Dataset Information

Comparison of database search strategies for high precursor mass accuracy MS/MS data.

ABSTRACT: In shotgun proteomics, the analysis of tandem mass spectrometry data from peptides can benefit greatly from high mass accuracy measurements. In this study, we have evaluated two database search strategies which use high mass accuracy measurements of the peptide precursor ion. Our results indicate that peptide identifications are improved when spectra are searched with a wide mass tolerance window and precursor mass is used as a filter to discard incorrect matches. Database searches with a peptide data set constrained to peptides within a narrow mass window resulted in fewer peptide identifications but a significantly faster database search time.

SUBMITTER: Hsieh EJ

PROVIDER: S-EPMC2818881 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature

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Comparison of database search strategies for high precursor mass accuracy MS/MS data.

Hsieh Edward J EJ Hoopmann Michael R MR MacLean Brendan B MacCoss Michael J MJ

Journal of proteome research 20100201 2

In shotgun proteomics, the analysis of tandem mass spectrometry data from peptides can benefit greatly from high mass accuracy measurements. In this study, we have evaluated two database search strategies which use high mass accuracy measurements of the peptide precursor ion. Our results indicate that peptide identifications are improved when spectra are searched with a wide mass tolerance window and precursor mass is used as a filter to discard incorrect matches. Database searches with a peptid ...[more]

PMID: 19938873

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Project description:MS-based proteomics generates rapidly increasing amounts of precise and quantitative information. Analysis of individual proteomic experiments has made great strides, but the crucial ability to compare and store information across different proteome measurements still presents many challenges. For example, it has been difficult to avoid contamination of databases with low quality peptide identifications, to control for the inflation in false positive identifications when combining data sets, and to integrate quantitative data. Although, for example, the contamination with low quality identifications has been addressed by joint analysis of deposited raw data in some public repositories, we reasoned that there should be a role for a database specifically designed for high resolution and quantitative data. Here we describe a novel database termed MaxQB that stores and displays collections of large proteomics projects and allows joint analysis and comparison. We demonstrate the analysis tools of MaxQB using proteome data of 11 different human cell lines and 28 mouse tissues. The database-wide false discovery rate is controlled by adjusting the project specific cutoff scores for the combined data sets. The 11 cell line proteomes together identify proteins expressed from more than half of all human genes. For each protein of interest, expression levels estimated by label-free quantification can be visualized across the cell lines. Similarly, the expression rank order and estimated amount of each protein within each proteome are plotted. We used MaxQB to calculate the signal reproducibility of the detected peptides for the same proteins across different proteomes. Spearman rank correlation between peptide intensity and detection probability of identified proteins was greater than 0.8 for 64% of the proteome, whereas a minority of proteins have negative correlation. This information can be used to pinpoint false protein identifications, independently of peptide database scores. The information contained in MaxQB, including high resolution fragment spectra, is accessible to the community via a user-friendly web interface at http://www.biochem.mpg.de/maxqb.

Dataset Information

Comparison of database search strategies for high precursor mass accuracy MS/MS data.

Publications

Comparison of database search strategies for high precursor mass accuracy MS/MS data.

Similar Datasets

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