Evidence map›Paper›PMID 29997509›Full record

ArticleFrontiers in pharmacology2018

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

Jianbo Fu, Jing Tang, Yunxia Wang, Xuejiao Cui, Qingxia Yang, Jiajun Hong, Xiaoxu Li, Shuang Li, Yuzong Chen, Weiwei Xue and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
6.4field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 76 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 2 countries.

Jianbo FuCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Jing TangCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Yunxia WangCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Xuejiao CuiCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Qingxia YangCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Jiajun HongCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Xiaoxu LiCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Shuang LiCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Yuzong ChenBioinformatics and Drug Design Group, Department of Pharmacy, Center for Computational Science and Engineering, National University of Singapore, Singapore, Singapore.
Weiwei XueSchool of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China.
Feng ZhuCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Zhejiang University · CNChongqing University · CNNational University of Singapore · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

normalizationpharmacoproteomicsprocessing methodSWATH-MStransformation

Identifiers

PMID29997509
PMCPMC6028727
OpenAlexW2810968367

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.