computing device 4000 may include a storage device 4004 (e.g., one or more storage devices). The storage device 4004 may include one or more memory devices such as random access memory (RAM) (e.g., static RAM (SRAM) devices, magnetic RAM (MRAM) devices, dynamic RAM (DRAM) devices, resistive RAM (RRAM) devices, or conductive-bridging RAM (CBRAM) devices), hard drive-based memory devices, solid-state memory devices, networked drives, cloud drives, or any combination of memory devices. In some embodiments, the storage device 4004 may include memory that shares a die with a processing device 4002. In such an embodiment, the memory may be used as cache memory and may include embedded dynamic random access memory (eDRAM) or spin transfer torque magnetic random access memory (STT-MRAM), for example. In some embodiments, the storage device 4004 may include non-transitory computer readable media having instructions thereon that, when executed by one or more processing devices (e.g., the processing device 4002), cause the computing device 4000 to perform any appropriate ones of or portions of the methods disclosed herein.

[0045] The computing device 4000 may include an interface device 4006 (e.g., one or more interface devices 4006). The interface device 4006 may include one or more communication chips, connectors, and/or other hardware and software to govern communications between the computing device 4000 and other computing devices. For example, the interface device 4006 may include circuitry for managing wireless communications for the transfer of data to and from the computing device 4000. The term "wireless" and its derivatives may be used to describe circuits, devices, systems, methods, techniques, communications channels, etc., that may communicate data through the use of modulated electromagnetic radiation through a nonsolid medium. The term does not imply that the associated devices do not contain any wires, although in some embodiments they might not. Circuitry included in the interface device 4006 for managing wireless communications may implement any of a number of wireless standards or protocols, including but not limited to Institute for Electrical and Electronic Engineers (IEEE) standards including Wi-Fi (IEEE 802.11 family), IEEE 802.16 standards (e.g., IEEE 802.16-2005 Amendment), Long-Term Evolution (LTE) project along with any amendments, updates, and/or revisions (e.g., advanced LTE project, ultra-mobile broadband (UMB) project (also referred to as "3GPP2"), etc.). In some embodiments, circuitry included in the interface device 4006 for managing wireless communications may operate in accordance with a Global System for Mobile Communication (GSM), General Packet Radio Service (GPRS), Universal Mobile Telecommunications System (UMTS), High Speed Packet Access (HSPA), Evolved HSPA (E-HSPA), or LTE network. In some embodiments, circuitry included in the interface device 4006 for managing wireless communications may operate in accordance with Enhanced Data for GSM Evolution (EDGE), GSM EDGE Radio Access Network (GERAN), Universal Terrestrial Radio Access Network (UTRAN), or Evolved UTRAN (E-UTRAN). In some embodiments, circuitry included in the interface device 4006 for managing wireless communications may operate in accordance with Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Digital Enhanced Cordless Telecommunications (DECT), Evolution-Data Optimized (EV-DO), and derivatives thereof, as well as any other wireless protocols that are designated as 3G, 4G, 5G, and beyond. In some embodiments, the interface device 4006 may include one or more antennas (e.g., one or more antenna arrays) to receipt and/or transmission of wireless communications.

[0046] In some embodiments, the interface device 4006 may include circuitry for managing wired communications, such as electrical, optical, or any other suitable communication protocols. For example, the interface device 4006 may include circuitry to support communications in accordance with Ethernet technologies. In some embodiments, the interface device 4006 may support both wireless and wired communication, and/or may support multiple wired communication protocols and/or multiple wireless communication protocols. For example, a first set of circuitry of the interface device 4006 may be dedicated to shorter-range wireless communications such as Wi-Fi or Bluetooth, and a second set of circuitry of the interface device 4006 may be dedicated to longer-range wireless communications such as global positioning system (GPS), EDGE, GPRS, CDMA, WiMAX, LTE, EV-DO, or others. In some embodiments, a first set of circuitry of the interface device 4006 may be dedicated to wireless communications, and a second set of circuitry of the interface device 4006 may be dedicated to wired communications. [0047] The computing device 4000 may include battery/power circuitry 4008. The battery/power circuitry 4008 may include one or more energy storage devices (e.g., batteries or capacitors) and/or circuitry for coupling components of the computing device 4000 to an energy source separate from the computing device 4000 (e.g., AC line power).

