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Biology subjects

Sarah Lutteropp

Publications and source records attributed to Sarah Lutteropp.

2 recordsLinked to original sources

Multi-rate Poisson Tree Processes for single-locus species delimitation under Maximum Likelihood and Markov Chain Monte Carlo.

MotivationIn recent years, molecular species delimitation has become a routine approach for quantifying and classifying biodiversity. Barcoding methods are of particular importance in large-scale surveys as they promote fast species discovery and biodiversity estimates. Among those, distance-based methods are the most common choice as they scale well with large datasets; however, they are sensitive to similarity threshold parameters and they ignore evolutionary relationships. The recently introduced \"Poisson Tree Processes\" (PTP) method is a phylogeny-aware approach that does not rely on such thresholds. Yet, two weaknesses of PTP impact its accuracy and practicality when applied to large datasets; it does not account for divergent intraspecific variation and is slow for a large number of sequences.\n\nResultsWe introduce the multi-rate PTP (mPTP), an improved method that alleviates the theoretical and technical shortcomings of PTP. It incorporates different levels of intraspecific genetic diversity deriving from differences in either the evolutionary history or sampling of each species. Results on empirical data suggest that mPTP is superior to PTP and popular distance-based methods as it, consistently, yields more accurate delimitations with respect to the taxonomy (i.e., identifies more taxonomic species, infers species numbers closer to the taxonomy). Moreover, mPTP does not require any similarity threshold as input. The novel dynamic programming algorithm attains a speedup of at least five orders of magnitude compared to PTP, allowing it to delimit species in large (meta-) barcoding data. In addition, Markov Chain Monte Carlo sampling provides a comprehensive evaluation of the inferred delimitation in just a few seconds for millions of steps, independently of tree size.\n\nAvailabilitymPTP is implemented in C and is available for download at http://github.com/Pas-Kapli/mptp under the GNU Affero 3 license. A web-service is available at http://mptp.h-its.org.\n\nContactPaschalia.Kapli@h-its.org, Alexandros.Stamatakis@hits.org, Tomas.Flouri@h-its.org

Bioinformatics

Two Independent and Highly Efficient Open Source TKF91 Implementations

In the context of a master level programming practical at the computer science department of the Karlsruhe Institute of Technology, we developed and make available two independent and highly optimized open-source implementations for the pair-wise statistical alignment model, also known as TKF91, that was developed by Thorne, Kishino, and Felsenstein in 1991. This paper has two parts. In the educational part, we cover teaching issues regarding the setup of the course and the practical and summarize student and teacher experiences. In the scientific part, the two student teams (Team I: Nikolai, Sebastian, Daniel; Team II: Sarah, Pierre) present their solutions for implementing efficient and numerically stable implementations of the TKF91 algorithm. The two teams worked independently on implementing the same algorithm. Hence, since the implementations yield identical results --with slight numerical deviations-- we are confident that the implementations are correct. We describe the optimizations applied and make them available as open-source codes in the hope that our findings and software will be useful to the community as well as for similar programming practicals at other universities.

Bioinformatics