PXD028901-1

PXD028901 is an original dataset announced via ProteomeXchange.

Title	MSLibrarian: Optimized predicted spectral libraries for DIA proteomics
Description	Data-independent mass spectrometry is the method of choice for deep, consistent and accurate single-shot profiling in bottom-up proteomics. While classic workflows required auxiliary DDA-MS analysis of subject samples to derive prior knowledge spectral libraries for targeted quantification from DIA-MS maps, library-free approaches based on in silico predicted libraries promise deep DIA-MS profiling with reduced experimental effort and cost. Coverage and sensitivity in such analyses, however, is limited, in part, by large library size and persistent deviations from experimental data. We present MSLibrarian, a workflow and tool to obtain optimized predicted spectral libraries by the integrated usage of spectrum-centric DIA data interpretation via the DIA-Umpire approach to inform and calibrate the in silico predicted library approach. Predicted-vs-observed comparisons enable optimization of intensity prediction parameters, calibration of retention time prediction for deviating chromatographic setups and optimization of library scope and sample representativeness. Benchmarking via a dedicated ground-truth-embedded species mixture experiment and quantitative ratio-validation confirms gains of up to 9 % on precursor and 7 % protein level at equivalent FDR control and validation criteria. MSLibrarian has been implemented as open-source R software package and, with step-by-step usage instructions, is availabe at https://github.com/MarcIsak/MSLibrarian.
HostingRepository	PRIDE
AnnounceDate	2022-01-17
AnnouncementXML	Submission_2022-01-17_09:19:45.446.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Christofer Karlsson
SpeciesList	scientific name: Mus musculus (Mouse); NCBI TaxID: 10090; scientific name: Saccharomyces cerevisiae (Baker's yeast); NCBI TaxID: 4932;
ModificationList	carbamoylated residue
Instrument	Q Exactive HF-X

Revision	Datetime	Status	ChangeLog Entry
0	2021-10-04 04:44:35	ID requested
⏵ 1	2022-01-17 09:19:45	announced
2	2022-01-18 01:46:30	announced	2022-01-18: Updated publication reference for DOI(s): 10.1021/acs.jproteome.1c00796.
3	2023-11-14 08:53:43	announced	2023-11-14: Updated project metadata.

Dataset with its publication pending

submitter keyword: DIA, predicted spectral library, Q-Exactive, HF-X, LFQ bench

Johan Malmström
contact affiliation	Infection Medicine Proteomics Lab, Division of Infection Medicine (BMC), Faculty of Medicine, Lund University, Lund, Sweden
contact email	johan.malmstrom@med.lu.se
lab head
Christofer Karlsson
contact affiliation	Lund University
contact email	Christofer.Karlsson@med.lu.se
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2022/01/PXD028901

PRIDE project URI

• PRIDE
  1. PXD028901
     1. Label: PRIDE project
     2. Name: MSLibrarian: Optimized predicted spectral libraries for DIA proteomics