Hi ChAMP users,

I am running the Champ according to the steps in the documentation. However, when trying to analyze the champ.block, I get errors, and from some reason - a different error in each run.

My data includes 37 samples analyzed by EPIC array. All the analyses up to this level (QC, norm, SVD, DMP) went smoothly.

This is the problematic line:

myBlock <- champ.Block(beta=myNorm,pheno=myLoad$pd$Sample_Group,arraytype="EPIC")

And here are the error lines:

Error in names(revOrder) <- seq_along(ret$idx) :
  attempt to set an attribute on NULL

OR

Error in x[[1]] : subscript out of bounds

Any idea how to solve this? Anyone else had this problem?

Thank you

Amit

Hello Amit:

Could you provide two things: one is sessionInfo, I want to know which version of ChAMP you are using, and secondly, could you paste more information here? I remember all champ function should return many messages, by providing them I could locate problem faster.

Best

Yuan Tian

Hello Yuan

I tried running the EPIC test data and had the same problem.

    Edit: I ran the 450K data and it worked smoothly.

In the global environment variables I see "probe.features", but not "probe.features.epic".

Here is the script I am using:

library(ChAMP)

data(EPICSimData)

champ.QC()

myNorm <- champ.norm(beta=myLoad$beta, arraytype="EPIC")

champ.SVD(beta=myNorm,pd=myLoad$pd)

myDMR <- champ.DMR(beta=myNorm,pheno=myLoad$pd$Sample_Group, method="Bumphunter")

DMR.GUI(DMR=myDMR)

And here are the messages I get until the R freezes while running DMR.GUI:

!!! important !!! Since we just upgrated champ.DMP() function, which is now can support multiple phenotypes. Here in DMR.GUI() function, if you want to use "runDMP" parameter, and your pheno contains more than two groups of phenotypes, you MUST specify compare.group parameter as compare.group=c("A","B") to get DMP value between group A and group B.

[ Section 1: Calculate DMP Start  ]

  You pheno is character type.

    Your pheno information contains following groups. >>

    <control>:8 samples.

    <case>:8 samples.

  Your pheno contains EXACTLY two phenotypes, which is good, compare.group is not needed.

Calculating DMP

[===========================]

[<<<<< ChAMP.DMP START >>>>>]

!!! Important !!! New Modification has been made on champ.DMP(): 

    (1): In this version champ.DMP() if your pheno parameter contains more than two groups of phenotypes, champ.DMP() would do pairewise differential methylated analysis between each pair of them. But you can also specify compare.group to only do comparasion between any two of them.

    (2): champ.DMP() now support numeric as pheno, and will do linear regression on them. So covariates like age could be inputted in this function. You need to make sure your inputted "pheno" parameter is "numeric" type.

[ Section 1:  Check Input Pheno Start ]

  You pheno is character type.

    Your pheno information contains following groups. >>

    <control>:8 samples.

    <case>:8 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.

    control_to_case compare group : control, case

[ Section 1:  Check Input Pheno Done ]

[ Section 2:  Find Differential Methylated CpGs Start ]

  -----------------------------

  Start to Compare : control, case

  Contrast Matrix

          Contrasts

Levels     pcontrol-pcase

  pcase                -1

  pcontrol              1

  You have found 780385 significant MVPs with a BH adjusted P-value below 1.

  Calculate DMP for control and case 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.]

[ Section 1: Calculate DMP Done  ]

Thank you again,

Amit