Maximally Efficient Modeling of DNA Sequence Motifs at All Levels of Complexity

Abstract

Abstract Identification of transcription factor binding sites is necessary for deciphering gene regulatory networks. Several new methods provide extensive data about the specificity of transcription factors but most methods for analyzing these data to obtain specificity models are limited in scope by, for example, assuming additive interactions or are inefficient in their exploration of more complex models. This article describes an approach—encoding of DNA sequences as the vertices of a regular simplex—that allows simultaneous direct comparison of simple and complex models, with higher-order parameters fit to the residuals of lower-order models. In addition to providing an efficient assessment of all model parameters, this approach can yield valuable insight into the mechanism of binding by highlighting features that are critical to accurate models.