Unbiased taxonomic annotation of metagenomic samples

The classification of reads from a metagenomic sample using a reference taxonomy is usually based on first mapping the reads to the reference sequences and then classifying each read at a node under the lowest common ancestor of the candidate sequences in the reference taxonomy with the least classification error. However, this taxonomic annotation can be biased by an imbalanced taxonomy and also by the presence of multiple nodes in the taxonomy with the least classification error for a given read. In this article, we show that the Rand index is a better indicator of classification error than the often used area under thereceiver operating characteristic (ROC) curve andF-measure for both balanced and imbalanced reference taxonomies, and we also address the second source of bias by reducing the taxonomic annotation problem for a whole metagenomic sample to a set cover problem, for which a logarithmic approximation can be obtained in linear time and an exact solution can be obtained by integer linear programming. Experimental results with a proof-of-concept implementation of the set cover approach to taxonomic annotation in a next release of the TANGO software show that the set cover approach further reduces ambiguity in the taxonomic annotation obtained with TANGO without distorting the relative abundance profile of the metagenomic sample.Peer ReviewedPostprint (published version

LIPIcs, Volume 261, ICALP 2023, Complete Volume

LIPIcs, Volume 261, ICALP 2023, Complete Volum

Natural Environment Management and Applied Systems Analysis

This volume contains papers from the NEMASA Konan-IIASA Joint Workshop on Natural Environment Management and Applied Systems Analysis, which took place at IIASA September 6-8, 2000. The workshop was an activity of the research project "Modeling by Computational Intelligence and its Application to Natural Environment Management." The project is being supported by the Hirao Taro Foundation of the Konan University Association for Academic Research, Kobe, Japan. The management of the natural environment -- in particular, the use of advanced agricultural practices -- poses a major challenge to modern society, but perhaps applied systems analysis can help. The workshop set was about to: present new concepts and methodologies for managing the environment, and offer an open forum for the exchange of ideas among research disciplines, especially between agro-environmental and applied systems analysis research and between researchers and practitioners. The paper deal with a range of topics. The editors have arranged them into the following categories: (1) modeling methodologies, (2) data analysis, (3) land use, (4) water management, and (5) applications

Collection of abstracts of the 24th European Workshop on Computational Geometry

International audienceThe 24th European Workshop on Computational Geomety (EuroCG'08) was held at INRIA Nancy - Grand Est & LORIA on March 18-20, 2008. The present collection of abstracts contains the 63 scientific contributions as well as three invited talks presented at the workshop