Cancer Inform 9 251-5
Wang J, Byers L, Yordy J, Liu W, Shen L, Baggerly K, Giri U, Myers J, Ang K, Story M, Girard L, Minna J, Heymach J, Coombes K
Department of Bioinformatics and Computational Biology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA.
BACKGROUND: While trying to integrate multiple data sets collected by different researchers, we noticed that the sample names were frequently entered inconsistently. Most of the variations appeared to involve punctuation, white space, or their absence, at the juncture between alphabetic and numeric portions of the cell line name.
RESULTS: Reasoning that the variant names could be described in terms of mutations or deletions of character strings, we implemented a simple version of the Needleman-Wunsch global sequence alignment algorithm and applied it to the cell line names. All correct matches were found by this procedure. Incorrect matches only occured when a cell line was present in one data set but not in the other. The raw match scores tended to be substantially worse for the incorrect matches.
CONCLUSIONS: A simple application of the Needleman-Wunsch global sequence alignment algorithm provides a useful first pass at matching sample names from different data sets.