ROIMCR: a powerful analysis strategy for LC-MS metabolomic datasets
[Background] The analysis of LC-MS metabolomic datasets appears to be a challenging task in a wide range of disciplines since it demands the highly extensive processing of a vast amount of data. Different LC-MS data analysis packages have been developed in the last few years to facilitate this analysis. However, most of these strategies involve chromatographic alignment and peak shaping and often associate each “feature” (i.e., chromatographic peak) with a unique m/z measurement. Thus, the development of an alternative data analysis strategy that is applicable to most types of MS datasets and properly addresses these issues is still a challenge in the metabolomics field.
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| Main Authors: | , , |
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| Other Authors: | |
| Format: | artículo biblioteca |
| Published: |
BioMed Central
2019-05-17
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| Subjects: | VRK1, Vaccinia-related kinase 1, Olaparib, Ionizing radiations, H2AX, NBS1, 53BP1, Histone H4, DNA repair, |
| Online Access: | http://hdl.handle.net/10261/181669 http://dx.doi.org/10.13039/501100002809 http://dx.doi.org/10.13039/501100003176 http://dx.doi.org/10.13039/501100000781 http://dx.doi.org/10.13039/501100003339 http://dx.doi.org/10.13039/501100003329 |
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| Summary: | [Background] The analysis of LC-MS metabolomic datasets appears to be a challenging task in a wide range of disciplines since it demands the highly extensive processing of a vast amount of data. Different LC-MS data analysis packages have been developed in the last few years to facilitate this analysis. However, most of these strategies involve chromatographic alignment and peak shaping and often associate each “feature” (i.e., chromatographic peak) with a unique m/z measurement. Thus, the development of an alternative data analysis strategy that is applicable to most types of MS datasets and properly addresses these issues is still a challenge in the metabolomics field. |
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