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Additional info for Advances in Genomic Sequence Analysis and Pattern Discovery (Science, Engineering, and Biology Informatics, 7)
Abstract RMESString class from which both the Word and the Sequence classes are derived. Indeed, in the current release of R’MES, the internal representation of words (coded as long integers) and sequences (coded as character vectors) are different enough to prevent the use of a single class for both entities. Figure 5 shows how these classes are organized. It also comes as no surprise that the main data structure used to store the results (the ResultSet class) is made of a series of vectors, one for each word-related quantity (count, expected count, variance, score and so on), indexed by an integer representation of each word.
Benos PV, Bulyk ML, Stormo GD. (2002) Additivity in protein-DNA interactions: How good an approximation is it? Nucleic Acids Res 30: 4442–4451. Bergman CM, Carlson JW, Celniker SE. (2005) Drosophila DNase I footprint database: A systematic genome annotation of transcription factor binding sites in the fruitfly, Drosophila melanogaster. Bioinformatics 21: 1747–1749. Bryne JC, Valen E, Tang M-HE et al. (2008) JASPAR, the open access database of transcription factor-binding profiles: New content and tools in the 2008 update.
In some cases it might be relevant to examine if the exceptionality of a word might be caused by the exceptionality of some of its subwords. R’MESPlot allows this, if result data are available December 21, 2010 42 18:19 9in x 6in Advances in Genomic Sequence Analysis and Pattern Discovery b1051-ch02 S. Schbath and M. Hoebeke Fig. 3. Screenshot of R’MESPlot showing how to plot word scores from two different result sets. Along the x-axis: scores computed using the Gaussian approximation. Along the y-axis: scores computed using the compound Poisson approximation.
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