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arXiv · 0901.3198

On subset seeds for protein alignment

Mikhail A. Roytberg·Anna Gambin·Laurent Noé·Slawomir Lasota·Eugenia Furletova·Ewa Szczurek·Gregory Kucherov
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Abstract

We apply the concept of subset seeds proposed in [1] to similarity search in protein sequences. The main question studied is the design of efficient seed alphabets to construct seeds with optimal sensitivity/selectivity trade-offs. We propose several different design methods and use them to construct several alphabets. We then perform a comparative analysis of seeds built over those alphabets and compare them with the standard BLASTP seeding method [2], [3], as well as with the family of vector seeds proposed in [4]. While the formalism of subset seeds is less expressive (but less costly to implement) than the cumulative principle used in BLASTP and vector seeds, our seeds show a similar or even better performance than BLASTP on Bernoulli models of proteins compatible with the common BLOSUM62 matrix. Finally, we perform a large-scale benchmarking of our seeds against several main databases of protein alignments. Here again, the results show a comparable or better performance of our seeds vs. BLASTP.

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Mikhail A. Roytberg, Anna Gambin, Laurent Noé, Slawomir Lasota, Eugenia Furletova, Ewa Szczurek, Gregory Kucherov. 2009-01-21. On subset seeds for protein alignment. https://doi.org/10.1109/tcbb.2009.4

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