2019 Association of Biomolecular Resource Facilities Multi-laboratory Data-Independent Acquisition Study

Published

June 2, 2023

Author(s)

Benjamin Neely, Paul Stemmer, Brian Searle, Laura Herring, LeRoy Martin, Mukul Midha, Brett Phinney, Baozhen Shan, Magnus Palmblad, Yan Wang, Pratik Jagtap, Joanna Kirkpatrick

Abstract

Despite the advantages of fewer missing values by collecting fragment ion data on all analytes in the sample as well as the potential for deeper coverage, the adoption of data-independent acquisition (DIA) in proteomics core facility settings has been slow. The Association of Biomolecular Resource Facilities conducted a large interlaboratory study to evaluate DIA performance in proteomics laboratories with various instrumentation. Participants were supplied with generic methods and a uniform set of test samples. The resulting 49 DIA datasets act as benchmarks and have utility in education and tool development. The sample set consisted of a tryptic HeLa digest spiked with high or low levels of 4 exogenous proteins. Data are available in MassIVE MSV000086479. Additionally, we demonstrate how the data can be analyzed by focusing on 2 datasets using different library approaches and show the utility of select summary statistics. These data can be used by DIA newcomers, software developers, or DIA experts evaluating performance with different platforms, acquisition settings, and skill levels.

Citation

The Journal of Biomolecular Techniques

Volume

34

Issue

2

Pub Type

Journals

Download Paper

https://doi.org/10.7171/3fc1f5fe.9b78d780

Local Download

Keywords

data-independent acquisition, label-free quantification, DIA, DDA, ABRF, proteomics

Citation

Neely, B. , Stemmer, P. , Searle, B. , Herring, L. , Martin, L. , Midha, M. , Phinney, B. , Shan, B. , Palmblad, M. , Wang, Y. , Jagtap, P. and Kirkpatrick, J. (2023), 2019 Association of Biomolecular Resource Facilities Multi-laboratory Data-Independent Acquisition Study, The Journal of Biomolecular Techniques, [online], https://doi.org/10.7171/3fc1f5fe.9b78d780, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=929177 (Accessed November 23, 2025)