Methods and systems for mass defect filtering of mass spectrometry data
View Patent ↗The present teachings relate to a method of filtering mass spectrometer data using a variable filter window. The width of the window can depend on the mass itself and the mass defects for a family of compounds. The teachings can be used with a plurality of compounds including but not limited to peptides and can be utilized on a brood range of mass spectrometers.
1. A method for mass defect filtering of mass spectrometry data, comprising:
analyzing a plurality of known compounds from one or more known samples using a mass spectrometer, producing a first plurality of mass measurements for the known compounds;
obtaining the first plurality of mass measurements from the mass spectrometer using a processor;
selecting a distribution function based on a distribution of the first plurality of mass measurements using the processor;
creating a mass defect function for a mass that is a function of mass and the distribution function using the processor;
analyzing a plurality of unknown compounds from one or more unknown samples using the mass spectrometer, producing a second plurality of mass measurements for the unknown compounds;
obtaining the second plurality of mass measurements from the mass spectrometer using a processor; and
filtering the second plurality of mass measurements using a filter window size that scales with mass according to the mass defect function using the processor.
2. The method of claim 1 , wherein the plurality of known compounds comprises a plurality of known peptides and the plurality of unknown compounds comprises a plurality of unknown peptides.
3. The method of claim 2 , wherein selecting a distribution function based on a distribution of the first plurality of mass measurements using the processor comprises selecting a normal distribution function based on a distribution of the first plurality of mass measurements using the processor.
4. The method of claim 3 , wherein creating a mass defect function for a mass that is a function of mass and the distribution function using the processor comprises creating a mass defect function for a mass that is a function of mass and a mean of the normal distribution function using the processor.
5. The method of claim 4 , wherein filtering the second plurality of mass measurements using a filter window size that scales with mass according to the mass defect function using the processor comprises filtering the second plurality of mass measurements using a filter window size that is within a multiple of a standard deviation of the normal distribution function using the processor.
6. The method of claim 1 , wherein the plurality of known compounds comprises a plurality of known peptides digested by an enzyme and the plurality of unknown compounds comprises a plurality of unknown peptides digested by the enzyme.
7. The method of claim 6 , wherein selecting a distribution function based on a distribution of the first plurality of mass measurements using the processor comprises selecting a normal distribution function based on a distribution of the first plurality of mass measurements using the processor.
8. The method of claim 7 , further comprising calculating an extra mass defect contribution based on a mass defect of an amino acid where the enzyme is known to cleave peptides.
9. The method of claim 8 , wherein creating a mass defect function for a mass that is a function of mass and the distribution function using the processor comprises creating a mass defect function for a mass that is a function of mass, a mean of the normal distribution function, and the extra mass defect contribution using the processor.
10. The method of claim 1 , wherein the plurality of known compounds comprises a plurality of known peptides that undergo a modification and the plurality of unknown compounds comprises a plurality of unknown peptides that undergo the modification.
11. The method of claim 10 , wherein selecting a distribution function based on a distribution of the first plurality of mass measurements using the processor comprises selecting a normal distribution function based on a distribution of the first plurality of mass measurements using the processor.
12. The method of claim 11 , further comprising calculating an extra mass defect contribution based on the modification using the processor.
13. The method of claim 12 , wherein creating a mass defect function for a mass that is a function of mass and the distribution function using the processor comprises creating a mass defect function for a mass that is a function of mass, a mean of the normal distribution function, and the extra mass defect contribution using the processor.
14. A system for mass defect filtering of mass spectrometry data, comprising:
a mass spectrometer that analyzes a plurality of known compounds from one or more known samples, producing a first plurality of mass measurements for the known compounds and analyzes a plurality of unknown compounds from one or more unknown samples, producing a second plurality of mass measurements for the known compounds; and
a processor in communication with the mass spectrometer that
obtains the first plurality of mass measurements from the mass spectrometer,
selects a distribution function based on a distribution of the first plurality of mass measurements,
creates a mass defect function for a mass that is a function of mass and the distribution function,
obtains the second plurality of mass measurements from the mass spectrometer, and
filters the second plurality of mass measurements using a filter window size that scales with mass according to the mass defect function.
15. The system of claim 14 , wherein the plurality of known compounds comprises a plurality of known peptides and the plurality of unknown compounds comprises a plurality of unknown peptides.
16. The system of claim 15 , wherein the processor selects a normal distribution function based on a distribution of the first plurality of mass measurements.
17. The system of claim 16 , wherein the processor creates a mass defect function for a mass that is a function of mass and a mean of the normal distribution function.
18. The system of claim 17 , wherein the processor filters the second plurality of mass measurements using a filter window size that is within a multiple of a standard deviation of the normal distribution function.
19. A computer program product, comprising a tangible computer-readable storage medium whose contents include a program with instructions being executed on a processor so as to perform a method for mass defect filtering of mass spectrometry data, the method comprising:
providing a system, wherein the system comprises distinct software modules, and wherein the distinct software modules comprise a receiving mass spectrometer data module, a determining a statistical model for mass defects module, and an applying a filter based on the mass defect model to the data module;
obtaining a first plurality of mass measurements produced from a plurality of known compounds from one or more known samples by a mass spectrometer using the receiving mass spectrometer data module;
selecting a distribution function based on a distribution of the first plurality of mass measurements using the determining a statistical model for mass defects module;
creating a mass defect function for a mass that is a function of mass and the distribution function using the determining a statistical model for mass defects module;
obtaining a second plurality of mass measurements produced from a plurality of unknown compounds from one or more unknown samples by the mass spectrometer using the receiving mass spectrometer data module; and
filtering the second plurality of mass measurements using a filter window size that scales with mass according to the mass defect function using the applying a filter based on the mass defect model to the data module.
20. The computer program product of claim 19 , wherein the plurality of known compounds comprises a plurality of known peptides and the plurality of unknown compounds comprises a plurality of unknown peptides.