Ontology type: schema:ScholarlyArticle
2019-12
AUTHORSZhijian Li, Marcel H. Schulz, Thomas Look, Matthias Begemann, Martin Zenke, Ivan G. Costa
ABSTRACTTransposase-Accessible Chromatin followed by sequencing (ATAC-seq) is a simple protocol for detection of open chromatin. Computational footprinting, the search for regions with depletion of cleavage events due to transcription factor binding, is poorly understood for ATAC-seq. We propose the first footprinting method considering ATAC-seq protocol artifacts. HINT-ATAC uses a position dependency model to learn the cleavage preferences of the transposase. We observe strand-specific cleavage patterns around transcription factor binding sites, which are determined by local nucleosome architecture. By incorporating all these biases, HINT-ATAC is able to significantly outperform competing methods in the prediction of transcription factor binding sites with footprints. More... »
PAGES45
http://scigraph.springernature.com/pub.10.1186/s13059-019-1642-2
DOIhttp://dx.doi.org/10.1186/s13059-019-1642-2
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1112388860
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/30808370
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Genetics",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Biological Sciences",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Animals",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "DNA Footprinting",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Dendritic Cells",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Genomics",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Humans",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "K562 Cells",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Mice",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Models, Genetic",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Nucleosomes",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Sequence Analysis, DNA",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Transcription Factors",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Transposases",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "RWTH Aachen University",
"id": "https://www.grid.ac/institutes/grid.1957.a",
"name": [
"Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical School, 52074, Aachen, Germany",
"Department of Cell Biology, Institute of Biomedical Engineering, RWTH Aachen University Medical School, 52074, Aachen, Germany"
],
"type": "Organization"
},
"familyName": "Li",
"givenName": "Zhijian",
"type": "Person"
},
{
"affiliation": {
"alternateName": "German Centre for Cardiovascular Research",
"id": "https://www.grid.ac/institutes/grid.452396.f",
"name": [
"Cluster of Excellence for Multimodal Computing and Interaction, Saarland Informatics Campus, Saarland University, Saarbr\u00fccken, Germany",
"Computational Biology & Applied Algorithmics, Max Planck Institute for Informatics, Saarbr\u00fccken, Germany",
"Institute for Cardiovascular Regeneration, Goethe University, Frankfurt am Main, Germany",
"German Centre for Cardiovascular Research (DZHK), Partner site RheinMain, Frankfurt am Main, Germany"
],
"type": "Organization"
},
"familyName": "Schulz",
"givenName": "Marcel H.",
"type": "Person"
},
{
"affiliation": {
"alternateName": "RWTH Aachen University",
"id": "https://www.grid.ac/institutes/grid.1957.a",
"name": [
"Department of Cell Biology, Institute of Biomedical Engineering, RWTH Aachen University Medical School, 52074, Aachen, Germany",
"Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany"
],
"type": "Organization"
},
"familyName": "Look",
"givenName": "Thomas",
"type": "Person"
},
{
"affiliation": {
"alternateName": "RWTH Aachen University",
"id": "https://www.grid.ac/institutes/grid.1957.a",
"name": [
"Institute of Human Genetics, RWTH Aachen University Medical School, Aachen, Germany"
],
"type": "Organization"
},
"familyName": "Begemann",
"givenName": "Matthias",
"type": "Person"
},
{
"affiliation": {
"alternateName": "RWTH Aachen University",
"id": "https://www.grid.ac/institutes/grid.1957.a",
"name": [
"Department of Cell Biology, Institute of Biomedical Engineering, RWTH Aachen University Medical School, 52074, Aachen, Germany",
"Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany"
],
"type": "Organization"
},
"familyName": "Zenke",
"givenName": "Martin",
"type": "Person"
},
{
"affiliation": {
"alternateName": "RWTH Aachen University",
"id": "https://www.grid.ac/institutes/grid.1957.a",
"name": [
"Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University Medical School, 52074, Aachen, Germany",
"Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany"
],
"type": "Organization"
},
"familyName": "Costa",
"givenName": "Ivan G.",
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1016/j.cell.2007.12.014",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000099864"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkv577",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1001398557"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1073/pnas.1216822110",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1002242079"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nature11232",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003040774",
"https://doi.org/10.1038/nature11232"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.1906",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003714959",
"https://doi.org/10.1038/nmeth.1906"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ncomms11938",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004333915",
"https://doi.org/10.1038/ncomms11938"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nbt.2798",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1005420455",
"https://doi.org/10.1038/nbt.2798"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.1923",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1006541515",
"https://doi.org/10.1038/nmeth.1923"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btp554",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1006715941"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.3768",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1007594424",
"https://doi.org/10.1038/nmeth.3768"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pone.0118432",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012273932"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.3542",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012712425",
"https://doi.org/10.1038/nmeth.3542"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ng.3646",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014039410",
"https://doi.org/10.1038/ng.3646"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/gr.4074106",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014714441"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s13059-014-0550-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1015222646",
"https://doi.org/10.1186/s13059-014-0550-8"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s13059-014-0550-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1015222646",
"https://doi.org/10.1186/s13059-014-0550-8"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/gr.112656.110",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1015402344"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.3772",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1015743890",
"https://doi.org/10.1038/nmeth.3772"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1371/journal.pone.0138030",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1017329805"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.2688",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020615304",
