The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
CAMERA: An Integrated Strategy for Compound Spectra Extraction and Annotation of Liquid Chromatography/Mass Spectrometry Data Sets
Open accessAbstract
Liquid chromatography coupled to mass spectrometry is routinely used for metabolomics experiments. In contrast to the fairly routine and automated data acquisition steps, subsequent compound annotation and identification require extensive manual analysis and thus form a major bottleneck in data interpretation. Here we present CAMERA, a Bioconductor package integrating algorithms to extract compound spectra, annotate isotope and adduct peaks, and propose the accurate compound mass even in highly complex data. To evaluate the algorithms, we compared the annotation of CAMERA against a manually defined annotation for a mixture of known compounds spiked into a complex matrix at different concentrations. CAMERA successfully extracted accurate masses for 89.7% and 90.3% of the annotatable compounds in positive and negative ion modes, respectively. Furthermore, we present a novel annotation approach that combines spectral information of data acquired in opposite ion modes to further improve the annotation rate. We demonstrate the utility of CAMERA in two different, easily adoptable plant metabolomics experiments, where the application of CAMERA drastically reduced the amount of manual analysis.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Smith, C. A., Want, E. J., O'Maille, G., Abagyan, R., & Siuzdak, G. (2006) · Analytical Chemistry · doi:10.1021/ac051437y · Cited by 5,262
Pluskal, T., Castillo, S., Villar-Briones, A., & Orešič, M. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-395 · Cited by 3,845
Near linear time algorithm to detect community structures in large-scale networks
Raghavan, U. N., Albert, R., & Kumara, S. (2007) · Physical Review E · doi:10.1103/physreve.76.036106 · Cited by 3,502
Psychogios, N., Hau, D. D., Peng, J., Guo, A. C., Mandal, R., Bouatra, S., Sinelnikov, I., Krishnamurthy, R., Eisner, R., Gautam, B., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016957 · Cited by 1,703
Feist, A. M., Henry, C. S., Reed, J. L., Krummenacker, M., Joyce, A. R., Karp, P. D., Broadbelt, L. J., Hatzimanikatis, V., & Palsson, B. Ø. (2007) · Molecular Systems Biology · doi:10.1038/msb4100155 · Cited by 1,383
Highly sensitive feature detection for high resolution LC/MS
Tautenhahn, R., Böttcher, C., & Neumann, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-504 · Cited by 1,185
Self-citationOpenMS – An open-source software framework for mass spectrometry
Sturm, M., Bertsch, A., Gröpl, C., Hildebrandt, A., Hussong, R., Lange, E., Pfeifer, N., Schulz-Trieglaff, O., Zerck, A., Reinert, K., et al. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-163 · Cited by 644
Interferences and contaminants encountered in modern mass spectrometry
Keller, B. O., Sui, J., Young, A. B., & Whittal, R. M. (2008) · Analytica Chimica Acta · doi:10.1016/j.aca.2008.04.043 · Cited by 623
Data processing for mass spectrometry-based metabolomics
Katajamaa, M., & Orešič, M. (2007) · Journal of Chromatography A · doi:10.1016/j.chroma.2007.04.021 · Cited by 616
Tikunov, Y., Lommen, A., de Vos, C. H. R., Verhoeven, H. A., Bino, R. J., Hall, R. D., & Bovy, A. G. (2005) · Plant Physiology · doi:10.1104/pp.105.068130 · Cited by 513
A clustering algorithm based on graph connectivity
Hartuv, E., & Shamir, R. (2000) · Information Processing Letters · doi:10.1016/s0020-0190(00)00142-3 · Cited by 480
