Mass spectrometry data compression method, system, storage medium and electronic device

Abstract

The application provides a mass spectrum data compression method, system, storage medium and electronic equipment, comprising the following steps: collecting mass-to-charge ratio data, ion intensity data and mass spectrum number data of multiple mass spectra; sorting the mass-to-charge ratio data, and generating a mass-to-charge ratio difference value data set through the difference between adjacent mass-to-charge ratio data after sorting; reducing the precision of the ion intensity data to generate an ion intensity data set; generating a corresponding mass spectrum number data set through the mass spectrum number data and the mass-to-charge ratio difference value data set; and finally compressing the generated sets by using a conventional compression algorithm. According to the characteristics that the adjacent mass-to-charge ratios in the mass spectrum do not change much, the mass-to-charge ratios in the multiple mass spectra are sorted, and the difference between the adjacent mass-to-charge ratios is used to replace the original data. In addition, since the ion intensity does not need to be very precise in many cases, the precision is reduced by rounding, so that the storage capacity of the overall mass spectrum data is further reduced.

Description

Technical Field

[0001] This invention relates to the field of mass spectrometry analysis technology, and in particular to a mass spectrometry data compression method, system, storage medium, and electronic device. Background Technology

[0002] In mass spectrometry analysis, high-precision mass spectrometry generates massive amounts of data. When using a mass spectrometer, 10GB or more of data can be generated per hour. With the development of mass spectrometry technology and the increase in analytical projects, the amount of mass spectrometry data is growing rapidly, making data storage and transmission a potential problem. However, current mass spectrometry data compression methods use conventional data compression algorithms without specifically optimizing for the characteristics of mass spectrometry data, resulting in mass spectrometry data still occupying excessive storage space. Summary of the Invention

[0003] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide a mass spectrometry data compression method, system, storage medium and electronic device to solve the problem that the prior art does not utilize the characteristics of mass spectrometry data for optimization, resulting in mass spectrometry data still occupying too much storage space.

[0004] To solve the above-mentioned technical problems, the present invention is implemented as follows: a mass spectrometry data compression method, the method comprising the following steps:

[0005] Step 1: Collect mass-to-charge ratio data of multiple mass spectrometers, ion intensity data corresponding to the mass-to-charge ratio data, and mass spectrometer number data corresponding to the mass-to-charge ratio data;

[0006] Step two: Sort the mass-to-charge ratio data and generate a mass-to-charge ratio difference data set by the difference between adjacent mass-to-charge ratio data after sorting; reduce the precision of the ion strength data to generate an ion strength data set;

[0007] Step 3: Generate the corresponding mass spectrometry number data set using the mass spectrometry number data set and the mass-to-charge ratio difference data set;

[0008] Step four: Compress the mass-to-charge ratio difference data set, ion intensity data set, and mass spectrometry number data set using a data compression algorithm.

[0009] To further address the technical problem to be solved by this invention, the second step of the mass spectrometry data compression method provided by this invention includes sorting the mass-to-charge ratio data from smallest to largest.

[0010] To further address the technical problem to be solved by this invention, the present invention provides a mass spectrometry data compression method, wherein step two includes retaining two decimal places for the mass-to-charge ratio data.

[0011] To further address the technical problem to be solved by this invention, the present invention provides a mass spectrometry data compression method, wherein step two includes rounding the ion intensity data.

[0012] To further address the technical problem to be solved by this invention, a mass spectrometry data compression method is provided by this invention, in which the difference between adjacent data in the mass spectrometry numbered data set is stored.

[0013] To further address the technical problem addressed by this invention, in a mass spectrometry data compression method provided by this invention, the difference between adjacent data in the mass spectrometry numbered data set is:

[0014] W = (k2 - k1 + K) % K,

[0015] Here, k1 and k2 are two adjacent data points, and K is the total number of mass spectra.

[0016] To further address the technical problems to be solved by this invention, the present invention provides a mass spectrometry data compression method in which the data compression algorithm includes LZW algorithm, LZSS algorithm, arithmetic coding algorithm, Huffman coding algorithm and RLE coding algorithm.

[0017] To further address the technical problems addressed by this invention, this invention also provides a mass spectrometry data compression system, the system comprising:

[0018] The data acquisition module is used to acquire mass-to-charge ratio data of multiple mass spectra, ion intensity data corresponding to the mass-to-charge ratio data, and mass spectrometer number data corresponding to the mass-to-charge ratio data;

[0019] The data sorting module is used to sort the mass-to-charge ratio data;

[0020] The data difference calculation module is used to calculate the difference between adjacent mass-to-charge ratio data.

