Evidence map›Paper›PMID 38854051›Full record

ArticlebioRxiv : the preprint server for biology2024

diaTracer enables spectrum-centric analysis of diaPASEF proteomics data.

Kai Li, Guo Ci Teo, Kevin L Yang, Fengchao Yu, Alexey I Nesvizhskii

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Kai LiDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Guo Ci TeoDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA.
Kevin L YangDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Fengchao YuDepartment of Pathology, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0002-7695-3698
Alexey I NesvizhskiiDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.

Funding

COMPUTATIONAL TOOLS FOR MASS SPECTROMETRY-BASED INTERACTOME DATAR01GM094231 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Alexey I Nesvizhskii · 2010 to 2026
$5.4M
Michigan Center for Translational Cancer Proteogenomics-Diversity SupplementU24CA271037 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Saravana Mohan Dhanasekaran, Alexey I Nesvizhskii · 2022 to 2026
$4.4M
NCI NIH HHS U24 CA271037NIGMS NIH HHS R01 GM094231
6 · The paper itself

Abstract

Data-independent acquisition (DIA) has become a widely used strategy for peptide and protein quantification in mass spectrometry-based proteomics studies. The integration of ion mobility separation into DIA analysis, such as the diaPASEF technology available on Bruker's timsTOF platform, further improves the quantification accuracy and protein depth achievable using DIA. We introduce diaTracer, a new spectrum-centric computational tool optimized for diaPASEF data. diaTracer performs three-dimensional (m/z, retention time, ion mobility) peak tracing and feature detection to generate precursor-resolved "pseudo-MS/MS" spectra, facilitating direct ("spectral-library free") peptide identification and quantification from diaPASEF data. diaTracer is available as a stand-alone tool and is fully integrated into the widely used FragPipe computational platform. We demonstrate the performance of diaTracer and FragPipe using diaPASEF data from triple-negative breast cancer (TNBC), cerebrospinal fluid (CSF), and plasma samples, data from phosphoproteomics and HLA immunopeptidomics experiments, and low-input data from a spatial proteomics study. We also show that diaTracer enables unrestricted identification of post-translational modifications from diaPASEF data using open/mass-offset searches.

Identifiers

PMID38854051
PMCPMC11160675

What OpenQuestion holds

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Registered trials

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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.