Dataset Information

New metrics for comparing and assessing discrepancies between RNA 3D structures and models.

ABSTRACT: To benchmark progress made in RNA three-dimensional modeling and assess newly developed techniques, reliable and meaningful comparison metrics and associated tools are necessary. Generally, the average root-mean-square deviations (RMSDs) are quoted. However, RMSD can be misleading since errors are spread over the whole molecule and do not account for the specificity of RNA base interactions. Here, we introduce two new metrics that are particularly suitable to RNAs: the deformation index and deformation profile. The deformation index is calibrated by the interaction network fidelity, which considers base-base-stacking and base-base-pairing interactions within the target structure. The deformation profile highlights dissimilarities between structures at the nucleotide scale for both intradomain and interdomain interactions. Our results show that there is little correlation between RMSD and interaction network fidelity. The deformation profile is a tool that allows for rapid assessment of the origins of discrepancies.

SUBMITTER: Parisien M

PROVIDER: S-EPMC2743038 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

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New metrics for comparing and assessing discrepancies between RNA 3D structures and models.

Parisien Marc M Cruz José Almeida JA Westhof Eric E Major François F

RNA (New York, N.Y.) 20090826 10

To benchmark progress made in RNA three-dimensional modeling and assess newly developed techniques, reliable and meaningful comparison metrics and associated tools are necessary. Generally, the average root-mean-square deviations (RMSDs) are quoted. However, RMSD can be misleading since errors are spread over the whole molecule and do not account for the specificity of RNA base interactions. Here, we introduce two new metrics that are particularly suitable to RNAs: the deformation index and defo ...[more]

PMID: 19710185

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Project description:Delimiting and describing species is fundamental to numerous biological disciplines such as evolution, macroecology, and conservation. Delimiting species as independent evolutionary lineages may and often does yield different outcomes depending on the species criteria applied, but methods should be chosen that minimize the inference of objectively erroneous species limits. Several protocols exploit single-gene or multi-gene coalescence statistics, assignment tests or other rationales related to nuclear DNA (nDNA) allele sharing to automatically delimit species. We apply seven different species delimitation protocols to a taxonomically confusing group of Malagasy lizards (Madascincus), and compare the resulting taxonomies with two newly developed metrics: the Taxonomic index of congruence C tax which quantifies the congruence between two taxonomies, and the Relative taxonomic resolving power index R tax which quantifies the potential of an approach to capture a high number of species boundaries. The protocols differed in the total number of species proposed, between 9 and 34, and were also highly incongruent in placing species boundaries. The Generalized Mixed Yule-Coalescent approach captured the highest number of potential species boundaries but many of these were clearly contradicted by extensive nDNA admixture between sympatric mitochondrial DNA (mtDNA) haplotype lineages. Delimiting species as phenotypically diagnosable mtDNA clades failed to detect two cryptic species that are unambiguous due to a lack of nDNA gene flow despite sympatry. We also consider the high number of species boundaries and their placement by multi-gene Bayesian species delimitation as poorly reliable whereas the Bayesian assignment test approach provided a species delimitation highly congruent with integrative taxonomic practice. The present study illustrates the trade-off in taxonomy between reliability (favored by conservative approaches) and resolving power (favored by inflationist approaches). Quantifying excessive splitting is more difficult than quantifying excessive lumping, suggesting a priority for conservative taxonomies in which errors are more liable to be detected and corrected by subsequent studies.

Dataset Information

New metrics for comparing and assessing discrepancies between RNA 3D structures and models.

Publications

New metrics for comparing and assessing discrepancies between RNA 3D structures and models.

Similar Datasets

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