[0048] The computing device 4000 may include a display device 4010 (e.g., multiple display devices). The display device 4010 may include any visual indicators, such as a heads-up display, a computer monitor, a projector, a touchscreen display, a liquid crystal display (LCD), a light-emitting diode display, or a flat panel display.

[0049] The computing device 4000 may include other input/output (I/O) devices 4012. The other I/O devices 4012 may include one or more audio output devices (e.g., speakers, headsets, earbuds, alarms, etc.), one or more audio input devices (e.g., microphones or microphone arrays), location devices (e.g., GPS devices in communication with a satellite-based system to receive a location of the computing device 4000, as known in the art), audio codecs, video codecs, printers, sensors (e.g., thermocouples or other temperature sensors, humidity sensors, pressure sensors, vibration sensors, accelerometers, gyroscopes, etc.), image capture devices such as cameras, keyboards, cursor control devices such as a mouse, a stylus, a trackball, or a touchpad, bar code readers, Quick Response (QR) code readers, or radio frequency identification (RFID) readers, for example.

[0050] The computing device 4000 may have any suitable form factor for its application and setting, such as a handheld or mobile computing device (e.g., a cell phone, a smart phone, a mobile internet device, a tablet computer, a laptop computer, a netbook computer, an ultrabook computer, a personal digital assistant (PDA), an ultra mobile personal computer, etc.), a desktop computing device, or a server computing device or other networked computing component.

[0051] One or more computing devices implementing any of the scientific instrument support modules or methods disclosed herein may be part of a scientific instrument support system. FIG. 5 is a block diagram of an example scientific instrument support system 5000 in which some or all of the scientific instrument support methods disclosed herein may be performed, in accordance with various embodiments. The scientific instrument support modules and methods disclosed herein (e.g., the scientific instrument support module 1000 of FIG. 1 and the method 2000 of FIG. 2) may be implemented by one or more of the scientific instrument 5010, the user local computing device 5020, the service local computing device 5030, or the remote computing device 5040 of the scientific instrument support system 5000.

[0052] Any of the scientific instrument 5010, the user local computing device 5020, the service local computing device 5030, or the remote computing device 5040 may include any of the embodiments of the computing device 4000 discussed herein with reference to FIG. 4, and any of the scientific instrument 5010, the user local computing device 5020, the service local computing device 5030, or the remote computing device 5040 may take the form of any appropriate ones of the embodiments of the computing device 4000 discussed herein with reference to FIG. 4.

[0053] The scientific instrument 5010, the user local computing device 5020, the service local computing device 5030, or the remote computing device 5040 may each include a processing device 5002, a storage device 5004, and an interface device 5006. The processing device 5002 may take any suitable form, including the form of any of the processing devices 4002 discussed herein with reference to FIG. 4, and the processing devices 5002 included in different ones of the scientific instrument 5010, the user local computing device 5020, the service local computing device 5030, or the remote computing device 5040 may take the same form or different forms. The storage device 5004 may take any suitable form, including the form of any of the storage devices 4004 discussed herein with reference to FIG. 4, and the storage devices 5004 included in different ones of the scientific instrument 5010, the user local computing device 5020, the service local computing device 5030, or the remote computing device 5040 may take the same form or different forms. The interface device 5006 may take any suitable form, including the form of any of the interface devices 4006 discussed herein with reference to FIG. 4, and the interface devices 5006 included in different ones of the scientific instrument 5010, the user local computing device 5020, the service local computing device 5030, or the remote computing device 5040 may take the same form or different forms.

