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The diversity of sequence alignment and tree space at high parameter density

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Title: The diversity of sequence alignment and tree space at high parameter density
Authors: Borrow, Christopher Andrew
Item Type: Thesis or dissertation
Abstract: When attempting to characterise communities by their phylogenetic diversity, Scarabaeinae provide an ideal model system. Historically three genes, cox1, 28S and 16S, have been widely used in phylogenetic studies for members of the Coleoptera and this is also the case for the Scarabaeinae. Two of these genes, 28S and 16S, are length variable. The alignment of nucleotide sequence data containing multiple insertion and deletion events is a notoriously difficult problem to resolve. Accurately doing so is important, as the accuracy of the alignment is thought to play a crucial role in determining phylogenetic tree topology. Therefore it is necessary to find a way to accurately align the sequence data before communities can be accurately characterised across a hypothesised phylogenetic tree. Little guidance is available on how the users of alignment programs should go about this task. In the following chapters an understanding of how alignment parameters act on the alignment of 16S data from Coleoptera species is reported along with a method for using members of the Clustal program family. The use of two scoring systems for judging the quality of alignments is also explored. Selecting alignments based on minimising overall alignment diversity appears to minimise synapomorphy and homoplasy, while maximising taxonomic consistency. Therefore, using the Shannon- Wiener or Simpsons Index of diversity to score alignment quality may prove useful to phylogeneticists.
Issue Date: Jul-2011
Date Awarded: Sep-2012
URI: http://hdl.handle.net/10044/1/10170
DOI: https://doi.org/10.25560/10170
Supervisor: Krell, F
Vogler, Alfried
Department: Biology
Publisher: Imperial College London
Qualification Level: Doctoral
Qualification Name: Doctor of Philosophy (PhD)
Appears in Collections:Biology PhD theses



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