Abstract
BackgroundThis paper describes a new MSA tool called PnpProbs, which constructs better multiple sequence alignments by better handling of guide trees. It classifies sequences into two types: normally related and distantly related. For normally related sequences, it uses an adaptive approach to construct the guide tree needed for progressive alignment; it first estimates the input’s discrepancy by computing the standard deviation of their percent identities, and based on this estimate, it chooses the better method to construct the guide tree. For distantly related sequences, PnpProbs abandons the guide tree and uses instead some non-progressive alignment method to generate the alignment.ResultsTo evaluate PnpProbs, we have compared it with thirteen other popular MSA tools, and PnpProbs has the best alignment scores in all but one test. We have also used it for phylogenetic analysis, and found that the phylogenetic trees constructed from PnpProbs’ alignments are closest to the model trees.ConclusionsBy combining the strength of the progressive and non-progressive alignment methods, we have developed an MSA tool called PnpProbs. We have compared PnpProbs with thirteen other popular MSA tools and our results showed that our tool usually constructed the best alignments.
Highlights
This paper describes a new MSA tool called PnpProbs, which constructs better multiple sequence alignments by better handling of guide trees
PnpProbs is based on an adaptive approach we proposed in [1], in which we observed that sequences having different similarities have different characteristics and structural properties, and by using some reliable measure to estimate the similarity of the input, we may exploit the corresponding properties to help generate better alignments
In Section “Phylogenetic analysis”, we compare PnpProbs with five other MSA tools, namely GLProbs, MSAProbs, PicXAA, MUSCLE and ClustalW, and our results showed that the phylogenetic trees generated from the outputs of PnpProbs are closer to the model phylogenetic trees than those constructed from the five other MSA tools
Summary
This paper describes a new MSA tool called PnpProbs, which constructs better multiple sequence alignments by better handling of guide trees. It classifies sequences into two types: normally related and distantly related. To study the feasibility of this idea, we have modified the open source code of MSAProbs [2] and developed a new adaptive MSA tool called GLProbs. Speaking, both tools construct the alignments in the following three stages:
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