[0054] The scientific instrument 5010, the user local computing device 5020, the service local computing device 5030, and the remote computing device 5040 may be in communication with other elements of the scientific instrument support system 5000 via communication pathways 5008. The communication pathways 5008 may communicatively couple the interface devices 5006 of different ones of the elements of the scientific instrument support system 5000, as shown, and may be wired or wireless communication pathways (e.g. , in accordance with any of the communication techniques discussed herein with reference to the interface devices 4006 of the computing device 4000 of FIG. 4). The particular scientific instrument support system 5000 depicted in FIG. 5 includes communication pathways between each pair of the scientific instrument 5010, the user local computing device 5020, the service local computing device 5030, and the remote computing device 5040, but this "fully connected” implementation is simply illustrative, and in various embodiments, various ones of the communication pathways 5008 may be absent. For example, in some embodiments, a service local computing device 5030 may not have a direct communication pathway 5008 between its interface device 5006 and the interface device 5006 of the scientific instrument 5010, but may instead communicate with the scientific instrument 5010 via the communication pathway 5008 between the service local computing device 5030 and the user local computing device 5020 and the communication pathway 5008 between the user local computing device 5020 and the scientific instrument 5010.

[0055] The user local computing device 5020 may be a computing device (e.g., in accordance with any of the embodiments of the computing device 4000 discussed herein) that is local to a user of the scientific instrument 5010. In some embodiments, the user local computing device 5020 may also be local to the scientific instrument 5010, but this need not be the case; for example, a user local computing device 5020 that is in a user’s home or office may be remote from, but in communication with, the scientific instrument 5010 so that the user may use the user local computing device 5020 to control and/or access data from the scientific instrument 5010. In some embodiments, the user local computing device 5020 may be a laptop, smartphone, or tablet device. In some embodiments the user local computing device 5020 may be a portable computing device. [0056] The service local computing device 5030 may be a computing device (e.g., in accordance with any of the embodiments of the computing device 4000 discussed herein) that is local to an entity that services the scientific instrument 5010. For example, the service local computing device 5030 may be local to a manufacturer of the scientific instrument 5010 or to a third-party service company. In some embodiments, the service local computing device 5030 may communicate with the scientific instrument 5010, the user local computing device 5020, and/or the remote computing device 5040 (e.g., via a direct communication pathway 5008 or via multiple “indirect” communication pathways 5008, as discussed above) to receive data regarding the operation of the scientific instrument 5010, the user local computing device 5020, and/or the remote computing device 5040 (e g., the results of self-tests of the scientific instrument 5010, calibration coefficients used by the scientific instrument 5010, the measurements of sensors associated with the scientific instrument 5010, etc.). In some embodiments, the service local computing device 5030 may communicate with the scientific instrument 5010, the user local computing device 5020, and/or the remote computing device 5040 (e.g., via a direct communication pathway 5008 or via multiple “indirect” communication pathways 5008, as discussed above) to transmit data to the scientific instrument 5010, the user local computing device 5020, and/or the remote computing device 5040 (e.g., to update programmed instructions, such as firmware, in the scientific instrument 5010, to initiate the performance of test or calibration sequences in the scientific instrument 5010, to update programmed instructions, such as software, in the user local computing device 5020 or the remote computing device 5040, etc.). A user of the scientific instrument 5010 may utilize the scientific instrument 5010 or the user local computing device 5020 to communicate with the service local computing device 5030 to report a problem with the scientific instrument 5010 or the user local computing device 5020, to request a visit from a technician to improve the operation of the scientific instrument 5010, to order consumables or replacement parts associated with the scientific instrument 5010, or for other purposes.

[0057] The remote computing device 5040 may be a computing device (e.g., in accordance with any of the embodiments of the computing device 4000 discussed herein) that is remote from the scientific instrument 5010 and/or from the user local computing device 5020. In some embodiments, the remote computing device 5040 may be included in a datacenter or other large-scale server environment. In some embodiments, the remote computing device 5040 may include network-attached storage (e.g., as part of the storage device 5004). The remote computing device 5040 may store data generated by the scientific instrument 5010, perform analyses of the data generated by the scientific instrument 5010 (e.g., in accordance with programmed instructions), facilitate communication between the user local computing device 5020 and the scientific instrument 5010, and/or facilitate communication between the service local computing device 5030 and the scientific instrument 5010.

