Evidence map›Paper›PMID 34239088›Full record

ArticleNature biotechnology2021

MaxDIA enables library-based and library-free data-independent acquisition proteomics.

Pavel Sinitcyn, Hamid Hamzeiy, Favio Salinas Soto, Daniel Itzhak, Frank McCarthy, Christoph Wichmann, Martin Steger, Uli Ohmayer, Ute Distler, Stephanie Kaspar-Schoenefeld and 8 more

Abstract read
In one paragraph

Article in Nature biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers.

0numbers the graph read from it
0cells of the map it votes in
126citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

126 citing papers in PubMed.

  1. Preprocessing Large-Scale Proteomics Data.Methods in molecular biology (Clifton, N.J.) · 2027
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  16. Methods for the Investigation of Protein-Ligands Interactions.Advances in experimental medicine and biology · 2026
    Review
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  20. Article

66 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

Pavel Sinitcyn *Computational Systems Biochemistry Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany.ORCID http://orcid.org/0000-0002-2653-1702
Hamid Hamzeiy *Computational Systems Biochemistry Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany.ORCID http://orcid.org/0000-0001-7990-2530
Favio Salinas Soto *Computational Systems Biochemistry Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany.
Daniel ItzhakChan Zuckerberg Biohub, San Francisco, CA, USA.
Frank McCarthyChan Zuckerberg Biohub, San Francisco, CA, USA.ORCID http://orcid.org/0000-0002-7933-6847
Christoph WichmannComputational Systems Biochemistry Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany.
Martin StegerEvotec München GmbH, Martinsried, Germany.
Uli OhmayerEvotec München GmbH, Martinsried, Germany.
Ute DistlerInstitute for Immunology, Johannes Gutenberg University, Mainz, Germany.ORCID http://orcid.org/0000-0002-8031-6384
Stephanie Kaspar-SchoenefeldBruker Daltonik, GmbH, Bremen, Germany.
Nikita PrianichnikovComputational Systems Biochemistry Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany.
Şule YılmazComputational Systems Biochemistry Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany.
Jan Daniel RudolphComputational Systems Biochemistry Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany.ORCID http://orcid.org/0000-0003-4196-057X
Stefan TenzerInstitute for Immunology, Johannes Gutenberg University, Mainz, Germany.ORCID http://orcid.org/0000-0003-3034-0017
Yasset Perez-RiverolEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.ORCID http://orcid.org/0000-0001-6579-6941
Nagarjuna NagarajBruker Daltonik, GmbH, Bremen, Germany.
Sean J HumphreySchool of Life and Environmental Sciences, Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia.ORCID http://orcid.org/0000-0002-2666-9744
Jürgen CoxComputational Systems Biochemistry Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany. cox@biochem.mpg.de.ORCID http://orcid.org/0000-0001-8597-205X

Funding

Biotechnology and Biological Sciences Research Council BB/P024599/1
6 · The paper itself

Abstract

MaxDIA is a software platform for analyzing data-independent acquisition (DIA) proteomics data within the MaxQuant software environment. Using spectral libraries, MaxDIA achieves deep proteome coverage with substantially better coefficients of variation in protein quantification than other software. MaxDIA is equipped with accurate false discovery rate (FDR) estimates on both library-to-DIA match and protein levels, including when using whole-proteome predicted spectral libraries. This is the foundation of discovery DIA-hypothesis-free analysis of DIA samples without library and with reliable FDR control. MaxDIA performs three- or four-dimensional feature detection of fragment data, and scoring of matches is augmented by machine learning on the features of an identification. MaxDIA's bootstrap DIA workflow performs multiple rounds of matching with increasing quality of recalibration and stringency of matching to the library. Combining MaxDIA with two new technologies-BoxCar acquisition and trapped ion mobility spectrometry-both lead to deep and accurate proteome quantification.

Indexed as

ProteomeProteomicsPeptide LibrarySoftwarePeptide LibraryProteome

Identifiers

PMID34239088
PMCPMC8668435

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.