Open Access Methodology article

A motif-independent metric for DNA sequence specificity

Luca Pinello12, Giosuè Lo Bosco3*, Bret Hanlon4 and Guo-Cheng Yuan12*

Author Affiliations

1 Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue, Boston MA 02115, USA

2 Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 44 Binney Street, Boston MA 02115, USA

3 Dipartimento di Matematica ed Informatica, Via Archirafi 34, Palermo 90123, Italy

4 Department of Statistics, University of Wisconsin, 1300 University Ave Madison, WI 53706, USA

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BMC Bioinformatics 2011, 12:408  doi:10.1186/1471-2105-12-408

Published: 21 October 2011

Additional files

Additional file 1:

Choice of the null model for sequence specificity. (a) The MIM values for H3k4me1 target sequences in different cell lines experiment with a null model obtained shuffling the original sequences. (b) The MIM values for the same experiment using as a null model a set of random sequences extracted from genome with matching lengths. Note that the the H1 cell line is far more specific than the other cell lines independently of the null model chosen.

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