Publications
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Reinar, William Brynildsen; Tørresen, Ole K.; Nederbragt, Lex; Matschiner, Michael; Jentoft, Sissel & Jakobsen, Kjetill Sigurd
(2023).
Teleost genomic repeat landscapes in light of diversification rates and ecology.
Mobile DNA.
14(1),
p. 1–12.
doi:
10.1186/s13100-023-00302-9.
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Repetitive DNA make up a considerable fraction of most eukaryotic genomes. In fish, transposable element (TE) activity has coincided with rapid species diversification. Here, we annotated the repetitive content in 100 genome assemblies, covering the major branches of the diverse lineage of teleost fish. We investigated if TE content correlates with family level net diversification rates and found support for a weak negative correlation. Further, we demonstrated that TE proportion correlates with genome size, but not to the proportion of short tandem repeats (STRs), which implies independent evolutionary paths. Marine and freshwater fish had large differences in STR content, with the most extreme propagation detected in the genomes of codfish species and Atlantic herring. Such a high density of STRs is likely to increase the mutational load, which we propose could be counterbalanced by high fecundity as seen in codfishes and herring.
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Eliassen, June Edvarda; Bøe, Maria Vetleseter; Nederbragt, Lex; Berg, Marthe Mjøen & Gregers, Tone Fredsvik
(2022).
Motivasjon for beregningsorientert biologi og sammenhengen med matematikk R2 fra videregående opplæring.
Nordic Journal of STEM Education.
4(2),
p. 58–70.
doi:
10.5324/njsteme.v4i2.4026.
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 Programmering og modellering har i de senere år blitt innført i høyere utdanning og ble innført i skolen med fagfornyelsen fra høsten 2020. Det har skapt behov for mer kunnskap om motivasjon og læring i emner som integrerer programmering som et nytt element i ellers veletablerte fagdisipliner. Denne studien undersøkte motivasjon for beregningsorientering (programmering og modellering) ved studieprogrammet biovitenskap ved Universitetet i Oslo. Spørreundersøkelser basert på Eccles’ forventning-verdi-modell ble gjennomført ved semesterstart og -slutt i to påfølgende år, før og etter innføring av krav om matematikk R2 (R2-kravet). Motivasjonsvariabler ble validert ved faktoranalyse og undersøkelse av indre konsistens. Resultatene viste at studentene hadde lavere mestringsforventning og interesse for et emne som integrerer programmering i biologi enn for studieprogrammet generelt. Nytteverdien var den sterkeste motiverende faktoren for emnet. Studenter med matematikk R2 hadde større mestringsforventning til emnet enn de som ikke hadde denne fordypningen, og opplevde mindre utfordring med matematikk og programmering i emnet. Samtidig opplevde disse studentene større utfordring med biologien i emnet, og det viste seg at studenter med full fordypning i matematikk R2 i mindre grad enn studenter uten R2 hadde full fordypning i biologi fra videregående opplæring. Resultatene drøftes i lys av motivasjonsteori med tanke på implikasjoner for undervisning, inntakskrav og videre forskning.
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Khelik, Ksenia; Sandve, Geir Kjetil; Nederbragt, Alexander Johan & Rognes, Torbjørn
(2020).
NucBreak: location of structural errors in a genome assembly by using paired-end Illumina reads.
BMC Bioinformatics.
21(1).
doi:
10.1186/s12859-020-3414-0.
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Background
Advances in whole genome sequencing strategies have provided the opportunity for genomic and comparative genomic analysis of a vast variety of organisms. The analysis results are highly dependent on the quality of the genome assemblies used. Assessment of the assembly accuracy may significantly increase the reliability of the analysis results and is therefore of great importance. Results
Here, we present a new tool called NucBreak aimed at localizing structural errors in assemblies, including insertions, deletions, duplications, inversions, and different inter- and intra-chromosomal rearrangements. The approach taken by existing alternative tools is based on analysing reads that do not map properly to the assembly, for instance discordantly mapped reads, soft-clipped reads and singletons. NucBreak uses an entirely different and unique method to localise the errors. It is based on analysing the alignments of reads that are properly mapped to an assembly and exploit information about the alternative read alignments. It does not annotate detected errors. We have compared NucBreak with other existing assembly accuracy assessment tools, namely Pilon, REAPR, and FRCbam as well as with several structural variant detection tools, including BreakDancer, Lumpy, and Wham, by using both simulated and real datasets. Conclusions
The benchmarking results have shown that NucBreak in general predicts assembly errors of different types and sizes with relatively high sensitivity and with lower false discovery rate than the other tools. Such a balance between sensitivity and false discovery rate makes NucBreak a good alternative to the existing assembly accuracy assessment tools and SV detection tools. NucBreak is freely available at https://github.com/uio-bmi/NucBreak under the MPL license.
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Grytten, Ivar; Rand, Knut Dagestad; Nederbragt, Alexander Johan & Sandve, Geir Kjetil
(2020).
Assessing graph-based read mappers against a baseline approach highlights strengths and weaknesses of current methods.
BMC Genomics.
21.
doi:
10.1186/s12864-020-6685-y.
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Background Graph-based reference genomes have become popular as they allow read mapping and follow-up analyses in settings where the exact haplotypes underlying a high-throughput sequencing experiment are not precisely known. Two recent papers show that mapping to graph-based reference genomes can improve accuracy as compared to methods using linear references. Both of these methods index the sequences for most paths up to a certain length in the graph in order to enable direct mapping of reads containing common variants. However, the combinatorial explosion of possible paths through nearby variants also leads to a huge search space and an increased chance of false positive alignments to highly variable regions. Results We here assess three prominent graph-based read mappers against a hybrid baseline approach that combines an initial path determination with a tuned linear read mapping method. We show, using a previously proposed benchmark, that this simple approach is able to improve overall accuracy of read-mapping to graph-based reference genomes. Conclusions Our method is implemented in a tool Two-step Graph Mapper, which is available at https://github.com/uio-bmi/two_step_graph_mapperalong with data and scripts for reproducing the experiments. Our method highlights characteristics of the current generation of graph-based read mappers and shows potential for improvement for future graph-based read mappers.
View all works in NVA
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Nederbragt, Lex
(2022).
Carpentry@UiO: Workshops for basic skills in programming and datamanagement at The University of Oslo (UiO).
Full text in Research Archive
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Eliassen, June Edvarda; Bøe, Maria Vetleseter; Nederbragt, Lex & Gregers, Tone Fredsvik
(2021).
Motivasjon for beregningsorientert biologi og sammenhengen med matematikk R2 fra videregående opplæring.
Full text in Research Archive
View all works in NVA
Published
Nov. 3, 2010 3:30 PM
- Last modified
Nov. 27, 2019 3:09 PM
