Over the years, many research facilities have performed head to head comparisons against PatternHunter. While some are available online, below a comparison between PatternHunter vs BLASTn vs MegaBLAST via BL2SEQ, using the most favorable parameters for BLASTn and MegaBLAST and standard parameters for PatternHunter.

Here's how the time and memory use compare with MegaBLAST on long sequences:

The output quality is also on par with the default BLASTn and much superior to MegaBLAST; the next figure shows a typical comparison of how alignment scores fall off (from best to worst):

At the default BLASTn sensitivity, PatternHunter runs at MegaBLAST speed, using only 25% of the memory used by either program. For a genome of length N, PatternHunter requires about 8N bytes of internal memory. When given two inputs of lengths M and N, PatternHunter requires M+8N internal memory. Memory usage can be reduced with PatternHunter's automatic database partitioning feature.

The time and sensitivity of different configurations of PatternHunter with BLAST were considered. In the following figure, Smith-Waterman algorithm's sensitivity is set to be 100%. The sensitivity curves of PatternHunter and BLAST indicate how many of the homologs found by Smith-Waterman can be found by PatternHunter and BLAST, respectively. The data utilized in this comparison is approximately 30k mouse EST sequences (25Mb) and 4k human EST sequences (3Mb). According to this figure, PatternHunter with 4 seeds ran at the same speed of BLAST but with sensitivity very similar to Smith-Waterman.