**0**wrote:

I have an experimental design as follows:

Patient | Disease | Treatment |

1 | Unaffected | Treated |

1 | Unaffected | Untreated |

2 | Unaffected | Treated |

2 | Unaffected | Untreated |

3 | Unaffected | Treated |

3 | Unaffected | Untreated |

4 | Affected | Treated |

4 | Affected | Untreated |

5 | Affected | Treated |

5 | Affected | Untreated |

6 | Affected | Treated |

6 | Affected | Untreated |

We'd like to test:

1) Untreated, Affected vs. Unaffected

2) Unaffected-only, Treated vs. Untreated

3) Affected-only, Treated vs. Untreated

We are trying to use SVA to also control for cell composition and the include the SV's in the model.

mod <- model.matrix(~0+Treatment:Disease, data=pd) mod0 <- model.matrix(~1, data=pd) svobj <- sva(M, mod, mod0) design <- model.matrix(data=pd, ~0+Treatment:Disease+svobj$sv) colnames(design) <- c(paste0('SV',seq(ncol(svobj$sv))),'Untreat_Unaff','Treat_Unaff','Untreat_Aff','Treat_Aff') contrast.matrix <- makeContrasts('Treat_Aff-Untreat_Aff', 'Treat_Unaff-Untreat_Unaff', 'Untreat_Aff-Untreat_Unaff', levels=design)

Then we'd like to account for pairing of patient samples without and with treatment using `duplicateCorrelation().`

dupCor <- duplicateCorrelation(M, design, block=factor(pd$Patient))

But we get this error:

Warning message in atanh(pmax(-1, rho)): "NaNs produced"

It works when I don't add the SV's to the model so just confused as to what's going on.

design <- model.matrix(data=pd, ~0+Treatment:Disease)

Is there something I'm not understanding about the design matrix, problem there causing this problem? Not at all confident we've set this up correctly.