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48 lines
2.1 KiB
Text
48 lines
2.1 KiB
Text
LocARNA: Alignment of RNAs
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==========================
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LocARNA is a collection of alignment tools for the structural analysis
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of RNA. Given a set of RNA sequences, LocARNA simultaneously aligns
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and predicts common structures for your RNAs. In this way, LocARNA
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performs Sankoff-like alignment and is in particular suited for
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analyzing sets of related RNAs without known common structure.
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LocARNA distinguishes itself from many other Sankoff-style multiple
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alignment programs by its performance and low memory complexity, high
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accuracy, and richness of features. As unique features, it offers
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structure-local alignment, flexible structure and anchor constraints,
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and provides efficient computation of reliabilities in
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sequence-structure alignment. The package offers a robust core of
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features and is used as experimental platform for the incorporation of
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new features in RNA sequence-structure alignment.
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At its core, the package offers global and local multiple alignment of
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RNAs.
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Multiple alignment can be performed in one of several different ways:
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* progressive alignment using sequence-structure alignment of profiles
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* progressive alignment after consistency transformation using
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T-Coffee
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* progressive alignment using probabilistic consistency transformation
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and sequence-structure profile alignments, optionally followed by
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iterative refinement.
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Besides of global alignment, LocARNA supports two kinds of
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locality. Local alignment as it is known from sequence alignment,
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identifies and aligns the best matching subsequences. This form of
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locality is called sequence local to distinguish it from structural
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locality. When performing structure local alignment, LocARNA
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identifies and aligns the best matching substructures in the RNAs. The
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sequences of those substructures can be discontinuous on the sequence
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level, but remain connected via structural bonds.
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Alignment Reliabilities (LocARNA-P). In this special, probabilistic
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mode of operation LocARNA supports the efficient computation of match
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probabilities, probabilistic consistency transformation for more
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accurate multiple alignment, and generates reliability profiles of
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multiple alignments.
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