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Sökning: WFRF:(Karaman Ibrahim.)

  • Resultat 1-8 av 8
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1.
  • Glasbey, JC, et al. (författare)
  • 2021
  • swepub:Mat__t
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2.
  • 2021
  • swepub:Mat__t
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3.
  • Bravo, L, et al. (författare)
  • 2021
  • swepub:Mat__t
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4.
  • Tabiri, S, et al. (författare)
  • 2021
  • swepub:Mat__t
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5.
  • 2021
  • swepub:Mat__t
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6.
  • Climaco Pinto, Rui, et al. (författare)
  • Finding Correspondence between Metabolomic Features in Untargeted Liquid Chromatography-Mass Spectrometry Metabolomics Datasets.
  • 2022
  • Ingår i: Analytical chemistry. - : American Chemical Society (ACS). - 1520-6882 .- 0003-2700. ; 94:14, s. 5493-5503
  • Tidskriftsartikel (refereegranskat)abstract
    • Integration of multiple datasets can greatly enhance bioanalytical studies, for example, by increasing power to discover and validate biomarkers. In liquid chromatography-mass spectrometry (LC-MS) metabolomics, it is especially hard to combine untargeted datasets since the majority of metabolomic features are not annotated and thus cannot be matched by chemical identity. Typically, the information available for each feature is retention time (RT), mass-to-charge ratio (m/z), and feature intensity (FI). Pairs of features from the same metabolite in separate datasets can exhibit small but significant differences, making matching very challenging. Current methods to address this issue are too simple or rely on assumptions that cannot be met in all cases. We present a method to find feature correspondence between two similar LC-MS metabolomics experiments or batches using only the features' RT, m/z, and FI. We demonstrate the method on both real and synthetic datasets, using six orthogonal validation strategies to gauge the matching quality. In our main example, 4953 features were uniquely matched, of which 585 (96.8%) of 604 manually annotated features were correct. In a second example, 2324 features could be uniquely matched, with 79 (90.8%) out of 87 annotated features correctly matched. Most of the missed annotated matches are between features that behave very differently from modeled inter-dataset shifts of RT, MZ, and FI. In a third example with simulated data with 4755 features per dataset, 99.6% of the matches were correct. Finally, the results of matching three other dataset pairs using our method are compared with a published alternative method, metabCombiner, showing the advantages of our approach. The method can be applied using M2S (Match 2 Sets), a free, open-source MATLAB toolbox, available at https://github.com/rjdossan/M2S.
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7.
  • Evangelou, Evangelos, et al. (författare)
  • Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.
  • 2018
  • Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 50:10, s. 1412-1425
  • Tidskriftsartikel (refereegranskat)abstract
    • High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.
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  • Resultat 1-8 av 8

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