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To compensate for systematic errors each array was normalised using loess normalisation, and then scaled so that the log-transformed ratios had the same median absolute deviation (Yang et al, 2002a, 2002b).
The signal median was quantile normalised between arrays followed by a LOESS normalisation within arrays.
Lumi (Du, 2008), also used in HumMethQCReport (Mancuso et al, 2011), offers an alternative to quantile normalisation through a robust spline normalisation, which is designed to normalise variance-stabilised data by combining features of both quantile and LOESS normalisation (Du, 2008).
PMOnly was chosen as a preferred method in previous studies [16], while Loess normalisation is an established method for pre-processing dual-channel arrays [13].
Results identify a method based on a combination of Loess normalisation and iterative K-means as best for time series normalisation for this problem.
Additional normalisation aims at reconciling use of both log ratios and log values by applying Loess normalisation to Affymetrix data and PMOnly normalisation to dual-channel data.
Similar(38)
Preprocessing was carried out by loess normalization.
We then applied Loess normalization to correct for GC bias.
The loess normalization based on all genes generated analogous results.
Of a selection of other normalisation methods, loess, and cubic-spline performed similarly to quantile and all of these methods out-performed simple median normalisation (Supplementary File 1).
Then, we performed a global intensity-dependent normalisation using the loess procedure [ 76] to correct the dye bias.
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