Improved methods for phylogenetics

textPhylogenetics is the study of evolutionary relationships. It is a scientific endeavour to discover history, and it is not easy. Massive amounts of data together with computationally difficult optimization problems mean that heuristics are prevalent, and ever better techniques are sought. New approaches are valuable if they are more accurate, but are considered even more so if they are faster than pre-existing methods. Improvements to existing algorithms, whether in terms of space requirements, or faster running times, are also worthwhile. This dissertation explores three new techniques, each of which is valuable according to the previous definitions. The first contribution is TASPI, a system for storing collections of phylogenetic trees, and performing post-tree analyses. TASPI stores collections of trees more compactly than the previous method, and this compact structure lends itself to post-tree analyses. This results in the ability to compute strict and majority consensus trees faster than common alternatives. As an added benefit, TASPI is written in ACL2, which allows properties of the algorithms and data structures to be formally verified. The second contribution is an improved method to generate phylogenetic trees. A common methodology involves two steps, first estimating a Multiple Sequence Alignment (MSA), and then estimating a tree using that MSA. This method changes the way in which the MSA is estimated, and this leads to improved accuracy of the resultant trees. Also, in some cases, the time required is also reduced. The third contribution is BLuTGEN, a method by which a phylogenetic tree is estimated from sequence data, but without ever generating an MSA for the full dataset. BLuTGEN is as accurate as one of the best published tree estimation techniques (SATé), but takes a novel approach which allows it to be applied to much larger datasets.Computer Science

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

Ketamine for the treatment of depression in patients receiving hospice care: a retrospective medical record review of thirty-one cases.

BACKGROUND: Depression is prevalent in patients receiving hospice care. Standard antidepressant medications do not work rapidly enough in this setting. Evidence suggests that ketamine rapidly treats treatment refractory depression in the general population. Ketamine׳s role for treating depression in the hospice population warrants further study. METHODS: A retrospective medical record review of 31 inpatients receiving hospice care who received ketamine for depression on a clinical basis was conducted. The primary outcome measure was the Clinical Global Impression Scale, which was used retrospectively to rate subjects׳ therapeutic improvement, global improvement, and side effects from ketamine over 21 days. Additionally, time to onset of therapeutic effect was analyzed. RESULTS: Using the Clinical Global Impression Scale, ketamine was found to be significantly therapeutically effective through the first week after ketamine dosing (p \u3c 0.05), with 93% of patients showing positive results for days 0-3 and 80% for days 4-7 following ketamine dosing. Patients experienced global improvement during all 4 studied time periods following ketamine dosing (p \u3c 0.05). Significantly more patients had either no side effects or side effects that did not significantly impair functioning at each of the 4 assessed time periods following ketamine dosing (p \u3c 0.05). Additionally, significantly more patients experienced their first therapeutic response during days 0-1 following ketamine dosing (p \u3c 0.001) than during any other time period. CONCLUSIONS: These data suggest that ketamine may be a safe, effective, and rapid treatment for clinical depression in patients receiving hospice care. Blinded, randomized, and controlled trials are required to substantiate these findings and support further clinical use of this medication in hospice settings

Accurate reconstruction of insertion-deletion histories by statistical phylogenetics

The Multiple Sequence Alignment (MSA) is a computational abstraction that represents a partial summary either of indel history, or of structural similarity. Taking the former view (indel history), it is possible to use formal automata theory to generalize the phylogenetic likelihood framework for finite substitution models (Dayhoff's probability matrices and Felsenstein's pruning algorithm) to arbitrary-length sequences. In this paper, we report results of a simulation-based benchmark of several methods for reconstruction of indel history. The methods tested include a relatively new algorithm for statistical marginalization of MSAs that sums over a stochastically-sampled ensemble of the most probable evolutionary histories. For mammalian evolutionary parameters on several different trees, the single most likely history sampled by our algorithm appears less biased than histories reconstructed by other MSA methods. The algorithm can also be used for alignment-free inference, where the MSA is explicitly summed out of the analysis. As an illustration of our method, we discuss reconstruction of the evolutionary histories of human protein-coding genes.Comment: 28 pages, 15 figures. arXiv admin note: text overlap with arXiv:1103.434

