DarkHorse: a method for genome-wide prediction of horizontal gene transfer - PubMed (original) (raw)

DarkHorse: a method for genome-wide prediction of horizontal gene transfer

Sheila Podell et al. Genome Biol. 2007.

Abstract

A new approach to rapid, genome-wide identification and ranking of horizontal transfer candidate proteins is presented. The method is quantitative, reproducible, and computationally undemanding. It can be combined with genomic signature and/or phylogenetic tree-building procedures to improve accuracy and efficiency. The method is also useful for retrospective assessments of horizontal transfer prediction reliability, recognizing orthologous sequences that may have been previously overlooked or unavailable. These features are demonstrated in bacterial, archaeal, and eukaryotic examples.

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Figures

Figure 1

Figure 1

Flow diagram illustrating DarkHorse work flow, with example numbers for Escherichia coli strain K12. Parallelograms indicate data, rectangles indicate processes. Parallelograms with dashed borders indicate intermediate data, output by one step and input to the next step.

Figure 2

Figure 2

Effect of filter threshold setting on maximum number of candidate set members per query.

Figure 3

Figure 3

Effect of expanding E. coli self definition terms on LPI score distribution histograms. Filter threshold setting was 10%. (a) Self = Escherichia (b) Self = Escherichia + Shigella + Salmonella.

Figure 4

Figure 4

Effect of expanding A. thaliana self definition terms on LPI score distribution histograms. Filter threshold setting was 10%. (a) Self = Arabidopsis. (b) Self = Arabidopsis + Oryza.

Figure 5

Figure 5

LPI score distribution histogram for T. acidophilum. Filter threshold setting was zero.

Figure 6

Figure 6

LPI score distribution histogram for T. maritima. Filter threshold setting was zero.

Figure 7

Figure 7

LPI score distribution histogram for E. histolytica. Filter threshold setting was zero.

References

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