Descrambling Order Analysis in Ciliates

Khan, Naseer Ahmed; McQuillan, Ian

doi:10.1007/978-3-319-58187-3_16

Cited by 3 publications

(1 citation statement)

References 16 publications

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“…Existing models of DNA rearrangements apply only to one-to-one, or one-to-many mappings [3, 4, 13, 12, 23], but in the context of ciliate genomics, a many-to-many correspondence between regions in rearrangement precursor and product is observed. Previous approaches to annotating ciliate genomes have been performed in species-specific ways, using custom scripts, with many complex cases left untreated, and many annotation parameters chosen arbitrarily without a precise definition of the parameters associated with the output [7, 8, 24]; these approaches complicate the reproducibilty of annotations, prevent crossspecies comparisons, and lack transparency and comprehensiveness.…”

Section: Introductionmentioning

confidence: 99%

SDRAP for annotating scrambled or rearranged genomes

Braun

Neme

Feng

et al. 2022

Preprint

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DNA rearrangements are important in various contexts, such as in vertebrate immunity, and cancer genome instability. The single-celled eukaryoteOxytricha trifallaxundergoes massive and reproducible genome rearrangement during post-zygotic development, making it a compelling model organism to study DNA rearrangements. To date, computational tools for the extraction and analysis of rearrangement annotations lack transparency and rely on assumptions that may not hold for all analyzed data, leading to irreproducibility of results and loss of information through data filtering or misrepresentation. An implementation of a procedure for the annotation and analysis of DNA rearrangement as a web application is discussed and tested. The resulting annotations provide an improvement over previous annotations in the following manner. (a) SDRAP achieves more complete precursor-product mappings than previous software (b) the software allows for full transparency of all parameters used during the annotation and therefore facilitates reproducible results, and (c) this parameter transparency makes SDRAP suitable for comparison of genomic data from different sources, including cancer genomes. This work introduces a theoretical framework and software to systematically extract and analyze annotations from pairs of genome assemblies corresponding to precursor and product rearrangement data. The software makes no assumptions about the structure of the rearrangements, and permits the user to select parameters to suit the data.

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Section: Introductionmentioning

confidence: 99%

SDRAP for annotating scrambled or rearranged genomes

Braun

Neme

Feng

et al. 2022

Preprint

View full text Add to dashboard Cite

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Descrambling Order Analysis in Ciliates

Khan

McQuillan

2017

Unconventional Computation and Natural Computation

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SDRAP for annotating scrambled or rearranged genomes

Braun,

Neme,

Feng

et al. 2023

NAR Genomics and Bioinformatics

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Genomes sometimes undergo large-scale rearrangements. Programmed genome rearrangements in ciliates offer an extreme example, making them a compelling model system to study DNA rearrangements. Currently, available methods for genome annotation are not adequate for highly scrambled genomes. We present a theoretical framework and software implementation for the systematic extraction and analysis of DNA rearrangement annotations from pairs of genome assemblies corresponding to precursor and product versions. The software makes no assumptions about the structure of the rearrangements, and permits the user to select parameters to suit the data. Compared to previous approaches, this work achieves more complete precursor-product mappings, allows for full transparency and reproducibility, and can be adapted to genomic data from different sources.

show abstract

Descrambling Order Analysis in Ciliates

Cited by 3 publications

References 16 publications

SDRAP for annotating scrambled or rearranged genomes

SDRAP for annotating scrambled or rearranged genomes

Descrambling Order Analysis in Ciliates

SDRAP for annotating scrambled or rearranged genomes

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