[0058] In some embodiments, one or more of the elements of the scientific instrument support system 5000 illustrated in FIG. 5 may not be present. Further, in some embodiments, multiple ones of various ones of the elements of the scientific instrument support system 5000 of FIG. 5 may be present. For example, a scientific instrument support system 5000 may include multiple user local computing devices 5020 (e.g., different user local computing devices 5020 associated with different users or in different locations). In another example, a scientific instrument support system 5000 may include multiple scientific instruments 5010, all in communication with service local computing device 5030 and/or a remote computing device 5040; in such an embodiment, the service local computing device 5030 may monitor these multiple scientific instruments 5010, and the service local computing device 5030 may cause updates or other information may be “broadcast” to multiple scientific instruments 5010 at the same time. Different ones of the scientific instruments 5010 in a scientific instrument support system 5000 may be located close to one another (e.g., in the same room) or farther from one another (e.g., on different floors of a building, in different buildings, in different cities, etc.). In some embodiments, a scientific instrument 5010 may be connected to an Internet-of-Things (loT) stack that allows for command and control of the scientific instrument 5010 through a web-based application, a virtual or augmented reality application, a mobile application, and/or a desktop application. Any of these applications may be accessed by a user operating the user local computing device 5020 in communication with the scientific instrument 5010 by the intervening remote computing device 5040. In some embodiments, a scientific instrument 5010 may be sold by the manufacturer along with one or more associated user local computing devices 5020 as part of a local scientific instrument computing unit 5012.

[0059] The following paragraphs provide various examples of the embodiments disclosed herein.

[0060] Example A1 is a mass spectrometry support apparatus including first logic to receive a plurality of sample data from a queue; second logic to generate, based on the sample data, a gel-lane plot comprising a stacked column of gel spots where the y-axis represents the mass, and the x-axis is discretized into a single sample or run; third logic to regularizing the y-axis to the sample data by employing a clustering technique (including, e.g., a high-resolution clustering algorithm and/or a low-resolution version) to mass cluster the sample data; and fourth logic to provide the gel-lane plot for display showing the deconvoluted mass spectra results for samples.

[0061] Example A2 includes the subject matter of Example 1, and further specifies that the third logic further comprises highlight intensity information from the sample data by applying a color to the gel spots.

[0062] Example A3 includes the subject matter of any of Examples A1 and A2, and further specifies that the gel-lane plot increasing the number of available page pixels and decrease data loss.

[0063] Example A4 includes the subject matter of any of Examples A1-3, and that the fourth logic further includes providing, for display, graphics to indicate instrument performance (QC) and an overall quality and purity of the samples.

[0064] Example A5 includes the subject matter of any of Examples A1-4, and further specifies that regularizing the y-axis to the sample data ensures that the pixels for data spots are not lost during pixel reduction.

[0065] Example A6 includes the subject matter of any of Examples A1-5, and further specifies that the display of the gel-lane plot compares to theoretical masses and experimental masses of the samples.

[0066] Example A7 includes the subject matter of any of Examples A1-6, and further specifies that the display of the gel-lane plot allows for cross sample comparisons on a single page or view. [0067] Example B1 is a mass spectrometry support apparatus, including logic to: receive data representative of mass spectra of a plurality of samples; generate, based on the data, a gel-lane plot including a plurality of stacked columns of gel spots, wherein the y-axis is indicative of mass, the x-axis is divided into a plurality of regions individually corresponding to different ones of the plurality of samples, and a color or shading of the gel spots represents intensity information of the data; and provide the gel-lane plot for display.

