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Proteomic datasets of HeLa and SiHa cell lines acquired by DDA-PASEF and diaPASEF.

Authors :
Huang Z
Kong W
Wong BJ
Gao H
Guo T
Liu X
Du X
Wong L
Goh WWB
Source :
Data in brief [Data Brief] 2022 Feb 04; Vol. 41, pp. 107919. Date of Electronic Publication: 2022 Feb 04 (Print Publication: 2022).
Publication Year :
2022

Abstract

We present four datasets on proteomics profiling of HeLa and SiHa cell lines associated with the research described in the paper "PROTREC: A probability-based approach for recovering missing proteins based on biological networks" [1]. Proteins in each cell line were acquired by two different data acquisition methods. The first was Data Dependent Acquisition-Parallel Accumulation Serial Fragmentation (DDA-PASEF) and the second was Parallel Accumulation-Serial Fragmentation combined with data-independent acquisition (diaPASEF) [2], [3]. Protein assembly was performed following search against the Swiss-Prot Human database using Peaks Studio for DDA datasets and Spectronaut for DIA datasets. The assembled result contains identified PSMs, peptides and proteins that are above threshold for each HeLa and SiHa sample. Coverage-wise, for DDA-PASEF, approximately 6,090 and 7,298 proteins were quantified for HeLa and SiHA sample, while13,339 and 8,773 proteins were quantified by diaPASEF for HeLa for SiHa sample, respectively. Consistency-wise, diaPASEF has fewer missing values (∼ 2%) compared to its DDA counterparts (∼5-7%). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the iProX partner repository [4] with the dataset identifier PXD029773.<br />Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (© 2022 The Author(s). Published by Elsevier Inc.)

Details

Language :
English
ISSN :
2352-3409
Volume :
41
Database :
MEDLINE
Journal :
Data in brief
Publication Type :
Academic Journal
Accession number :
35198691
Full Text :
https://doi.org/10.1016/j.dib.2022.107919