11 months ago by

University of Manchester, UK

The following text is from UCSC's page on PhastCons / PhyloP (LINK). I think for the size of splice-sites that the fine grained PhyloP score might be most useful.

"PhastCons is a hidden Markov model-based method that estimates the
probability that each nucleotide belongs to a conserved element, based
on the multiple alignment. It considers not just each individual
alignment column, but also its flanking columns. By contrast, phyloP
separately measures conservation at individual columns, ignoring the
effects of their neighbors. As a consequence, the phyloP plots have a
less smooth appearance than the phastCons plots, with more "texture"
at individual sites. The two methods have different strengths and
weaknesses. PhastCons is sensitive to "runs" of conserved sites, and
is therefore effective for picking out conserved elements. PhyloP, on
the other hand, is more appropriate for evaluating signatures of
selection at particular nucleotides or classes of nucleotides (e.g.,
third codon positions, or first positions of miRNA target sites)."

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link
written
11 months ago by
Ian ♦ **5.6k**
I used phyloP scores to build a 'risk score' algorithm in the past, purely because the scores are intuitive and measured as negative log10 p-values (I believe), with positive meaning more conserved and negative meaning less conserved. I used the scores as priors in a Bayesian regression model for the variants of interest, with the mean prior being the mean phyloP score for all bases across the genome. This had the effect of 'adjusting' the derived p-values and odds ratios from the model.

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