Algorithms Evaluation Based On Data-Independence-Acquisition Data Processing And Research On Quantitative Signal Extraction Algorithm For Peptide

Proteome attempts to character the expression of the full set of proteins for a biological sample under defined conditions qualitatively and quantitatively.Quantitative proteomics based on mass spectrometry(MS)is a hotspot in proteomics research.Data-dependent-acquisition(DDA)method was used to identify the peptide fragments with high signal intensity and abundant abundance in the MS spectrum,and the corresponding peptides were identified by the MS/MS spectrum.The drawbacks of the DDA strategy are obvious,whose MS/MS spectrum depends on the MS scan results,which are easy to cause low-abundance peptide loss,and have random results,poor reproducibility of the experiment.With the advance of MS technology and data analysis methods,data-independent-acquisition(DIA)is becoming the mainstream of quantitation proteomics.The DIA method is to divide the m/z ratio of precursor ion into several acquisition windows,and process sequential acquisition of all precursor ion information among the acquisition windows,resulting in several complex MS/MS spectra.DIA can take full advantage of precursor ion information in the MS spectrum,and achieve more accurate protein quantification.In this dissertation,the difference and relationship between DDA and DIA are discussed,and we summarize the DIA quantitative technology and the DIA quantitative software.Subsequently quantitative effect of DIA software is evaluated.Three different DIA datasets were used to compare the effect of DDA and DIA data processing with the traditional database searching method,and qualitative analysis based on mass spectrometry DIA and DDA methods were carried out.It was proved that the MS-DIA method was more effective in protein identification than the DDA method.In the second part of the paper,a new algorithm of XICFinder,which is used to the extracted ion chromatogram--the pivotal step of the label-free quantitative analysis,was developed.We introduce the XICFinder algorithm from the aspects of algorithm flow,principle,data structure and relationship of function called.The experimental data set of CPTAC.study6 was used to test the XICFinder.The influence of the minimum number of isotope peaks and the tolerance of precursor ion mass error on the performance of the algorithm was evaluated.Peptides were identified and quantified by XIC peaks,and compared with MaxQuant and PANDA.In terms of the XIC number,peptide identification rate,etc.,XICFinder has a good performance.