Background#R##N#Genomic data production is at its highest level and continues to increase, making available novel primary data and existing public data to researchers for exploration. Here we explore the consequences of “batch” correction for biological discovery in two publicly available expression datasets. We consider this to include the estimation of and adjustment for wide-spread systematic heterogeneity in genomic measurements that is unrelated to the effects under study, whether it be technical or biological in nature.
['Andrew E. Jaffe', 'Thomas M. Hyde', 'Joel E. Kleinman', 'Daniel R. Weinbergern', 'Joshua G. Chenoweth', 'Ron McKay', 'Jeffrey T. Leek', 'Carlo Colantuoni']
Practical impacts of genomic data “cleaning” on biological discovery using surrogate variable analysis