Stephen Pollard's ProBlog (Posts about Perl)

Convergence-Divergence MCMC

Stephen Pollard — Thu, 28 Nov 2019 07:00:00 GMT

2015-2017

The Convergence-Divergence MCMC is a Markov chain Monte Carlo method used to fit a customized model of the expected distribution of the convergence, divergence, and distance between many different branches on a phylogenetic tree. The definition of a convergence between two branches is when there are two substitutions at the same site on the two branches to the same amino acid. For example, a substitution on branch #403 at site 14 from Alanine to Glutamine and a substitution on branch #586 at site 14 from Methionine to Glutamine would be a single convergence event between branches #403 and #586. If either of the substitutions above were to an amino acid other than Glutamine, the event would count as a divergence. The distance between the branches on a phylogenetic tree is calculated from the top (ancestor) of one branch, back in time to the most recent common ancestor, and down the top (ancestor) of the other branch.

Perl Modules

Stephen Pollard — Thu, 28 Nov 2019 07:00:00 GMT

2012-2019

A collection of Perl modules for phylogenetic analysis and statistical inference.

Repository: https://publichg.stephentpollard.com/PerlModules

Acceptability Model

Stephen Pollard — Mon, 04 Nov 2019 07:00:00 GMT

2017 - 2019

The goal of the Acceptability model project was to propose a new model of protein evolution based on the assumption that the propensity for each amino acid at a site changes over time. Most previous models either required the amino acid propensities to be unchanging with time or to only change at specific points on the tree. Although it is much more difficult to design and test a model that changes continuously, that was precisely the goal of this project.

PLEX

Stephen Pollard — Mon, 04 Nov 2019 07:00:00 GMT

2013 - 2018

The goal of the Phylogenetics, Likelihood, Evolution and compleXity (PLEX) project is to develop a platform for testing complex models of evolution against large amounts of DNA sequence data. The goal is to make possible fitting to data more realistic models of evolution that were previously computationally impossible to test. This is achieved by using an advanced statistical technique known as Uniformization, which allows avoiding previously computationally expensive methods such as Spectral Decomposition of the evolutionary rate matrix. PLEX compares models in a Bayesian framework using Markov chain Monte Carlo (MCMC) anaylsis.

P-clouds

Stephen Pollard — Fri, 16 Aug 2019 06:00:00 GMT

2013 - 2016

P-clouds is a methodology for identifying transposable elements in genomes and for estimating the false positive and false negative rates of identification. While using this program, I found a number of critical bugs in the software that lead incorrect results. I tracked down these errors and fixed them as they were found. I then created a number of new methods for identification using similar ideas from P-clouds and tested their efficacy against older methods.

Associated publication:

Gu, Wanjun, et al. "Identification of repeat structure in large genomes using repeat probability clouds." Analytical biochemistry 380.1 (2008): 77-83.

Tools: C, Perl, R, Git

Repository: https://github.com/PollockLaboratory/pclouds