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Proteomic datasets of HeLa and SiHa cell lines acquired by DDA-PASEF and diaPASEF
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 ac...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8844217/ https://www.ncbi.nlm.nih.gov/pubmed/35198691 http://dx.doi.org/10.1016/j.dib.2022.107919 |
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author | Huang, Zelu Kong, Weijia Wong, Bertrand Jernhan Gao, Huanhuan Guo, Tiannan Liu, Xianming Du, Xiaoxian Wong, Limsoon Goh, Wilson Wen Bin |
author_facet | Huang, Zelu Kong, Weijia Wong, Bertrand Jernhan Gao, Huanhuan Guo, Tiannan Liu, Xianming Du, Xiaoxian Wong, Limsoon Goh, Wilson Wen Bin |
author_sort | Huang, Zelu |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8844217 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-88442172022-02-22 Proteomic datasets of HeLa and SiHa cell lines acquired by DDA-PASEF and diaPASEF Huang, Zelu Kong, Weijia Wong, Bertrand Jernhan Gao, Huanhuan Guo, Tiannan Liu, Xianming Du, Xiaoxian Wong, Limsoon Goh, Wilson Wen Bin Data Brief Data Article 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. Elsevier 2022-02-04 /pmc/articles/PMC8844217/ /pubmed/35198691 http://dx.doi.org/10.1016/j.dib.2022.107919 Text en © 2022 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Huang, Zelu Kong, Weijia Wong, Bertrand Jernhan Gao, Huanhuan Guo, Tiannan Liu, Xianming Du, Xiaoxian Wong, Limsoon Goh, Wilson Wen Bin Proteomic datasets of HeLa and SiHa cell lines acquired by DDA-PASEF and diaPASEF |
title | Proteomic datasets of HeLa and SiHa cell lines acquired by DDA-PASEF and diaPASEF |
title_full | Proteomic datasets of HeLa and SiHa cell lines acquired by DDA-PASEF and diaPASEF |
title_fullStr | Proteomic datasets of HeLa and SiHa cell lines acquired by DDA-PASEF and diaPASEF |
title_full_unstemmed | Proteomic datasets of HeLa and SiHa cell lines acquired by DDA-PASEF and diaPASEF |
title_short | Proteomic datasets of HeLa and SiHa cell lines acquired by DDA-PASEF and diaPASEF |
title_sort | proteomic datasets of hela and siha cell lines acquired by dda-pasef and diapasef |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8844217/ https://www.ncbi.nlm.nih.gov/pubmed/35198691 http://dx.doi.org/10.1016/j.dib.2022.107919 |
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