Open Access Software

xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data

Karan Uppal16, Quinlyn A Soltow2, Frederick H Strobel3, W Stephen Pittard1, Kim M Gernert1, Tianwei Yu4 and Dean P Jones25*

Author Affiliations

1 BimCore, School of Medicine, Emory University, Atlanta, GA, USA

2 Department of Medicine, Division of Pulmonary, Allergy and Critical Care, Emory University, Atlanta, GA, USA

3 Mass Spectrometry Center, Emory University, Atlanta, GA, USA

4 Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA

5 Clinical Biomarkers Laboratory, Emory University, Atlanta, GA, USA

6 School of Biology, Georgia Institute of Technology, Atlanta, GA, USA

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BMC Bioinformatics 2013, 14:15  doi:10.1186/1471-2105-14-15

Published: 16 January 2013

Additional files

Additional file 1:

xMSanalyzer results at different +/− m/z tolerance levels (ppm) for merging features identified at {3,0.3} and {3,0.8} (Sample Set 1, 44 samples, min.exp = 50%).

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Additional file 2:

Feature detection using apLCMS while varying min.run and min.pres in a) Sample Set 1 Column B; b) Sample Set 2 AE Column; and c) Sample Set 2 C18Column.

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Additional file 3:

Venn Diagrams representing overlapping features between the default setting and variations in min.run at min.pres = 0.3. Only unique features atm/ztolerance level of 10 ppm were used to generate Venn diagrams using BioVenn (http://www.cmbi.ru.nl/cdd/biovenn/ webcite).

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Additional file 4:

Effect of variation in min.bw and max.bw on feature detection at default settings using a random subset of 10 samples from the Sample Set 1 Column A.

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Additional file 5:

Results for merging more than two parameter settings using the Sample Set 1 Column A.

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Additional file 6:

Evaluating fitness of parameter combinations based on parameter sensitivity analysis in a) Sample Set 1 Column B; b) Sample Set 2 Column A; and c) Sample Set 2 Column B.

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Additional file 7:

R code for xMSanalyzer.

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Additional file 8:

Extracted ion chromatograms of unique features identified by xMSanalyzer in three biological samples: a) m/z 290.1358 (Gly-Asp-Val); b) m/z 425.16421 (Asp-Tyr-Gln); c) m/z 175.1187 (arginine).

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Additional file 9:

Summary of MS/MS analysis.

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Additional file 10:

MS/MS validation results for the metabolites exclusively identified by xMSanalyzer and with matches in Metlin. The first column is the full MS scan, second column is the MS/MS spectrum on LTQ Velos Orbitrap, and the third column shows the corresponding MS/MS spectrum from Metlin’s database.

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Additional file 11:

MS/MS validation results for the 8 putative metabolites identified using DeconMSn. The first row shows the elution profile of the feature, middle row shows the full MS scan, and the last row shows the deconvoluted MS/MS spectrum obtained from DeconMSn.

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