A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data

  title={A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data},
  author={J Luo and Melanie Schumacher and Anna Scherer and Despina Sanoudou and Dalila Megherbi and Tanya Davison and Tingyan Shi and Weida Tong and Leming Shi and Huixiao Hong and Chunfang Zhao and Fathi Elloumi and Weiwei Shi and Robert W. L. Thomas and Shang Ming Lin and Guy Tillinghast and Guixia. Liu and Yi-yi Zhou and Damir Herman and Yan Xiu Li and Y Deng and Hengfu Fang and Pierre Bushel and Mark Woods and Jinming Zhang},
  booktitle={The Pharmacogenomics Journal},
Batch effects are the systematic non-biological differences between batches (groups) of samples in microarray experiments due to various causes such as differences in sample preparation and hybridization protocols. Previous work focused mainly on the development of methods for effective batch effects removal. However, their impact on cross-batch prediction performance, which is one of the most important goals in microarray-based applications, has not been addressed. This paper uses a broad… CONTINUE READING
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