資料載入中.....
|
請使用永久網址來引用或連結此文件:
https://ir.lib.ncu.edu.tw/handle/987654321/102770
|
| 題名: | IMet-Q: A user-friendly tool for label-free metabolomics quantitation using dynamic peak-width determination |
| 作者: | 張彙音;Chang, Hui-Yin;Chen, Ching-Tai;Lih, T. Mamie;Lynn, Ke-Shiuan;Juo, Chiun-Gung;Hsu, Wen-Lian;Sung, Ting-Yi |
| 貢獻者: | 生醫理工學院生醫科學與工程學系 |
| 關鍵詞: | Abundance;Algorithms;Analytical chemistry;Arabidopsis;Arabidopsis - metabolism;Bioinformatics;Chromatography;Comics;Computational biology;Data processing;Datasets;Downloading;Humans;Identification;Informatics;Information science;Interfaces;Isotope ratios;Mass spectrometry;Metabolites;Metabolome;Metabolomics;Metabolomics - methods;Performance evaluation;Programming languages;Proteomics;Quantitation;Retention;Science;Scientific imaging;Software;Statistical analysis |
| 日期: | 2016-01-01 |
| 上傳時間: | 2026-04-23 11:16:21 (UTC+8) |
| 出版者: | Public Library of Science;United States: Public Library of Science |
| 摘要: | 摘要： Efficient and accurate quantitation of metabolites from LC-MS data has become an important topic. Here we present an automated tool, called iMet-Q (intelligent Metabolomic Quantitation), for label-free metabolomics quantitation from high-throughput MS1 data. By performing peak detection and peak alignment, iMet-Q provides a summary of quantitation results and reports ion abundance at both replicate level and sample level. Furthermore, it gives the charge states and isotope ratios of detected metabolite peaks to facilitate metabolite identification. An in-house standard mixture and a public Arabidopsis metabolome data set were analyzed by iMet-Q. Three public quantitation tools, including XCMS, MetAlign, and MZmine 2, were used for performance comparison. From the mixture data set, seven standard metabolites were detected by the four quantitation tools, for which iMet-Q had a smaller quantitation error of 12% in both profile and centroid data sets. Our tool also correctly determined the charge states of seven standard metabolites. By searching the mass values for those standard metabolites against Human Metabolome Database, we obtained a total of 183 metabolite candidates. With the isotope ratios calculated by iMet-Q, 49% (89 out of 183) metabolite candidates were filtered out. From the public Arabidopsis data set reported with two internal standards and 167 elucidated metabolites, iMet-Q detected all of the peaks corresponding to the internal standards and 167 metabolites. Meanwhile, our tool had small abundance variation (≤ 0.19) when quantifying the two internal standards and had higher abundance correlation (≥ 0.92) when quantifying the 167 metabolites. iMet-Q provides user-friendly interfaces and is publicly available for download at http://ms.iis.sinica.edu.tw/comics/Software_iMet-Q.html.
其他題名： PLoS One
出版者： United States: Public Library of Science
出版日期： 2016-01-19
出處： PloS one, 2016-01, Vol.11 (1), p.e0146112
資源來源： Agricultural & Environmental Science Collection
版權： COPYRIGHT 2016 Public Library of Science
版權： 2016 Chang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
版權： 2016 Chang et al 2016 Chang et al
識別號： ISSN: 1932-6203
識別號： EISSN: 1932-6203
識別號： DOI: 10.1371/journal.pone.0146112
識別號： PMID: 26784691 |
| 顯示於類別: | [生醫科學與工程學系] 期刊論文
|
文件中的檔案:
| 檔案 |
描述 |
大小 | 格式 | 瀏覽次數 |
|---|
| index.html | | 0Kb | HTML | 14 | 檢視/開啟 |
|
在NCUIR中所有的資料項目都受到原著作權保護.
|
