Have DNA motifs 6-12bp long, trying to get conservation scores I have about 200 short nucleotide motifs (6-12 bp in length) from the human genome, and I'm trying to see how conserved they are across vertebrates. 

I was thinking that I'd need to make a bed file for each motif that lists all of its occurrences in the human genome. From there, I could map the beds to a bigwig files of PhastCons scores (essentially doing the reverse of what the PhastCons software was designed to do). Does that sound like the best approach? 

I'm getting stuck at the step of going from motifs to bed files. I've tried using BLAST to find all occurrences of motifs, but their short length is causing issues.
I've tried messing with the e-value threshold, word size, and filter parameters, but I still don't get any hits. 

Is there a work-around for this issue, or should I just rethink my entire approach?
In case you have only ACGT in your motifs

The short motifs make it sound as if you are in the business of looking for a kmer counter. You can choose to use existing software or build your own.


Using existing software might be your easiest path. An older post from 2014 will probably give you a first idea what's out there: http://homolog.us/blogs/blog/2014/04/07/kmer-counting-a-2014-recap/ . Note that a couple of algorithms mentioned there got successors, so it is worthwhile digging a bit around. The small kmer size will make most of them usable for your needs.
As the maximum size of your kmers is comparatively small (12 nt need 24 bits, i.e., max 16.7 million entries in your kmer table), you should be able to easily roll your own kmer counting in about any language you like and on about any of nowadays computer. The pseudocode section on the Wikipedia entry for kmers will give you first pointers for that. Might be a bit more work, but maybe more flexible depending on your needs.


In case you have IUPAC bases (N, W, etc.) in your motifs

I don't know any any pre-existing software doing what you need. I could imagine that the short motifs make using regular expressions doable for this kind of search, but I may be wrong. Testing this should be easy in a simple script as all major programming languages have modules or libraries for REs. Even if it should take a couple of hours to run on your data set, that would be good enough for a one-off calculation.