Normalization and missing value imputation for label-free LC-MS analysis. Academic Article uri icon


  • Shotgun proteomic data are affected by a variety of known and unknown systematic biases as well as high proportions of missing values. Typically, normalization is performed in an attempt to remove systematic biases from the data before statistical inference, sometimes followed by missing value imputation to obtain a complete matrix of intensities. Here we discuss several approaches to normalization and dealing with missing values, some initially developed for microarray data and some developed specifically for mass spectrometry-based data.

published proceedings

  • BMC Bioinformatics

altmetric score

  • 1

author list (cited authors)

  • Karpievitch, Y. V., Dabney, A. R., & Smith, R. D.

citation count

  • 244

complete list of authors

  • Karpievitch, Yuliya V||Dabney, Alan R||Smith, Richard D

publication date

  • November 2012