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http://hdl.handle.net/1942/30899
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DC Field | Value | Language |
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dc.contributor.author | Everaert, Celine | - |
dc.contributor.author | Volders, Pieter-Jan | - |
dc.contributor.author | Morlion, Annelien | - |
dc.contributor.author | THAS, Olivier | - |
dc.contributor.author | Mestdagh, Pieter | - |
dc.date.accessioned | 2020-03-31T07:15:31Z | - |
dc.date.available | 2020-03-31T07:15:31Z | - |
dc.date.issued | 2020 | - |
dc.date.submitted | 2020-03-20T15:37:28Z | - |
dc.identifier.citation | BMC BIOINFORMATICS, 21 (Art N° 58) | - |
dc.identifier.issn | 1471-2105 | - |
dc.identifier.uri | http://hdl.handle.net/1942/30899 | - |
dc.description.abstract | Background To understand biology and differences among various tissues or cell types, one typically searches for molecular features that display characteristic abundance patterns. Several specificity metrics have been introduced to identify tissue-specific molecular features, but these either require an equal number of replicates per tissue or they can't handle replicates at all. Results We describe a non-parametric specificity score that is compatible with unequal sample group sizes. To demonstrate its usefulness, the specificity score was calculated on all GTEx samples, detecting known and novel tissue-specific genes. A webtool was developed to browse these results for genes or tissues of interest. An example python implementation of SPECS is available at . The precalculated SPECS results on the GTEx data are available through a user-friendly browser at . Conclusions SPECS is a non-parametric method that identifies known and novel specific-expressed genes. In addition, SPECS could be adopted for other features and applications. | - |
dc.description.sponsorship | This work has been supported by the Fund for Scientific Research Flanders (FWO), Stichting Tegen Kanker, Kom Op Tegen Kanker and Vocatio. A.M is supported by Kom op Tegen Kanker and P.V. is supported by Fund for Scientific Research Flanders (FWO). | - |
dc.language.iso | en | - |
dc.publisher | BMC | - |
dc.rights | The Author(s). 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated | - |
dc.subject.other | Specificity scoring | - |
dc.subject.other | RNA-sequencing | - |
dc.subject.other | GTEx | - |
dc.title | SPECS: a non-parametric method to identify tissue-specific molecular features for unbalanced sample groups | - |
dc.type | Journal Contribution | - |
dc.identifier.volume | 21 | - |
local.format.pages | 8 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | Everaert, C (reprint author), Univ Ghent, Dept Biomol Med, Ctr Med Genet, Ghent, Belgium.; Everaert, C (reprint author), Canc Res Inst Ghent, Ghent, Belgium. | - |
dc.description.notes | celine.everaert@ugent.be | - |
dc.description.other | Everaert, C (reprint author), Univ Ghent, Dept Biomol Med, Ctr Med Genet, Ghent, Belgium; Canc Res Inst Ghent, Ghent, Belgium. celine.everaert@ugent.be | - |
local.publisher.place | CAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
local.bibliographicCitation.artnr | 58 | - |
dc.source.type | Article | - |
dc.identifier.doi | 10.1186/s12859-020-3407-z | - |
dc.identifier.pmid | 32066370 | - |
dc.identifier.isi | WOS:000517131900002 | - |
dc.identifier.eissn | - | |
local.provider.type | wosris | - |
local.uhasselt.uhpub | yes | - |
local.uhasselt.international | no | - |
item.fullcitation | Everaert, Celine; Volders, Pieter-Jan; Morlion, Annelien; THAS, Olivier & Mestdagh, Pieter (2020) SPECS: a non-parametric method to identify tissue-specific molecular features for unbalanced sample groups. In: BMC BIOINFORMATICS, 21 (Art N° 58). | - |
item.contributor | Everaert, Celine | - |
item.contributor | Volders, Pieter-Jan | - |
item.contributor | Morlion, Annelien | - |
item.contributor | THAS, Olivier | - |
item.contributor | Mestdagh, Pieter | - |
item.validation | ecoom 2021 | - |
item.accessRights | Open Access | - |
item.fulltext | With Fulltext | - |
crisitem.journal.issn | 1471-2105 | - |
crisitem.journal.eissn | 1471-2105 | - |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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everaert.pdf | Published version | 1.64 MB | Adobe PDF | View/Open |
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