[0068] Example B2 may include the subject matter of Example B1 , and may further specify that the logic is further to, as part of generating the gel-lane plot, regularize the y-axis and the data by employing a clustering technique.

[0069] Example B3 may include the subject matter of any of Examples B1-2, and may further specify that the y-axis represents mass or mass over charge.

[0070] Example B4 may include the subject matter of any of Examples B1-3, and may further specify that the logic is further to: provide a graphic indicative of quality or purity of individual samples based on the data.

[0071] Example B5 may include the subject matter of any of Examples B1-4, and may further specify that the logic is further to: generate a box or line corresponding to a particular mass and extending across the columns of the gellane plot.

[0072] Example B6 may include the subject matter of any of Examples B1-5, and may further specify that the logic is further to: enable printing of the gel-lane plot onto a single sheet of paper.

[0073] Example B7 is a mass spectrometry system, including: a mass spectrometer; and a computing device communicatively coupled to the mass spectrometer, wherein the computing device is to: receive data from the mass spectrometer, wherein the data is indicative of mass spectra of a plurality of samples; generate a plot based on the data, wherein the plot includes a plurality of vertical lanes, with individual lanes associated with individual ones of the samples, and one or more spots distributed along the vertical length of individual ones of the lanes, wherein the one or more spots in a lane associated with a particular sample indicate intensity information in the mass spectrum associated with that sample; and output the plot to a user of the mass spectrometry system.

[0074] Example B8 may include the subject matter of Example B7, and may further specify that the spots in a particular lane represent clustered data from the mass spectrum of the sample associated with that lane.

[0075] Example B9 may include the subject matter of any of Examples B7-8, and may further specify that the spots include a visual indicator of the intensity of one or more associated peaks in the mass spectrum.

[0076] Example B10 may include the subject matter of Example B9, and may further specify that the visual indicator includes a color.

[0077] Example B11 may include the subject matter of any of Examples B7-10, and may further specify that a vertical location of a spot in a lane corresponds to a mass associated with the associated peak.

[0078] Example B12 may include the subject matter of any of Examples B7-11 , and may further specify that the computing device is further to output, to the user, a graphic indicative of quality or purity of individual samples based on the data. [0079] Example B13 is one or more non-transitory computer readable media having instructions thereon that, when executed by one or more processing devices of a computing device, cause the computing device to: receive data from the mass spectrometer, wherein the data is indicative of mass spectra of a plurality of samples; generate, for display, a gel-lane plot representative of the data, wherein the gel-lane plot includes a plurality of vertical lanes, with individual lanes associated with individual ones of the samples, and one or more spots distributed along the vertical length of individual ones of the lanes, and wherein a vertical location of a spot is indicative of an associated mass; and generate, for display, a graphic indicative of quality or purity of individual samples based on the data.

[0080] Example B14 may include the subject matter of Example B13, and may further specify that the instructions, upon execution, further cause the computing device to: generate, for display, a box or line corresponding to a particular mass and extending across the columns of the gel-lane plot.

[0081] Example B15 may include the subject matter of any of Examples B13-14, and may further specify that the gel-lane plot includes white space of different lengths along the vertical length of one or more of the vertical lanes to indicate mass differences between associated spots.

[0082] Example B16 may include the subject matter of any of Examples B13-15, and may further specify that the spots in a particular lane represent clustered data from the mass spectrum of the sample associated with that lane. [0083] Example B17 may include the subject matter of any of Examples B13-16, and may further specify that the spots include a visual indicator of the intensity of one or more associated peaks in the mass spectrum.

[0084] Example B18 may include the subject matter of any of Examples B13-17, and may further specify that the visual indicator includes a color.

[0085] Example B19 may include the subject matter of any of Examples B13-18, and may further specify that the data is received from a queue.

[0086] Example B20 may include the subject matter of any of Examples B13-19, and may further specify that the mass range associated with the vertical length of a lane includes at least 50-1,000,000 Da.

