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Pipelines and Syste...
Pipelines and Systems for Threshold-Avoiding Quantification of LC-MS/MS Data
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- Sánchez Brotons, Alejandro (author)
- University of Groningen
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- Eriksson, Jonatan O. (author)
- Lund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,Clinical Protein Science and Imaging,Forskargrupper vid Lunds universitet,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH,Lund University Research Groups
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- Kwiatkowski, Marcel (author)
- University of Groningen,University of Innsbruck
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- Wolters, Justina C. (author)
- University of Groningen
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- Kema, Ido P. (author)
- University of Groningen
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- Barcaru, Andrei (author)
- University of Groningen
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- Kuipers, Folkert (author)
- University of Groningen
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- Bakker, Stephan J.L. (author)
- University of Groningen
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- Bischoff, Rainer (author)
- University of Groningen
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- Suits, Frank (author)
- IBM Research
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- Horvatovich, Péter (author)
- University of Groningen
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(creator_code:org_t)
- 2021-08-06
- 2021
- English 10 s.
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In: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; 93:32, s. 11215-11224
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Abstract
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- The accurate processing of complex liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) data from biological samples is a major challenge for metabolomics, proteomics, and related approaches. Here, we present the pipelines and systems for threshold-avoiding quantification (PASTAQ) LC-MS/MS preprocessing toolset, which allows highly accurate quantification of data-dependent acquisition LC-MS/MS datasets. PASTAQ performs compound quantification using single-stage (MS1) data and implements novel algorithms for high-performance and accurate quantification, retention time alignment, feature detection, and linking annotations from multiple identification engines. PASTAQ offers straightforward parameterization and automatic generation of quality control plots for data and preprocessing assessment. This design results in smaller variance when analyzing replicates of proteomes mixed with known ratios and allows the detection of peptides over a larger dynamic concentration range compared to widely used proteomics preprocessing tools. The performance of the pipeline is also demonstrated in a biological human serum dataset for the identification of gender-related proteins.
Subject headings
- NATURVETENSKAP -- Biologi -- Biokemi och molekylärbiologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Biochemistry and Molecular Biology (hsv//eng)
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- art (subject category)
- ref (subject category)
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Sánchez Brotons, ...
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Eriksson, Jonata ...
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Kwiatkowski, Mar ...
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Wolters, Justina ...
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Kema, Ido P.
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Barcaru, Andrei
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show more...
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Kuipers, Folkert
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Bakker, Stephan ...
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Bischoff, Rainer
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Suits, Frank
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Horvatovich, Pét ...
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Biological Scien ...
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and Biochemistry and ...
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Analytical Chemi ...
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Lund University