A Review of Recent Alignment-Free Clustering Algorithms in Expressed Sequence Tag

Abstract

Expressed sequence tags (ESTs) are short single pass sequence reads derived from cDNA libraries, they have been used for gene discovery, detection of splice variants, expression of genes and also transciptome analysis. Clustering of ESTs is a vital step before they can be processed further. Currently there are many EST clustering algorithms available. Basically they can be generalized into two broad approaches, i.e. alignment-based and alignment-free. The former approach is reliable but inefficient in terms of running time, while the latter approach is gaining popularity and currently under rapid development due to its faster speed and acceptable result. In this paper, we propose a taxonomy for sequence comparison algorithms and another taxonomy for EST clustering algorithms. In addition, we also highlight the peculiarities of recently introduced alignment-free EST clustering algorithms by focusing on their features, distance measures, advantages and disadvantages.