comparison NmrNormalization_script.R @ 6:221cbd549c40 draft default tip

planemo upload for repository https://github.com/workflow4metabolomics/normalization commit 4bbd4d65e954192aff1a4d210001deb625667136

5:3d00a98974b7

    # Reference spectrum
    # Recuperation spectres individus controle
    control.spectra <- data.normalized[,sampleMetadata[,pqnFactor]==nomControl]
    spectrum.ref <- apply(control.spectra,1,median)

    # Ratio between normalized and reference spectra
    data.normalized.ref <- data.normalized/spectrum.ref

    # Median ratio
    data.normalized.ref.median <- apply(data.normalized.ref,1,median)

    # Normalization
    data.normalizedPQN <- data.normalized[,1]/data.normalized.ref.median
    for (i in 2:ncol(data))
      data.normalizedPQN <- cbind(data.normalizedPQN,data.normalized[,i]/data.normalized.ref.median)

  ## OUTPUTS
  return(list(NormalizedBucketedSpectra))

}

6:221cbd549c40

    # Reference spectrum
    # Recuperation spectres individus controle
    control.spectra <- data.normalized[,sampleMetadata[,pqnFactor]==nomControl]
    spectrum.ref <- apply(control.spectra,1,median)
    for (j in 1:length(spectrum.ref))
    {
      if (spectrum.ref[j] == 0)
        spectrum.ref[j] <- mean(control.spectra[j, ])
      if (spectrum.ref[j] == 0)
        spectrum.ref[j] <- 10^(-24)
    }

    # Ratio between normalized and reference spectra
    data.normalized.ref <- data.normalized/spectrum.ref

    # Median ratio
    data.normalized.ref.median <- apply(data.normalized.ref,1,median)
    for (j in 1:length(data.normalized.ref.median))
      if (data.normalized.ref.median[j] == 0 | is.na(data.normalized.ref.median[j]) | data.normalized.ref.median == "NaN" | data.normalized.ref.median == "NA")
        data.normalized.ref.median[j] <- mean(data.normalized.ref[j, ])

    # Normalization
    data.normalizedPQN <- data.normalized[,1]/data.normalized.ref.median
    for (i in 2:ncol(data))
      data.normalizedPQN <- cbind(data.normalizedPQN,data.normalized[,i]/data.normalized.ref.median)

  ## OUTPUTS
  return(list(NormalizedBucketedSpectra))

}