[0021] The data rounding calculation module is used to round the ion strength data.

[0022] The data integration module is used to generate a set of mass-to-charge ratio difference data, a set of ion intensity data, and a set of mass spectrometer number data.

[0023] The data compression module is used to compress the mass-to-charge ratio difference data set, ion intensity data set, and mass spectrometry number data set using a data compression algorithm.

[0024] To further address the technical problem to be solved by the present invention, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a mass spectrometry data compression method.

[0025] To further address the technical problems addressed by this invention, this invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of a mass spectrometry data compression method.

[0026] As described above, the mass spectrometry data compression method, system, storage medium, and electronic device of the present invention, through ingenious design, takes advantage of the small variation between adjacent mass-to-charge ratios in mass spectra, sorts the mass-to-charge ratios of multiple mass spectra, and replaces the original data with the difference between adjacent mass-to-charge ratios. Since the difference is often very small or even zero, a significant amount of storage space is saved. Furthermore, since ion intensity does not require high precision in many cases, rounding it reduces the precision, thereby further reducing the overall storage capacity of the mass spectrometry data. Attached Figure Description

[0027] Figure 1 The flowchart shown is a mass spectrometry data compression method according to an embodiment of the present invention;

[0028] Figure 2 The diagram shows a framework schematic of a mass spectrometry data compression system according to an embodiment of the present invention.

[0029] Figure 3 The diagram shown is a structural schematic of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0030] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0031] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0032] Please see Figures 1 to 3 This invention provides a method for mass spectrometry data compression, the method comprising the following steps:

[0033] Step 1: Collect mass-to-charge ratio data, corresponding ion intensity data, and mass spectrometer number data for multiple mass spectrometers.

[0034] Step two involves sorting the mass-to-charge ratio (MMR) data and generating a MMR difference dataset based on the differences between adjacent MMR values ​​after sorting. The MMR data is sorted in ascending order. If high precision is not required for the MMR in certain situations, the MMR data can be pre-sorted to two decimal places, or retain only a few key decimal places.

[0035] Since the precision of ion strength data does not need to be so strict, reducing the precision of ion strength data to generate an ion strength data set can be achieved by rounding down the ion strength data to reduce precision and storage space.

[0036] Step 3: Generate a corresponding mass spectrometry ID dataset using the mass spectrometry ID data and the mass-to-charge ratio difference dataset. Store the differences between adjacent data points in the mass spectrometry ID dataset. The differences between adjacent data points in the mass spectrometry ID dataset are:

[0037] W = (k2 - k1 + K) % K,

[0038] Here, k1 and k2 are two adjacent data points, and K is the total number of mass spectra. The operator "%" represents the modulo operation, which is a commonly used modulo operator in C.

[0039] Step four involves compressing the mass-to-charge ratio difference dataset, ion intensity dataset, and mass spectrometer number dataset using data compression algorithms. These algorithms include LZW, LZSS, arithmetic coding, Huffman coding, and RLE coding.

[0040] This invention also provides a mass spectrometry data compression system, comprising a data acquisition module, a data sorting module, a data difference calculation module, a data rounding calculation module, a data integration module, and a data compression module. The data acquisition module is used to acquire mass-to-charge ratio (M / C ratio) data, corresponding ion intensity data, and corresponding mass spectrometry number data from multiple mass spectrometers. The data sorting module is used to sort the M / C ratio data. The data difference calculation module is used to calculate the difference between adjacent M / C ratio data. The data rounding calculation module is used to round the ion intensity data. The data integration module is used to generate a set of M / C ratio difference data, a set of ion intensity data, and a set of mass spectrometry number data. The data compression module is used to compress the M / C ratio difference data, the ion intensity data, and the mass spectrometry number data using a data compression algorithm.

[0041] Suppose there are three mass spectrometers, each with two peaks (X, Y), as shown below:

[0042] The first mass spectrometer, numbered 0, has the following parameters: {(99.9, 86.464), (150.3, 45.775)}.

[0043] The second mass spectrometer, numbered 1, is: {(100.1, 85.547), (149.9, 43, 325)};

[0044] The third mass spectrometer, numbered 2, is {(99.6, 84.435), (149.5, 46.235)}.

