Title

Processing strategies and software solutions for data-independent acquisition in mass spectrometry

UMMS Affiliation

Program in Molecular Medicine

Publication Date

3-1-2015

Document Type

Article

Disciplines

Amino Acids, Peptides, and Proteins | Biochemistry | Genomics | Molecular Biology

Abstract

Data-independent acquisition (DIA) offers several advantages over data-dependent acquisition (DDA) schemes for characterizing complex protein digests analyzed by LC-MS/MS. In contrast to the sequential detection, selection, and analysis of individual ions during DDA, DIA systematically parallelizes the fragmentation of all detectable ions within a wide m/z range regardless of intensity, thereby providing broader dynamic range of detected signals, improved reproducibility for identification, better sensitivity, and accuracy for quantification, and, potentially, enhanced proteome coverage. To fully exploit these advantages, composite or multiplexed fragment ion spectra generated by DIA require more elaborate processing algorithms compared to DDA. This review examines different DIA schemes and, in particular, discusses the concepts applied to and related to data processing. Available software implementations for identification and quantification are presented as comprehensively as possible and examples of software usage are cited. Processing workflows, including complete proprietary frameworks or combinations of modules from different open source data processing packages are described and compared in terms of software availability and usability, programming language, operating system support, input/output data formats, as well as the main principles employed in the algorithms used for identification and quantification. This comparative study concludes with further discussion of current limitations and expectable improvements in the short- and midterm future.

Keywords

Bottom-up proteomics, Data processing and analysis, Data-independent acquisition, Label-free quantification, Mass spectrometry-LC-MS/MS

DOI of Published Version

10.1002/pmic.201400323

Source

Proteomics. 2015 Mar;15(5-6):964-80. doi: 10.1002/pmic.201400323. Epub 2015 Feb 2. Link to article on publisher's site

Journal/Book/Conference Title

Proteomics

Related Resources

Link to Article in PubMed

PubMed ID

25430050

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