TY - JOUR
T1 - Open-Source and FAIR Research Software for Proteomics
AU - Perez-Riverol, Yasset
AU - Bittremieux, Wout
AU - Noble, William S.
AU - Martens, Lennart
AU - Bilbao, Aivett
AU - Lazear, Michael R.
AU - Grüning, Bjorn
AU - Katz, Daniel S.
AU - MacCoss, Michael J.
AU - Dai, Chengxin
AU - Eng, Jimmy K.
AU - Bouwmeester, Robbin
AU - Shortreed, Michael R.
AU - Audain, Enrique
AU - Sachsenberg, Timo
AU - Van Goey, Jeroen
AU - Wallmann, Georg
AU - Wen, Bo
AU - Käll, Lukas
AU - Fondrie, William E.
N1 - The authors declare the following competing financial interest(s): W.E.F. is an employee of Talus Bioscience Inc., a drug-discovery biotechnology company that develops and contributes to OSS and does not currently sell software. Additionally, Talus Bioscience has a collaborative research agreement with Bruker. T.S. is an officer in OpenMS Inc., a non-profit foundation that manages the international coordination of OpenMS development. MRL is an employee of Belharra Therapeutics, Inc., and an officer of Chaparral Labs, Inc., a company offering SaaS solutions for proteomics, in addition to commercial support for OSS software. JVG is an employee of InstaDeep Ltd. The MacCoss Lab at the University of Washington receives funding from Agilent, Bruker, Sciex, Shimadzu, Thermo Fisher Scientific, and Waters to support the development of Skyline, an open-source software tool for quantitative proteomics. MJM is a paid consultant for Thermo Fisher Scientific. The CompOmics group at Ghent University and VIB (RB and LM) receives funding from Bruker. Acknowledgments
Y.P.-R. is funded by Wellcome grants (numbers 208391/Z/17/Z, 223745/Z/21/Z) and EMBL core funding. T.S. acknowledges funding by the Federal Ministry of Education and Research in the frame of de.NBI/ELIXIR-DE (W-de.NBI-022) and is supported by the Ministry of Science, Research and Arts Baden-Wu\u0308rttemberg. MJM acknowledges financial support from National Institutes of Health grants R24 GM141156, U01 DK137097, and U19 AG065156. R.B. and L.M. acknowledge funding from the Research Foundation Flanders (FWO) (12A6L24N, G010023N, and G028821N). L.M. acknowledges funding from the Ghent University Concerted Research Action (BOF21/GOA/033) and the European Union\u2019s Horizon Europe Programme (101080544, 101103253, 101195186, and 10119173). L.K. acknowledges funding from the Swedish Research Council (VR 2024-05887)
PY - 2025/5/2
Y1 - 2025/5/2
N2 - Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms, predictive models, and workflows, but the field faces challenges, including the increasing complexity of mass spectrometry data, limited reproducibility due to proprietary software, and difficulties integrating with other omics disciplines. Closed-source, platform-specific tools exacerbate these issues by restricting innovation, creating inefficiencies, and imposing hidden costs on the community. Open-source software (OSS), aligned with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), offers a solution by promoting transparency, reproducibility, and community-driven development, which fosters collaboration and continuous improvement. In this manuscript, we explore the role of OSS in computational proteomics, its alignment with FAIR principles, and its potential to address challenges related to licensing, distribution, and standardization. Drawing on lessons from other omics fields, we present a vision for a future where OSS and FAIR principles underpin a transparent, accessible, and innovative proteomics community.
AB - Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms, predictive models, and workflows, but the field faces challenges, including the increasing complexity of mass spectrometry data, limited reproducibility due to proprietary software, and difficulties integrating with other omics disciplines. Closed-source, platform-specific tools exacerbate these issues by restricting innovation, creating inefficiencies, and imposing hidden costs on the community. Open-source software (OSS), aligned with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), offers a solution by promoting transparency, reproducibility, and community-driven development, which fosters collaboration and continuous improvement. In this manuscript, we explore the role of OSS in computational proteomics, its alignment with FAIR principles, and its potential to address challenges related to licensing, distribution, and standardization. Drawing on lessons from other omics fields, we present a vision for a future where OSS and FAIR principles underpin a transparent, accessible, and innovative proteomics community.
KW - best practices
KW - computational proteomics
KW - data reuse
KW - FAIR principles
KW - mass spectrometry
KW - open data
KW - open source
KW - proteomics
UR - http://www.scopus.com/inward/record.url?scp=105003728834&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=105003728834&partnerID=8YFLogxK
U2 - 10.1021/acs.jproteome.4c01079
DO - 10.1021/acs.jproteome.4c01079
M3 - Review article
C2 - 40267229
AN - SCOPUS:105003728834
SN - 1535-3893
VL - 24
SP - 2222
EP - 2234
JO - Journal of Proteome Research
JF - Journal of Proteome Research
IS - 5
ER -