"https://doi.org/10.1038/nmeth.2688"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.2688",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020615304",
"https://doi.org/10.1038/nmeth.2688"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s13059-016-0882-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021720128",
"https://doi.org/10.1186/s13059-016-0882-7"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gku810",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022151402"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btp352",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1023014918"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nbt.3121",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1024452826",
"https://doi.org/10.1038/nbt.3121"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.cell.2011.11.013",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1026652255"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/gb-2008-9-9-r137",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027608848",
"https://doi.org/10.1186/gb-2008-9-9-r137"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nature11247",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029065430",
"https://doi.org/10.1038/nature11247"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btr614",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030955572"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkj143",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1031585631"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2105-10-82",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1032493578",
"https://doi.org/10.1186/1471-2105-10-82"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.2762",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1033430428",
"https://doi.org/10.1038/nmeth.2762"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkt997",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036657357"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nature11212",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1039250372",
"https://doi.org/10.1038/nature11212"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/bti410",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1041637304"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1101/gr.183848.114",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1041784702"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.cell.2012.04.040",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1042988592"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btu519",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1046132333"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1145/1143844.1143874",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1046546824"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth888",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1050155075",
"https://doi.org/10.1038/nmeth888"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth888",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1050155075",
"https://doi.org/10.1038/nmeth888"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkw1061",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1051032920"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1073/pnas.0400678101",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1051122245"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nature14590",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1051474676",
"https://doi.org/10.1038/nature14590"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1126/science.1256271",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1052527424"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkq992",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1052742245"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btw740",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1059415104"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/5.18626",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061178979"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tpami.2008.71",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061743667"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12859-017-1766-x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1090941218",
"https://doi.org/10.1186/s12859-017-1766-x"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12859-017-1766-x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1090941218",
"https://doi.org/10.1186/s12859-017-1766-x"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.4396",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1091372842",
"https://doi.org/10.1038/nmeth.4396"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nmeth.4396",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1091372842",
"https://doi.org/10.1038/nmeth.4396"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkx1053",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1092299685"
],
"type": "CreativeWork"
}
],
"datePublished": "2019-12",
"datePublishedReg": "2019-12-01",
"description": "Transposase-Accessible Chromatin followed by sequencing (ATAC-seq) is a simple protocol for detection of open chromatin. Computational footprinting, the search for regions with depletion of cleavage events due to transcription factor binding, is poorly understood for ATAC-seq. We propose the first footprinting method considering ATAC-seq protocol artifacts. HINT-ATAC uses a position dependency model to learn the cleavage preferences of the transposase. We observe strand-specific cleavage patterns around transcription factor binding sites, which are determined by local nucleosome architecture. By incorporating all these biases, HINT-ATAC is able to significantly outperform competing methods in the prediction of transcription factor binding sites with footprints.",
"genre": "research_article",
"id": "sg:pub.10.1186/s13059-019-1642-2",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": [
{
"id": "sg:journal.1023439",
"issn": [
"1474-760X",
"1465-6906"
],
"name": "Genome Biology",
"type": "Periodical"
},
{
"issueNumber": "1",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "20"
}
],
"name": "Identification of transcription factor binding sites using ATAC-seq",
"pagination": "45",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"1b56e648155322142f5f0c4c06ab827c96d62b5fbe2364d8110cd2608179b932"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"30808370"
]
},
{
"name": "nlm_unique_id",
"type": "PropertyValue",
"value": [
"100960660"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1186/s13059-019-1642-2"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1112388860"
]
}
],
"sameAs": [
"https://doi.org/10.1186/s13059-019-1642-2",
"https://app.dimensions.ai/details/publication/pub.1112388860"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T12:53",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000364_0000000364/records_72839_00000001.jsonl",
"type": "ScholarlyArticle",
"url": "https://link.springer.com/10.1186%2Fs13059-019-1642-2"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s13059-019-1642-2'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13059-019-1642-2'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13059-019-1642-2'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13059-019-1642-2'
This table displays all metadata directly associated to this object as RDF triples.
324 TRIPLES
21 PREDICATES
90 URIs
33 LITERALS
21 BLANK NODES