4,679 research outputs found
Gene set bagging for estimating replicability of gene set analyses
Background: Significance analysis plays a major role in identifying and
ranking genes, transcription factor binding sites, DNA methylation regions, and
other high-throughput features for association with disease. We propose a new
approach, called gene set bagging, for measuring the stability of ranking
procedures using predefined gene sets. Gene set bagging involves resampling the
original high-throughput data, performing gene-set analysis on the resampled
data, and confirming that biological categories replicate. This procedure can
be thought of as bootstrapping gene-set analysis and can be used to determine
which are the most reproducible gene sets. Results: Here we apply this approach
to two common genomics applications: gene expression and DNA methylation. Even
with state-of-the-art statistical ranking procedures, significant categories in
a gene set enrichment analysis may be unstable when subjected to resampling.
Conclusions: We demonstrate that gene lists are not necessarily stable, and
therefore additional steps like gene set bagging can improve biological
inference of gene set analysis.Comment: 3 Figure
Towards a Taxonomically Intelligent Phylogenetic Database
This note outlines some of the key intellectual obstacles that stand in the way of creating a usable phylogenetic database. These challenges include the need to accommodate multiple taxonomic names and classifications, and the need for tools to query trees in biologically meaningful ways. Until these problems are addressed, and a taxonomically intelligent phylogenetic database created, much of our phylogenetic knowledge will languish in the pages of journals
Accurate Reconstruction of Molecular Phylogenies for Proteins Using Codon and Amino Acid Unified Sequence Alignments (CAUSA)
Based on molecular clock hypothesis, and neutral theory of molecular evolution, molecular phylogenies have been widely used for inferring evolutionary history of organisms and individual genes. Traditionally, alignments and phylogeny trees of proteins and their coding DNA sequences are constructed separately, thus often different conclusions were drawn. Here we present a new strategy for sequence alignment and phylogenetic tree reconstruction, codon and amino acid unified sequence alignment (CAUSA), which aligns DNA and protein sequences and draw phylogenetic trees in a unified manner. We demonstrated that CAUSA improves both the accuracy of multiple sequence alignments and phylogenetic trees by solving a variety of molecular evolutionary problems in virus, bacteria and mammals. Our results support the hypothesis that the molecular clock for proteins has two pointers existing separately in DNA and protein sequences. It is more accurate to read the molecular clock by combination (additive) of these two pointers, since the ticking rates of them are sometimes consistent, sometimes different. CAUSA software were released as Open Source under GNU/GPL license, and are downloadable free of charge from the website www.dnapluspro.com
Evolutionary Inference via the Poisson Indel Process
We address the problem of the joint statistical inference of phylogenetic
trees and multiple sequence alignments from unaligned molecular sequences. This
problem is generally formulated in terms of string-valued evolutionary
processes along the branches of a phylogenetic tree. The classical evolutionary
process, the TKF91 model, is a continuous-time Markov chain model comprised of
insertion, deletion and substitution events. Unfortunately this model gives
rise to an intractable computational problem---the computation of the marginal
likelihood under the TKF91 model is exponential in the number of taxa. In this
work, we present a new stochastic process, the Poisson Indel Process (PIP), in
which the complexity of this computation is reduced to linear. The new model is
closely related to the TKF91 model, differing only in its treatment of
insertions, but the new model has a global characterization as a Poisson
process on the phylogeny. Standard results for Poisson processes allow key
computations to be decoupled, which yields the favorable computational profile
of inference under the PIP model. We present illustrative experiments in which
Bayesian inference under the PIP model is compared to separate inference of
phylogenies and alignments.Comment: 33 pages, 6 figure
Effects of memory on the shapes of simple outbreak trees
Genomic tools, including phylogenetic trees derived from sequence data, are increasingly used to understand outbreaks of infectious diseases. One challenge is to link phylogenetic trees to patterns of transmission. Particularly in bacteria that cause chronic infections, this inference is affected by variable infectious periods and infectivity over time. It is known that non-exponential infectious periods can have substantial effects on pathogens’ transmission dynamics. Here we ask how this non-Markovian nature of an outbreak process affects the branching trees describing that process, with particular focus on tree shapes. We simulate Crump-Mode-Jagers branching processes and compare different patterns of infectivity over time. We find that memory (non-Markovian-ness) in the process can have a pronounced effect on the shapes of the outbreak’s branching pattern. However, memory also has a pronounced effect on the sizes of the trees, even when the duration of the simulation is fixed. When the sizes of the trees are constrained to a constant value, memory in our processes has little direct effect on tree shapes, but can bias inference of the birth rate from trees. We compare simulated branching trees to phylogenetic trees from an outbreak of tuberculosis in Canada, and discuss the relevance of memory to this dataset
Geographic range size and evolutionary age in birds
Together with patterns of speciation and extinction, post-speciation transformations in the range sizes of individual species determine the form of contemporary species-range-size distributions. However, the methodological problems associated with tracking the dynamics of a species' range size over evolutionary time have precluded direct study of such range-size transformations, although indirect evidence has led to several models being proposed describing the form that they might take. Here, we use independently derived molecular data to estimate ages of species in six monophyletic groups of birds, and examine the relationship between species age and global geographic range size. We present strong evidence that avian range sizes are not static over evolutionary time. In addition, it seems that, with the regular exception of certain taxa (for example island endemics and some threatened species), range-size transformations are non-random in birds. In general, range sizes appear to expand relatively rapidly post speciation; subsequently, and perhaps more gradually, they then decline as species age. We discuss these results with reference to the various models of range-size dynamics that have been proposed
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