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Table 2 Differentially abundant features identified by different methods based on the lung cancer exosomal lipids data

From: SDA: a semi-parametric differential abundance analysis method for metabolomics and proteomics data

Feature ID \(\hat {\gamma }_{g}\) \(\hat {\beta }_{g}\) q SDA q 2 T q 2 W q ELRT
C47H86O6 0.56 -1.17 0.02 0.01 0.25
C53H94O6 1.97 -0.7 0.02 0.02 0.08
C57H108O6* 1.13 -0.89 0.02 0.18 0.3 0.33
C59H104O6 2.54 -0.23 0.02 0.03 0.08
C54H100O6 1.3 -0.57 0.04 0.07 0.14
C49H92O6* 1.3 -0.66 0.05 0.26 0.32 0.33
C39H79N2O6P1* 0.38 0.07 0.7 0.74 0.73
C40H80N1O8P1* 0.31 0.07 0.38 0.32 0.33
C51H94O6* 1.87 -0.48 0.07 0.26 0.32 0.33
C52H98O6* 0.59 -0.8 0.07 0.18 0.32
C56H104O6* 0.99 -0.57 0.07 0.13 0.25
C56H106O6 -0.3 -0.94 0.07 0.04 0.3
C59H106O6* 1.03 -0.7 0.07 0.17 0.25
C59H112O6 -0.49 -0.91 0.07 0.01 0.13
C56H102O6* 1.13 -0.54 0.08 0.18 0.3
  1. FDR threshold was 0.1. Estimations of γ and β as well as q-values from different methods are presented. Lipid assignments of those features are provided in Table S1 in Additional file 2. * indicates features only identified by SDA. — indicates results not available. For C39H79N2O6P1 and C40H80N1O8P1, the calculation of \(\hat {\gamma }_{g}\) is not available because there is no zero value in the cancer samples. For the ELRT method, q-values for many features were not available