Efficient match scoring with the fast Fourier transform

从历史上看，在计算生物学中，快速傅里叶变换（FFT）几乎专门用于计算两个生物序列之间精确字母匹配的数量。相比之下，本项目探索了一种FFT算法，该算法可以根据位置特定评分矩阵（PSSM）计算序列的匹配分数。该算法在序列的所有PSSM偏移量上同时找到PSSM分数，尽管像所有以前的FFT算法一样，它仍然不允许间隙。虽然该算法是在全局匹配的背景下提出的，但它可以适应局部匹配而不存在间隙。作为基准，改进pssm的FFT算法计算成对匹配分数。在计时实验中，最有效的成对评分FFT实现似乎比传统FFT实现快10到26，只有2倍的加速度归因于先前已知的

Historically, in computational biology the fast Fourier transform (FFT) has been used almost exclusively to count the number of exact letter matches between two biosequences. In contrast, this project explores an FFT algorithm that can compute the match score of a sequence against a position-specific scoring matrix (PSSM). The algorithm finds the PSSM score simultaneously over all offsets of the PSSM with the sequence, although like all previous FFT algorithms, it still disallows gaps. Although the algorithm is presented in the context of global matching, it can be adapted to local matching without gaps. As a benchmark, the PSSM-modified FFT algorithm computed pairwise match scores. In timing experiments, the most efficient FFT implementation for pairwise scoring appeared to be 10 to 26 faster than a traditional FFT implementation, with only a factor of 2 in the acceleration attributable to a previously known compression scheme. Many important algorithms for detecting biosequence similarities, e.g., gapped BLAST or PSIBLAST, have a heuristic screening phase that disallows gaps. We are currently exploring FFT algorithms in these screening contexts