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pmid:35198691

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

Zelu Huang · Weijia Kong · Bertrand Jernhan Wong · Huanhuan Gao · Tiannan Guo · Xianming Liu · Xiaoxian Du · Limsoon Wong · Wilson Wen Bin Goh

Data in brief · 2022 doi:10.1016/j.dib.2022.107919

Paper

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Experiment

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Proteomic datasets of HeLa and SiHa cell lines acquired by DDA-PASEF and diaPASEF.
doi
10.1016/j.dib.2022.107919
pmid
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Zelu Huang
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Weijia Kong
[2]
Bertrand Jernhan Wong
[3]
Huanhuan Gao
[4]
Tiannan Guo
[5]
Xianming Liu
[6]
Xiaoxian Du
[7]
Limsoon Wong
[8]
Wilson Wen Bin Goh
journal
Data in brief
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.
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