The whole alignment and nothing but the alignment: the problem of spurious alignment flanks
By Martin C. Frith, Yonil Park, Sergey Sheetlin, J. Spouge. 2008
26 citations recorded by the source corpus.
Pairwise sequence alignment is a ubiquitous tool for inferring the evolution and function of DNA, RNA and protein sequences. It is therefore essential to identify alignments arising by chance alone, i.e. spurious alignments. On one hand, if an entire alignment is spurious, statistical techniques for identifying and eliminating it are well known. On the other hand, if only a part of the alignment is spurious, elimination is much more problematic. In practice, even the sizes and frequencies of spurious subalignments remain unknown. This article shows that some common scoring schemes tend to overextend alignments and generate spurious alignment flanks up to hundreds of base pairs/amino acids in length. In the UCSC genome database, e.g. spurious flanks probably comprise >18% of the human–fugu genome alignment. To evaluate the possibility that chance alone generated a particular flank on a particular pairwise alignment, we provide a simple ‘overalignment’ P-value. The overalignment P-value can identify spurious alignment flanks, thereby eliminating potentially misleading inferences about evolution and function. Moreover, by explicitly demonstrating the tradeoff between over- and under-alignment, our methods guide the rational choice of scoring schemes for various alignment tasks.
Subfields: Molecular Biology
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In Molecular Biology
- Johannes Söding
- Martin Steinegger
- Michael Remmert
- Travis J. Wheeler
- Robert D. Finn
- David T. Jones
- Sean R. Eddy
- Jody Clements
Citations in the corpus
- MMseqs2: sensitive protein sequence searching for the analysis of massive data sets (2017, background): “to reduce homologous overextension of alignments [9] (online methods).”
- Protein sequence comparison and fold recognition: progress and good-practice benchmarking. (2011, methodology): “In [40], a statistical framework is developed to calculate P-values for the alignment ends and to remove overaligned ends.”
- The Dfam database of repetitive DNA families (2015, background): “Low relative entropy substitution matrices have been shown to permit high levels of overextension (24,25), and low relative entropy has a similar impact in the context of profile hidden Markov model alignment (Rivas & Eddy, submitted).”