Claims

Claims:

1 . A mass spectrometry support apparatus, comprising logic to: receive data representative of mass spectra of a plurality of samples; generate, based on the data, a gel-lane plot including a plurality of stacked columns of gel spots, wherein the y-axis is indicative of mass, the x-axis is divided into a plurality of regions individually corresponding to different ones of the plurality of samples, and a color or shading of the gel spots represents intensity information of the data; and provide the gel-lane plot for display.

2. The mass spectrometry support apparatus of claim 1 , wherein the logic is further to, as part of generating the gellane plot, regularize the y-axis and the data by employing a clustering technique.

3. The mass spectrometry support apparatus of claim 1 , wherein the y-axis represents mass or mass over charge.

4. The mass spectrometry support apparatus of claim 1 , wherein the logic is further to: provide a graphic indicative of quality or purity of individual samples based on the data.

5. The mass spectrometry support apparatus of claim 1 , wherein the logic is further to: generate a box or line corresponding to a particular mass and extending across the columns of the gel-lane plot.

6. The mass spectrometry support apparatus of claim 1 , wherein the logic is further to: enable printing of the gel-lane plot onto a single sheet of paper.

7. A mass spectrometry system, comprising: a mass spectrometer; and a computing device communicatively coupled to the mass spectrometer, wherein the computing device is to: receive data from the mass spectrometer, wherein the data is indicative of mass spectra of a plurality of samples; generate a plot based on the data, wherein the plot includes a plurality of vertical lanes, with individual lanes associated with individual ones of the samples, and one or more spots distributed along the vertical length of individual ones of the lanes, wherein the one or more spots in a lane associated with a particular sample indicate intensity information in the mass spectrum associated with that sample; and output the plot to a user of the mass spectrometry system.

8. The mass spectrometry system of claim 7, wherein the spots in a particular lane represent clustered data from the mass spectrum of the sample associated with that lane.

9. The mass spectrometry system of claim 7, wherein the spots include a visual indicator of the intensity of one or more associated peaks in the mass spectrum.

10. The mass spectrometry system of claim 9, wherein the visual indicator includes a color.

11 The mass spectrometry system of claim 7, wherein a vertical location of a spot in a lane corresponds to a mass associated with the associated peak.

12. The mass spectrometry system of claim 7, wherein the computing device is further to output, to the user, a graphic indicative of quality or purity of individual samples based on the data

13. One or more non-transitory computer readable media having instructions thereon that, when executed by one or more processing devices of a computing device, cause the computing device to: receive data from the mass spectrometer, wherein the data is indicative of mass spectra of a plurality of samples; generate, for display, a gel-lane plot representative of the data, wherein the gel-lane plot includes a plurality of vertical lanes, with individual lanes associated with individual ones of the samples, and one or more spots distributed along the vertical length of individual ones of the lanes, and wherein a vertical location of a spot is indicative of an associated mass; and generate, for display, a graphic indicative of quality or purity of individual samples based on the data.

14. The one or more non-transitory computer readable media of claim 13, wherein the instructions, upon execution, further cause the computing device to: generate, for display, a box or line corresponding to a particular mass and extending across the columns of the gellane plot.

15. The one or more non-transitory computer readable media of claim 13, wherein the gel-lane plot includes white space of different lengths along the vertical length of one or more of the vertical lanes to indicate mass differences between associated spots.

16. The one or more non-transitory computer readable media of claim 13, wherein the spots in a particular lane represent clustered data from the mass spectrum of the sample associated with that lane.

17. The one or more non-transitory computer readable media of claim 13, wherein the spots include a visual indicator of the intensity of one or more associated peaks in the mass spectrum.

18. The one or more non-transitory computer readable media of claim 13, wherein the visual indicator includes a color.

19. The one or more non-transitory computer readable media of claim 13, wherein the data is received from a queue.

20. The one or more non-transitory computer readable media of claim 13, wherein the mass range associated with the vertical length of a lane includes at least 50-1 ,000,000 Da.