Dunn, W. B. (2008) · Physical Biology · doi:10.1088/1478-3975/5/1/011001 · Cited by 278
Expanding Coverage of the Metabolome for Global Metabolite Profiling
Yanes, O., Tautenhahn, R., Patti, G. J., & Siuzdak, G. (2011) · Analytical Chemistry · doi:10.1021/ac102981k · Cited by 274
Self-citationA general approach to calculating isotopic distributions for mass spectrometry
Yergey, J. A. (1983) · International Journal of Mass Spectrometry and Ion Physics · doi:10.1016/0020-7381(83)85053-0 · Cited by 222
Brown, M., Wedge, D. C., Goodacre, R., Kell, D. B., Baker, P. N., Kenny, L. C., Mamas, M. A., Neyses, L., & Dunn, W. B. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr079 · Cited by 192
Metabolite profiling as an aid to metabolic engineering in plants
Trethewey, R. N. (2004) · Current Opinion in Plant Biology · doi:10.1016/j.pbi.2003.12.003 · Cited by 179
Böttcher, C., von Roepenack-Lahaye, E., Schmidt, J., Schmotz, C., Neumann, S., Scheel, D., & Clemens, S. (2008) · Plant Physiology · doi:10.1104/pp.108.117754 · Cited by 159
Self-citationDistribution of sinapine and related compounds in seeds of Brassica and allied genera
Bouchereau, A., HAMELIN, J., Lamour, I., Renard, M., & Larher, F. (1991) · Phytochemistry · doi:10.1016/0031-9422(91)85031-t · Cited by 84
Simple Data-Reduction Method for High-Resolution LC–MS Data in Metabolomics
Scheltema, R. A., Decuypere, S., Dujardin, J., Watson, D., Jansen, R., & Breitling, R. (2009) · Bioanalysis · doi:10.4155/bio.09.146 · Cited by 56
Annotation of LC/ESI-MS Mass Signals
Tautenhahn, R., Böttcher, C., & Neumann, S. (2007) · Springer eBooks · doi:10.1007/978-3-540-71233-6_29 · Cited by 54
Self-citationA Statistically Rigorous Test for the Identification of Parent−Fragment Pairs in LC-MS Datasets
Ipsen, A. B., Want, E. J., Lindon, J. C., et al. (2010) · Analytical Chemistry · doi:10.1021/ac902361f · Cited by 33
Cited by
Feature-based molecular networking in the GNPS analysis environment
Nothias, L.-F., Petras, D., Schmid, R., Dührkop, K., Rainer, J., Sarvepalli, A., Protsyuk, I., Ernst, M., Tsugawa, H., Fleischauer, M., et al. (2020) · Nature Methods · doi:10.1038/s41592-020-0933-6 · Cited by 1,634
Self-citationPang, Z., Zhou, G., Ewald, J., Chang, L., Hacariz, O., Basu, N., & Xia, J. (2022) · Nature Protocols · doi:10.1038/s41596-022-00710-w · Cited by 1,444
Current approaches and challenges for the metabolite profiling of complex natural extracts
Wolfender, J.-L., Marti, G., Thomas, A., & Bertrand, S. (2015) · Journal of Chromatography A · doi:10.1016/j.chroma.2014.10.091 · Cited by 635
Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics
Dunn, W. B., Erban, A., Weber, R. J. M., Creek, D. J., Brown, M., Breitling, R., Hankemeier, T., Goodacre, R., Neumann, S., Kopka, J., et al. (2013) · Metabolomics · doi:10.1007/s11306-012-0434-4 · Cited by 555
Self-citationThe food metabolome: a window over dietary exposure
Scalbert, A., Brennan, L., Manach, C., Andres-Lacueva, C., Dragsted, L. O., Draper, J., Rappaport, S. M., van der Hooft, J. J., & Wishart, D. S. (2014) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.113.076133 · Cited by 519
Metadata
- Authors
- Kuhl, C., Tautenhahn, R., Böttcher, C., Larson, T. R., & Neumann, S.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2011-12-12
- Volume
- 84
- Issue
- 1
- Pages
- 283-289
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W143096088
- Cited by
- 1,203
- References
- 21
- FWCI
- 12.11
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
