dc.date.accessioned | 2020-06-05T19:12:47Z | |
dc.date.available | 2020-06-05T19:12:47Z | |
dc.date.created | 2019-06-06T13:01:52Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Grytten, Ivar Rand, Knut Dagestad Nederbragt, Alexander Johan Storvik, Geir Olve Glad, Ingrid Kristine Sandve, Geir Kjetil . Graph Peak Caller: Calling ChIP-seq peaks on graph-based reference genomes. PLoS Computational Biology. 2019, 15(2), 1-13 | |
dc.identifier.uri | http://hdl.handle.net/10852/76717 | |
dc.description.abstract | Graph-based representations are considered to be the future for reference genomes, as they allow integrated representation of the steadily increasing data on individual variation. Currently available tools allow de novo assembly of graph-based reference genomes, alignment of new read sets to the graph representation as well as certain analyses like variant calling and haplotyping. We here present a first method for calling ChIP-Seq peaks on read data aligned to a graph-based reference genome. The method is a graph generalization of the peak caller MACS2, and is implemented in an open source tool, Graph Peak Caller. By using the existing tool vg to build a pan-genome of Arabidopsis thaliana, we validate our approach by showing that Graph Peak Caller with a pan-genome reference graph can trace variants within peaks that are not part of the linear reference genome, and find peaks that in general are more motif-enriched than those found by MACS2. | |
dc.language | EN | |
dc.publisher | Public Library of Science (PLoS) | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.title | Graph Peak Caller: Calling ChIP-seq peaks on graph-based reference genomes | |
dc.type | Journal article | |
dc.creator.author | Grytten, Ivar | |
dc.creator.author | Rand, Knut Dagestad | |
dc.creator.author | Nederbragt, Alexander Johan | |
dc.creator.author | Storvik, Geir Olve | |
dc.creator.author | Glad, Ingrid Kristine | |
dc.creator.author | Sandve, Geir Kjetil | |
cristin.unitcode | 185,15,5,35 | |
cristin.unitname | Forskningsgruppen for biomedisinsk informatikk | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 2 | |
dc.identifier.cristin | 1703165 | |
dc.identifier.bibliographiccitation | info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=PLoS Computational Biology&rft.volume=15&rft.spage=1&rft.date=2019 | |
dc.identifier.jtitle | PLoS Computational Biology | |
dc.identifier.volume | 15 | |
dc.identifier.issue | 2 | |
dc.identifier.doi | https://doi.org/10.1371/journal.pcbi.1006731 | |
dc.identifier.urn | URN:NBN:no-79836 | |
dc.type.document | Tidsskriftartikkel | |
dc.type.peerreviewed | Peer reviewed | |
dc.source.issn | 1553-734X | |
dc.identifier.fulltext | Fulltext https://www.duo.uio.no/bitstream/handle/10852/76717/2/journal.pcbi.1006731.pdf | |
dc.type.version | PublishedVersion | |
cristin.articleid | e1006731 | |