[0045] After sorting the mass-to-charge ratio data (X-axis) to {99.6, 99.9, 100.1, 149.5, 149.9, 150.3}, the resulting mass-to-charge ratio difference data set is {99.6, 0.3, 0.2, 49.4, 0.4, 0.4}. The ion intensity data (Y-axis), after retaining integers in their original order, is the resulting ion intensity data set {86, 45, 85, 43, 84, 46}. The corresponding mass spectrometer number set is {2, 0, 1, 2, 1, 0}. Finally, the LZW algorithm is used to compress the data for {99.6, 99.9, 100.1, 149.5, 149.9, 150.3}, {99.6, 0.3, 0.2, 49.4, 0.4, 0.4}, and {2, 0, 1, 2, 1, 0} respectively.

[0046] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the mass spectrometry data compression method described above. The computer-readable medium can be any means capable of containing, storing, communicating, propagating, or transmitting a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires, a portable computer disk drive, random access memory, read-only memory, erasable and editable read-only memory, fiber optic devices, and portable optical disc read-only memory. Furthermore, the computer-readable medium can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0047] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the memory and the processor are connected via a bus, and the processor executes the computer program stored in the memory to implement the steps of a mass spectrometry data compression method as described in the above embodiment.

[0048] In summary, the mass spectrometry data compression method, system, storage medium, and electronic device of this invention, through ingenious design, takes advantage of the small variation between adjacent mass-to-charge ratios in mass spectrometry. It sorts the mass-to-charge ratios of multiple mass spectra and replaces the original data with the differences between adjacent mass-to-charge ratios. Since these differences are often very small or even zero, a significant amount of storage space is saved. Furthermore, since ion intensity does not require high precision in many cases, rounding it down reduces the overall storage capacity of the mass spectrometry data, further minimizing the overall storage capacity. Therefore, this invention effectively overcomes the various shortcomings of existing technologies and achieves better practical results.

[0049] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for mass spectrometry data compression, characterized in that, The method includes the following steps: Step 1: Collect mass-to-charge ratio data of multiple mass spectrometers, ion intensity data corresponding to the mass-to-charge ratio data, and mass spectrometer number data corresponding to the mass-to-charge ratio data; Step two: Sort the mass-to-charge ratio data and generate a mass-to-charge ratio difference data set by the difference between adjacent mass-to-charge ratio data after sorting; reduce the precision of the ion strength data to generate an ion strength data set; Step 3: Generate the corresponding mass spectrometry number data set using the mass spectrometry number data set and the mass-to-charge ratio difference data set; Step four: Compress the mass-to-charge ratio difference data set, ion intensity data set, and mass spectrometry number data set using a data compression algorithm.

2. The mass spectrometry data compression method according to claim 1, characterized in that: Step two includes sorting the mass-to-charge ratio data from smallest to largest.

3. The mass spectrometry data compression method according to claim 1, characterized in that: Step two includes reserving two decimal places for the mass-to-charge ratio data.

4. The mass spectrometry data compression method according to claim 1, characterized in that: Step two includes rounding the ion strength data.

5. The mass spectrometry data compression method according to claim 1, characterized in that: The difference between adjacent data in the mass spectrometry numbered data set is stored.

6. The mass spectrometry data compression method according to claim 5, characterized in that: The difference between adjacent data in the mass spectrometry numbering dataset is: W = (k2 - k1 + K) % K, Here, k1 and k2 are two adjacent data points, and K is the total number of mass spectra.

7. The mass spectrometry data compression method according to claim 1, characterized in that: The data compression algorithms include LZW algorithm, LZSS algorithm, arithmetic coding algorithm, Huffman coding algorithm and RLE coding algorithm.

8. A mass spectrometry data compression system, characterized in that, The system includes: The data acquisition module is used to acquire mass-to-charge ratio data of multiple mass spectra, ion intensity data corresponding to the mass-to-charge ratio data, and mass spectrometer number data corresponding to the mass-to-charge ratio data; The data sorting module is used to sort the mass-to-charge ratio data; The data difference calculation module is used to calculate the difference between adjacent mass-to-charge ratio data. The data rounding calculation module is used to round the ion strength data. The data integration module is used to generate a set of mass-to-charge ratio difference data, a set of ion intensity data, and a set of mass spectrometer number data. The data compression module is used to compress the mass-to-charge ratio difference data set, ion intensity data set, and mass spectrometry number data set using a data compression algorithm.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When executed by a processor, the computer program implements the steps of a mass spectrometry data compression method according to any one of claims 1-7.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the steps of the mass spectrometry data compression method according to any one of claims 1-7.

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