Dear List,

For high-throughput experiments (mircroarray, RNASeq, etc) with many
batches of samples, as a routine procedure, we are suggested to apply
Combat, SVA, PCA or PEER method to remove batch effects and hidden
variables before any downstream analysis. But in terms of specific steps, I
have listed the following 3 methods after normalization. Could anybody tell
me which method is the best or other suggestions?

Method1:
    Step1: remove outliers
    Step2: remove *Batch effects *if we know the exact batches
    Step3: apply SVA/PCA/PEER to remove *other hidden variables*.

Method2:
    Step1: remove outliers
    Step2: apply SVA/PCA/PEER to remove *Batch effects and other hidden *
variables.

Method3:
    Step1: directly apply SVA/PCA/PEER to remove *outliers, Batch effects
and other hidden variables* in one step.

Many thanks,
Shirley

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