RNA Secondary Structure Visualization using Tree Edit Distance

Eliáš, Richard; Hoksza, David

doi:10.17706/ijbbb.2016.6.1.9-17

“…In this work, we developed several metrics that operate on the topology of lineages and applied them to the analysis of the C. elegans embryonic cell lineage. The first of these is the tree edit distance 15 , which has previously been applied to the comparison of neuron morphology 16 and RNA secondary structure 17 . The tree edit distance allows one to quantify the topological changes in lineage between different embryos, different sublineages, or different experimental conditions.…”

mentioning

confidence: 99%

Novel metrics reveal new structure and unappreciated heterogeneity in C. elegans development

Natesan,

Hamilton,

Deeds

et al. 2023

Preprint

View full text Add to dashboard Cite

High throughput experimental approaches are increasingly allowing for the quantitative description of cellular and organismal phenotypes. Distilling these large volumes of complex data into meaningful measures that can drive biological insight remains a central challenge. In the quantitative study of development, for instance, one can resolve phenotypic measures for single cells onto their lineage history, enabling joint consideration of heritable signals and cell fate decisions. Most attempts to analyze this type of data, however, discard much of the information content contained within lineage trees. In this work we introduce a generalized metric, which we term the branch edit distance, that allows us to compare any two embryos based on phenotypic measurements in individual cells. This approach aligns those phenotypic measurements to the underlying lineage tree, providing a flexible and intuitive framework for quantitative comparisons between, for instance, Wild-Type (WT) and mutant developmental programs. We apply this novel metric to data on cell-cycle timing from over 1300 WT and RNAi-treated Caenorhabditis elegans embryos. Our new metric revealed surprising heterogeneity within this data set, including subtle batch effects in WT embryos and dramatic variability in RNAi-induced developmental phenotypes, all of which had been missed in previous analyses. Further investigation of these results suggests a novel, quantitative link between pathways that govern cell fate decisions and pathways that pattern cell cycle timing in the early embryo. Our work demonstrates that the branch edit distance we propose, and similar metrics like it, have the potential to revolutionize our quantitative understanding of organismal phenotype.

show abstract

Tree Isomorphism

Valiente

¹

2021

Texts in Computer Science

0

View full text Add to dashboard Cite

Novel metrics reveal new structure and unappreciated heterogeneity in Caenorhabditis elegans development

Natesan,

Hamilton,

Deeds

et al. 2023

PLoS Comput Biol

6

0

View full text Add to dashboard Cite

High throughput experimental approaches are increasingly allowing for the quantitative description of cellular and organismal phenotypes. Distilling these large volumes of complex data into meaningful measures that can drive biological insight remains a central challenge. In the quantitative study of development, for instance, one can resolve phenotypic measures for single cells onto their lineage history, enabling joint consideration of heritable signals and cell fate decisions. Most attempts to analyze this type of data, however, discard much of the information content contained within lineage trees. In this work we introduce a generalized metric, which we term the branch edit distance, that allows us to compare any two embryos based on phenotypic measurements in individual cells. This approach aligns those phenotypic measurements to the underlying lineage tree, providing a flexible and intuitive framework for quantitative comparisons between, for instance, Wild-Type (WT) and mutant developmental programs. We apply this novel metric to data on cell-cycle timing from over 1300 WT and RNAi-treated Caenorhabditis elegans embryos. Our new metric revealed surprising heterogeneity within this data set, including subtle batch effects in WT embryos and dramatic variability in RNAi-induced developmental phenotypes, all of which had been missed in previous analyses. Further investigation of these results suggests a novel, quantitative link between pathways that govern cell fate decisions and pathways that pattern cell cycle timing in the early embryo. Our work demonstrates that the branch edit distance we propose, and similar metrics like it, have the potential to revolutionize our quantitative understanding of organismal phenotype.

show abstract

RNA Secondary Structure Visualization using Tree Edit Distance

Cited by 3 publications

References 20 publications

Novel metrics reveal new structure and unappreciated heterogeneity in C. elegans development

Novel metrics reveal new structure and unappreciated heterogeneity in C. elegans development

Tree Isomorphism

Novel metrics reveal new structure and unappreciated heterogeneity in Caenorhabditis elegans development

Contact Info

Product

Resources

About