> Could you suggest whether we are on the right track? What is the right > approach to set a uniform sensitivity for all inputs? E-values already incorporate statistics to eliminate (normalize for) a number of factors, including query size. Getting rid of that normalization is possible, but not necessarily a good idea unless you know exactly what you're doing. E values for identical HSPs grow with the product of the sizes of the query and the target set. The rationale is that the same hit will be more and more likely to occur by random chance in a larger sample of sequence. Said HSPs will be less and less statistically interesting as the query and the target set grow. This leads to your observation that you must increase the E-value threshold to keep getting the same hits. The question you seem to be asking is "find me all of the HSPs that fit some criterion, regardless of their statistical significance." The question that BLAST is designed to answer is "find me most of the statistically significant HSPs for some particular search, and extend them to build up gapped local alignments." If you're willing to share your goal in running these searches, the list might be able to suggest alternative tools better suited to your problem. -Chris Dwan The BioTeam