Development and Evaluation of a Palliative Medicine Curriculum for Third-Year Medical Students

Abstract Objective: To assess the impact, retention, and magnitude of effect of a required didactic and experiential palliative care curriculum on third-year medical students' knowledge, confidence, and concerns about end-of-life care, over time and in comparison to benchmark data from a national study of internal medicine residents and faculty. Design: Prospective study of third-year medical students prior to and immediately after course completion, with a follow-up assessment in the fourth year, and in comparison to benchmark data from a large national study. Setting: Internal Medicine Clerkship in a public accredited medical school. Participants: Five hundred ninety-three third-year medical students, from July 2002 to December 2007. Main outcome measures: Pre- and postinstruction performance on: knowledge, confidence (self-assessed competence), and concerns (attitudes) about end-of-life care measures, validated in a national study of internal medicine residents and faculty. Medical student's reflective written comments were qualitatively assessed. Intervention: Required 32-hour didactic and experiential curriculum, including home hospice visits and inpatient hospice care, with content drawn from the AMA-sponsored Education for Physicians on End-of-life Care (EPEC) Project. Results: Analysis of 487 paired t tests shows significant improvements, with 23% improvement in knowledge (F1,486=881, p<0.001), 56% improvement in self-reported competence (F1,486=2,804, p<0.001), and 29% decrease in self-reported concern (F1,486=208, p<0.001). Retesting medical students in the fourth year showed a further 5% increase in confidence (p<0.0002), 13% increase in allaying concerns (p<0.0001), but a 6% drop in knowledge. The curriculum's effect size on M3 students' knowledge (0.56) exceeded that of a national cross-sectional study comparing residents at progressive training levels (0.18) Themes identified in students' reflective comments included perceived relevance, humanism, and effectiveness of methods used to teach and assess palliative care education. Conclusions: We conclude that required structured didactic and experiential palliative care during the clinical clerkship year of medical student education shows significant and largely sustained effects indicating students are better prepared than a national sample of residents and attending physicians.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98455/1/jpm%2E2010%2E0502.pd

PASTA: Ultra-Large Multiple Sequence Alignment

In this paper, we introduce a new and highly scalable algorithm, PASTA, for large-scale multiple sequence alignment estimation. PASTA uses a new technique to produce an alignment given a guide tree that enables it to be both highly scalable and very accurate. We present a study on biological and simulated data with up to 200,000 sequences, showing that PASTA produces highly accurate alignments, improving on the accuracy of the leading alignment methods on large datasets, and is able to analyze much larger datasets than the current methods. We also show that trees estimated on PASTA alignments are highly accurate – slightly better than SATe ́ trees, but with substantial improvements rela-tive to other methods. Finally, PASTA is very fast, highly parallelizable, and requires relatively little memory

AST: An Automated Sequence-Sampling Method for Improving the Taxonomic Diversity of Gene Phylogenetic Trees

A challenge in phylogenetic inference of gene trees is how to properly sample a large pool of homologous sequences to derive a good representative subset of sequences. Such a need arises in various applications, e.g. when (1) accuracy-oriented phylogenetic reconstruction methods may not be able to deal with a large pool of sequences due to their high demand in computing resources; (2) applications analyzing a collection of gene trees may prefer to use trees with fewer operational taxonomic units (OTUs), for instance for the detection of horizontal gene transfer events by identifying phylogenetic conflicts; and (3) the pool of available sequences is biased towards extensively studied species. In the past, the creation of subsamples often relied on manual selection. Here we present an Automated sequence-Sampling method for improving the Taxonomic diversity of gene phylogenetic trees, AST, to obtain representative sequences that maximize the taxonomic diversity of the sampled sequences. To demonstrate the effectiveness of AST, we have tested it to solve four problems, namely, inference of the evolutionary histories of the small ribosomal subunit protein S5 of E. coli, 16 S ribosomal RNAs and glycosyl-transferase gene family 8, and a study of ancient horizontal gene transfers from bacteria to plants. Our results show that the resolution of our computational results is almost as good as that of manual inference by domain experts, hence making the tool generally useful to phylogenetic studies by non-phylogeny specialists. The program is available at http://csbl.bmb.uga.edu/~zhouchan/AST.php