I would like to show that certain types of RBP motifs are enriched in RNA editing islands (i.e. clusters of RNA editing). However, I am unsure about how to think about sequence motifs with respect to their occurrence in other genomic features.I understand how to find the probability of a motif at a location. i.e.P(sequence is at position i) = P(A)^[A] * P(C)^[C] * P(G)^[G] * P(T)^[T]where (.) is the base pair and [.] is the number of bps. Instead what I would like to find is: P(sequence S is contained in a feature type T) = ???where feature type T is an gene, intron, editing island, etc. I think I should incorporate length since I will mainly be comparing genes or introns vs. editing islands. Also, I am not sure what to do about the editing islands being located within genes. How can I keep from counting the same motif twice?Any ideas would be greatly appreciated. Thank you for your time. 
How to calculate statistical significance of sequence motifs
statistics;motifs
As far as I remember the exact probability computation is an open problem. The reason is that potential motifs can overlap, which makes probability computations for an arbitrary string non-trivial, and depends on the motif.For example if he have a binary string of four digits, the probability of 01 will be 11/16, while the probability of 11 will be 8/16=1/2.The simplest approximation is to assume that probability of the motif on every position of the sequence is equal and independent. In such case (this comes from this course):(Probability of text of length N having at least t occurrences of a k-mer Pattern, A is the number of letters in the alphabet, n = N  t * k)This approximation is very rough, there are better here.