000303376 001__ 303376
000303376 005__ 20250807114414.0
000303376 0247_ $$2doi$$a10.1038/s41598-025-08808-3
000303376 0247_ $$2pmid$$apmid:40759673
000303376 037__ $$aDKFZ-2025-01625
000303376 041__ $$aEnglish
000303376 082__ $$a600
000303376 1001_ $$aKorshevniuk, Maryna$$b0
000303376 245__ $$aOptimized summary-statistic-based single-cell eQTL meta-analysis.
000303376 260__ $$a[London]$$bSpringer Nature$$c2025
000303376 3367_ $$2DRIVER$$aarticle
000303376 3367_ $$2DataCite$$aOutput Types/Journal article
000303376 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1754484504_17601
000303376 3367_ $$2BibTeX$$aARTICLE
000303376 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000303376 3367_ $$00$$2EndNote$$aJournal Article
000303376 520__ $$aThe identification of expression quantitative trait loci (eQTLs) holds great potential to improve the interpretation of disease-associated genetic variation. As many such disease-associated variants act in a context-, tissue- or even cell-type-specific manner, single-cell RNA-sequencing (scRNA-seq) data is uniquely suitable for identifying the specific cell type or context in which these genetic variants act. However, due to the limited sample sizes in single-cell studies, discovery of cell-type-specific eQTLs is now limited. To improve power to detect such eQTLs, large-scale joint analyses are needed. These are however, complicated by privacy constraints due to sharing of genotype data and the measurement and technical variety across different scRNA-seq datasets as a result of differences in mRNA capture efficiency, experimental protocols, and sequencing strategies. A solution to these issues is a federated weighted meta-analysis (WMA) approach in which summary statistics are integrated using dataset-specific weights. Here, we compare different strategies and provide best practice recommendations for eQTL WMA across scRNA-seq datasets.
000303376 536__ $$0G:(DE-HGF)POF4-312$$a312 - Funktionelle und strukturelle Genomforschung (POF4-312)$$cPOF4-312$$fPOF IV$$x0
000303376 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
000303376 650_7 $$2Other$$aWeighted meta-analysis
000303376 650_7 $$2Other$$aeQTL
000303376 650_7 $$2Other$$ascRNA-seq
000303376 650_2 $$2MeSH$$aQuantitative Trait Loci
000303376 650_2 $$2MeSH$$aSingle-Cell Analysis: methods
000303376 650_2 $$2MeSH$$aHumans
000303376 650_2 $$2MeSH$$aSequence Analysis, RNA
000303376 7001_ $$aWestra, Harm-Jan$$b1
000303376 7001_ $$aOelen, Roy$$b2
000303376 7001_ $$avan der Wijst, Monique G P$$b3
000303376 7001_ $$aFranke, Lude$$b4
000303376 7001_ $$0P:(DE-He78)ed3a2ed903bfbc6b0c33ef7009b141ce$$aBonder, Marc Jan$$b5
000303376 7001_ $$aConsortium, sc-eQTLGen$$b6$$eCollaboration Author
000303376 7001_ $$aAlquicira-Hernández, José$$b7$$eContributor
000303376 7001_ $$aKaptijn, Daniel$$b8$$eContributor
000303376 7001_ $$aKorshevniuk, Maryna$$b9$$eContributor
000303376 7001_ $$aLee, Jimmy Tsz Hang$$b10$$eContributor
000303376 7001_ $$aMichielsen, Lieke$$b11$$eContributor
000303376 7001_ $$aNeavin, Drew$$b12$$eContributor
000303376 7001_ $$aOelen, Roy$$b13$$eContributor
000303376 7001_ $$aRipoll-Cladellas, Aida$$b14$$eContributor
000303376 7001_ $$aVochterloo, Martijn$$b15$$eContributor
000303376 7001_ $$aAndo, Yoshinari$$b16$$eContributor
000303376 7001_ $$aBayaraa, Odmaa$$b17$$eContributor
000303376 7001_ $$avan Blokland, Irene$$b18$$eContributor
000303376 7001_ $$aDieng, Mame M$$b19$$eContributor
000303376 7001_ $$aGordon, M Grace$$b20$$eContributor
000303376 7001_ $$aGroot, Hilde E$$b21$$eContributor
000303376 7001_ $$avan der Harst, Pim$$b22$$eContributor
000303376 7001_ $$aHon, Chung-Chau$$b23$$eContributor
000303376 7001_ $$aIdaghdour, Youssef$$b24$$eContributor
000303376 7001_ $$aManikanda, Vinu$$b25$$eContributor
000303376 7001_ $$aMoody, Jonathan$$b26$$eContributor
000303376 7001_ $$aNawijn, Martijn C$$b27$$eContributor
000303376 7001_ $$aOkada, Yukinori$$b28$$eContributor
000303376 7001_ $$0P:(DE-He78)9aabcfee1a1fc9202398a45a63f0b1e3$$aStegle, Oliver$$b29$$eContributor$$udkfz
000303376 7001_ $$aPark, Woong-Yang$$b30$$eContributor
000303376 7001_ $$aRajagopalan, Deepa$$b31$$eContributor
000303376 7001_ $$aShahin, Tala$$b32$$eContributor
000303376 7001_ $$aShin, Jay W$$b33$$eContributor
000303376 7001_ $$aTrynka, Gosia$$b34$$eContributor
000303376 7001_ $$aWestra, Harm-Jan$$b35$$eContributor
000303376 7001_ $$aYazar, Seyhan$$b36$$eContributor
000303376 7001_ $$aYe, Jimmie$$b37$$eContributor
000303376 7001_ $$aHemberg, Martin$$b38$$eContributor
000303376 7001_ $$aMahfouz, Ahmed$$b39$$eContributor
000303376 7001_ $$aMelé, Marta$$b40$$eContributor
000303376 7001_ $$aPowell, Joseph E$$b41$$eContributor
000303376 7001_ $$aFranke, Lude$$b42$$eContributor
000303376 7001_ $$avan der Wijst, Monique G P$$b43$$eContributor
000303376 7001_ $$aBonder, Marc Jan$$b44$$eContributor
000303376 773__ $$0PERI:(DE-600)2615211-3$$a10.1038/s41598-025-08808-3$$gVol. 15, no. 1, p. 28407$$n1$$p28407$$tScientific reports$$v15$$x2045-2322$$y2025
000303376 909CO $$ooai:inrepo02.dkfz.de:303376$$pVDB
000303376 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)ed3a2ed903bfbc6b0c33ef7009b141ce$$aDeutsches Krebsforschungszentrum$$b5$$kDKFZ
000303376 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)9aabcfee1a1fc9202398a45a63f0b1e3$$aDeutsches Krebsforschungszentrum$$b29$$kDKFZ
000303376 9131_ $$0G:(DE-HGF)POF4-312$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vFunktionelle und strukturelle Genomforschung$$x0
000303376 9141_ $$y2025
000303376 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bSCI REP-UK : 2022$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2024-07-29T15:28:26Z
000303376 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2024-07-29T15:28:26Z
000303376 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Anonymous peer review$$d2024-07-29T15:28:26Z
000303376 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)1040$$2StatID$$aDBCoverage$$bZoological Record$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2024-12-18
000303376 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2024-12-18
000303376 9201_ $$0I:(DE-He78)B260-20160331$$kB260$$lB260 Bioinformatik der Genomik und Systemgenetik$$x0
000303376 980__ $$ajournal
000303376 980__ $$aVDB
000303376 980__ $$aI:(DE-He78)B260-20160331
000303376 980__ $$aUNRESTRICTED