We present an EST sequence assembler that specializes in reconstruction of pristine mRNA transcripts, while at the same time detecting and classifying single nucleotide polymorphisms (SNPs) occuring in different variations thereof. The assembler uses iterative multipass strategies centered on high-confidence regions within sequences and has a fallback strategy for using low-confidence regions when needed. It features special functions to assemble high numbers of highly similar sequences without prior masking, an automatic editor that edits and analyzes alignments by inspecting the underlying traces, and detection and classification of sequence properties like SNPs with a high specificity and a sensitivity down to one mutation per sequence. In addition, it includes possibilities to use incorrectly preprocessed sequences, routines to make use of additional sequencing information such as base-error probabilities, template insert sizes, strain information, etc., and functions to detect and resolve possible misassemblies. The assembler is routinely used for such various tasks as mutation detection in different cell types, similarity analysis of transcripts between organisms, and pristine assembly of sequences from various sources for oligo design in clinical microarray experiments.On the way to understand the function of all genes of an organism, it is now clear that the genome sequence alone may be not enough, especially if the organism shows a high degree of complexity. Analysis of the genome must be supported by efforts on understanding its transcription-the transcriptome-occurring in cells. Citing Camargo et al. (2001), the "most definitive approach to the elucidation of transcripts remains their direct sequencing." This corresponds with earlier findings of Bonfield et al. (1998), who concluded that "direct sequencing is required to define the precise location and nature of any [mutation] change", as this method ensures the highest reliability and quality regarding the definition of single nucleotide polymorphisms (SNPs).Several approaches have been proposed to assemble ESTs and detect SNPs in the resulting alignments, among these are TRACE-DIFF by Bonfield et al. (1998) Barker et al. (2003). The most significant shortcoming common to all of these methods is the fact that they determine potential SNP positions from assemblies that align all available sequences together, regardless of whether they contain differing SNP positions or originate from different sources such as, for example, organisms, strains, cell types, etc. Unfortunately, the intrinsic properties of alignment algorithms can, and do lead to misassemblies, especially when the sequences involved are highly similar. This, in turn, leads to wrongly assembled transcripts, and these can cause false or nonexistent proteins to be predicted as is shown in Figure 1. As a side effect, nonexistent SNP positions are also generated.To address these problems, the method we have devised and implemented, the miraEST assembler, consists of an iterative multiple-pass...

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