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Discovery of the Consistently Well-Performed Analysis Chain for SWATH-MS Based Pharmacoproteomic Quantification

Overview of attention for article published in Frontiers in Pharmacology, June 2018
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  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

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Title
Discovery of the Consistently Well-Performed Analysis Chain for SWATH-MS Based Pharmacoproteomic Quantification
Published in
Frontiers in Pharmacology, June 2018
DOI 10.3389/fphar.2018.00681
Pubmed ID
Authors

Jianbo Fu, Jing Tang, Yunxia Wang, Xuejiao Cui, Qingxia Yang, Jiajun Hong, Xiaoxu Li, Shuang Li, Yuzong Chen, Weiwei Xue, Feng Zhu

Abstract

Sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) has emerged as one of the most popular techniques for label-free proteome quantification in current pharmacoproteomic research. It provides more comprehensive detection and more accurate quantitation of proteins comparing with the traditional techniques. The performance of SWATH-MS is highly susceptible to the selection of processing method. Till now, ≥27 methods (transformation, normalization, and missing-value imputation) are sequentially applied to construct numerous analysis chains for SWATH-MS, but it is still not clear which analysis chain gives the optimal quantification performance. Herein, the performances of 560 analysis chains for quantifying pharmacoproteomic data were comprehensively assessed. Firstly, the most complete set of the publicly available SWATH-MS based pharmacoproteomic data were collected by comprehensive literature review. Secondly, substantial variations among the performances of various analysis chains were observed, and the consistently well-performed analysis chains (CWPACs) across various datasets were for the first time generalized. Finally, the log and power transformations sequentially followed by the total ion current normalization were discovered as one of the best performed analysis chains for the quantification of SWATH-MS based pharmacoproteomic data. In sum, the CWPACs identified here provided important guidance to the quantification of proteomic data and could therefore facilitate the cutting-edge research in any pharmacoproteomic studies requiring SWATH-MS technique.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 22%
Researcher 4 15%
Student > Master 3 11%
Lecturer > Senior Lecturer 2 7%
Other 1 4%
Other 4 15%
Unknown 7 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 19%
Agricultural and Biological Sciences 3 11%
Medicine and Dentistry 3 11%
Chemistry 3 11%
Engineering 2 7%
Other 5 19%
Unknown 6 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 July 2018.
All research outputs
#15,536,861
of 23,090,520 outputs
Outputs from Frontiers in Pharmacology
#6,594
of 16,441 outputs
Outputs of similar age
#209,952
of 329,059 outputs
Outputs of similar age from Frontiers in Pharmacology
#147
of 402 outputs
Altmetric has tracked 23,090,520 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 16,441 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 55% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,059 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 402 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.