Dear, everyone.

Currently, I am doing find out DMPs in Champ using Illumina EPIC methylation array. And I am doing case-control studies

But I got the error message Error in champ.DMP() : ChAMP.DMP Have not detected even one significant CpGs. You may try other threshold. Then I found the reason why I got the error message due to the Benjamini-Hochberg correction, and my lowest adjusted p-values are 0.999996913. (adj.P.Val)

Therefore, when I am looking at GUI there is no result when the threshold is <0.05. When the threshold should be raised to 1.0, I can see the result.

(1) Threshold p<0.05

myDMP <- champ.DMP()

[ Section 1:  Check Input Pheno Start ]

  You pheno is character type.
    Your pheno information contains following groups. >>
    <Sarcopenia>:9 samples.
    <Normal>:9 samples.
    [The power of statistics analysis on groups contain very few samples may not strong.]
    pheno contains only 2 phenotypes
    compare.group parameter is NULL, two pheno types will be added into Compare List.
    Sarcopenia_to_Normal compare group : Sarcopenia, Normal

[ Section 1:  Check Input Pheno Done ]


[ Section 2:  Find Differential Methylated CpGs Start ]

  -----------------------------
  Start to Compare : Sarcopenia, Normal
  Contrast Matrix
             Contrasts
Levels        pSarcopenia-pNormal
  pNormal                      -1
  pSarcopenia                   1
  You have found 0 significant MVPs with a BH adjusted P-value below 0.05.
  Calculate DMP for Sarcopenia and Normal done.

[ Section 2:  Find Numeric Vector Related CpGs Done ]

Error in champ.DMP() : 
  ChAMP.DMP Have not detected even one significant CpGs. You may try other threshold.


sessionInfo( )

(2) Threshold p=1.0

myDMP <- champ.DMP(beta = myNorm,
               pheno = myLoad$pd$Sample_Group,
               compare.group = NULL,
               adjPVal = 1.0,
               adjust.method = "BH",
               arraytype = "EPIC")



  [ Section 1:  Check Input Pheno Done ]
   [ Section 2:  Find Differential Methylated CpGs Start ]

  -----------------------------
  Start to Compare : Sarcopenia, Normal
  Contrast Matrix
             Contrasts
  Levels        pSarcopenia-pNormal
  pNormal                      -1
  pSarcopenia                   1
  You have found 727958 significant MVPs with a BH adjusted P-value below 1.
  Calculate DMP for Sarcopenia and Normal done.

  [ Section 2:  Find Numeric Vector Related CpGs Done ]


  [ Section 3:  Match Annotation Start ]


  [ Section 3:  Match Annotation Done ]

  [<<<<<< ChAMP.DMP END >>>>>>]
  [===========================]
   [You may want to process DMP.GUI() or champ.GSEA() next.]

Is there any idea what the problem can be here? or should I use another correction method?

Any comments that help me are welcome. Any help would be greatly appreciated.

Kind regards, Seohyun