Dh Technologies Development Pte. Ltd.

Ignat V Shilov

Wilfred H Tang

Stephen Alexander Tate

Sean L Seymour

Ron Bonner

Alpesh A Patel

A method is disclosed for calculating and recalculating protein confidence values by recalculating peptide confidence values in proteomic analysis. A plurality of scans are performed of a sample that is proteolytically digested into surrogate peptide analytes. A plurality of spectra are obtained, and a plurality of peptides are identified. A protein database is searched for proteins matching peptides from the plurality of peptides. Peptide confidence values are determined for the set of peptides. A protein confidence value is calculated for each protein in the set of proteins. A protein from the set of proteins with a largest protein confidence value is selected, the largest protein confidence value for the protein is saved, the protein from the set of proteins is removed, and peptides corresponding to the protein is removed from the set of peptides. The protein confidence value is recalculated for each protein in the set of proteins.

Systems and methods for calculating protein confidence values

A plurality of product ion spectra measured over plurality of cycles for each precursor ion mass selection window of two or more precursor ion mass selection windows are received from a tandem mass spectrometer. A product ion extracted ion chroatograms (XIC) is calculated for each precursor ion mass selection window of the two or more precursor ion mass selection windows from the plurality of product ion spectra for each precursor ion mass selection window. Two or more product ion XICs are produced. A two-dimensional binary bit matrix is generated to represent each product ion XIC of the two or more product ion XICs. For each XIC of the two or more product ion XICs, the binary bit matrix is separately initialized with binary values calculated from each XIC and the initialized binary bit matrix is compared with stored information about known compounds to identify known compounds of each XIC.

Rapid scoring of LC-MS/MS peptide data

Protein confidence values are calculated in proteomic analysis. A protein database is searched for proteins matching peptides found from mass spectrometry of a sample producing a set of proteins and a corresponding set of peptides. Peptide confidence values for the set of peptides are determined. Protein confidence values are calculated for the set of proteins based on the peptide confidence values. A protein is selected from the set of proteins with a largest protein confidence value, the largest protein confidence value is saved for the protein, the protein is removed from the set of proteins, and one or more peptides corresponding to the protein are removed from the set of peptides. Protein confidence values are recalculated for the set of proteins based on the peptide confidence values and an effect of removing the one or more peptides from the set of peptides.

The present teachings provide for identification of peptides using small sequence tags to focus computational resources on searching regions of a protein database that are the most likely to yield correct identifications. They allow for the incorporation of modifications and in doing so focuses the search to peptides with a precursor mass match. Additionally, probability or relevance factors can be used to determine peptide hypotheses. Various embodiments are presented that search for peptides when a single precursor is selected or when multiple precursors are simultaneously fragmented.

Method, system, and computer program product for scoring theoretical peptides

A background component of reporter ion signals is determined by fitting a distribution function. A plurality of samples that include a protein labeled with a plurality of isobaric reporter ions is analyzed at a plurality of different times using a mass spectrometer, producing a plurality of mass spectra for the plurality of isobaric reporter ions. A cumulative distribution is calculated for an inverse coefficient of differential expression of the plurality of mass spectra using a processor. A Pearson Type IV distribution shifted by a constant value is fitted to the cumulative distribution and the constant value is solved for using the processor. A background component for each spectrum of the plurality of mass spectra is calculated from the constant value, a calculated coefficient of differential expression for each spectrum, and an average reporter ion signal value for each spectrum using the processor.

Methods and systems for analysis and correction of mass spectrometer data

A corrected reporter ion intensity is calculated in tandem mass spectrometry based quantitation using isobaric labels. An analyte in each of two or more samples of a mixture of samples is labeled with a different isobaric label. The analyte is eluted from the mixture of samples and intensities of the eluting analyte are measured. An analyte intensity is selected at each of at least two times from the measured intensities. Tandem mass spectrometry is performed on the eluting analyte at each of the at least two times. A plurality of reporter ion intensities is produced. A system of linear equations is created expressing each reporter ion intensity of the plurality of reporter ion intensities as a sum of a background noise intensity and the product of a fragmentation efficiency and an analyte intensity. A corrected reporter ion intensity is calculated from a solution of the system of linear equations.

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Palo Alto, CA, United States of America

Ignat V Shilov