guest ::
| Home > Publications Database > FARVAT: a family-based rare variant association test. > print |
| 001 | 137632 | ||
| 005 | 20240321220302.0 | ||
| 024 | 7 | _ | |a 10.1093/bioinformatics/btu496 |2 doi |
| 024 | 7 | _ | |a pmid:25075118 |2 pmid |
| 024 | 7 | _ | |a 0266-7061 |2 ISSN |
| 024 | 7 | _ | |a 1367-4803 |2 ISSN |
| 024 | 7 | _ | |a 1367-4811 |2 ISSN |
| 024 | 7 | _ | |a 1460-2059 |2 ISSN |
| 024 | 7 | _ | |a altmetric:2558370 |2 altmetric |
| 037 | _ | _ | |a DZNE-2020-03954 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 570 |
| 100 | 1 | _ | |a Choi, Sungkyoung |0 P:(DE-HGF)0 |b 0 |
| 245 | _ | _ | |a FARVAT: a family-based rare variant association test. |
| 260 | _ | _ | |a Oxford |c 2014 |b Oxford Univ. Press |
| 264 | _ | 1 | |3 online |2 Crossref |b Oxford University Press (OUP) |c 2014-07-29 |
| 264 | _ | 1 | |3 print |2 Crossref |b Oxford University Press (OUP) |c 2014-11-15 |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1588080504_27523 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Individuals in each family are genetically more homogeneous than unrelated individuals, and family-based designs are often recommended for the analysis of rare variants. However, despite the importance of family-based samples analysis, few statistical methods for rare variant association analysis are available.In this report, we propose a FAmily-based Rare Variant Association Test (FARVAT). FARVAT is based on the quasi-likelihood of whole families, and is statistically and computationally efficient for the extended families. FARVAT assumed that families were ascertained with the disease status of family members, and incorporation of the estimated genetic relationship matrix to the proposed method provided robustness under the presence of the population substructure. Depending on the choice of working matrix, our method could be a burden test or a variance component test, and could be extended to the SKAT-O-type statistic. FARVAT was implemented in C++, and application of the proposed method to schizophrenia data and simulated data for GAW17 illustrated its practical importance.The software calculates various statistics for the analysis of related samples, and it is freely downloadable from http://healthstats.snu.ac.kr/software/farvat.won1@snu.ac.kr or tspark@stats.snu.ac.krsupplementary data are available at Bioinformatics online. |
| 536 | _ | _ | |a 345 - Population Studies and Genetics (POF3-345) |0 G:(DE-HGF)POF3-345 |c POF3-345 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef, PubMed, |
| 650 | _ | 2 | |a Family |2 MeSH |
| 650 | _ | 2 | |a Genetic Association Studies: methods |2 MeSH |
| 650 | _ | 2 | |a Genetic Variation |2 MeSH |
| 650 | _ | 2 | |a Humans |2 MeSH |
| 650 | _ | 2 | |a Schizophrenia: genetics |2 MeSH |
| 650 | _ | 2 | |a Software |2 MeSH |
| 700 | 1 | _ | |a Lee, Sungyoung |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Cichon, Sven |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Nöthen, Markus M |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Lange, Christoph |0 P:(DE-2719)9000181 |b 4 |u dzne |
| 700 | 1 | _ | |a Park, Taesung |0 P:(DE-HGF)0 |b 5 |e Corresponding author |
| 700 | 1 | _ | |a Won, Sungho |0 P:(DE-HGF)0 |b 6 |
| 773 | 1 | 8 | |a 10.1093/bioinformatics/btu496 |b : Oxford University Press (OUP), 2014-07-29 |n 22 |p 3197-3205 |3 journal-article |2 Crossref |t Bioinformatics |v 30 |y 2014 |x 1460-2059 |
| 773 | _ | _ | |a 10.1093/bioinformatics/btu496 |g Vol. 30, no. 22, p. 3197 - 3205 |0 PERI:(DE-600)1468345-3 |n 22 |q 30:22<3197 - 3205 |p 3197-3205 |t Bioinformatics |v 30 |y 2014 |x 1460-2059 |
| 909 | C | O | |o oai:pub.dzne.de:137632 |p VDB |
| 910 | 1 | _ | |a Deutsches Zentrum für Neurodegenerative Erkrankungen |0 I:(DE-588)1065079516 |k DZNE |b 4 |6 P:(DE-2719)9000181 |
| 913 | 1 | _ | |a DE-HGF |b Forschungsbereich Gesundheit |l Erkrankungen des Nervensystems |1 G:(DE-HGF)POF3-340 |0 G:(DE-HGF)POF3-345 |2 G:(DE-HGF)POF3-300 |v Population Studies and Genetics |x 0 |
| 914 | 1 | _ | |y 2014 |
| 915 | _ | _ | |a Nationallizenz |0 StatID:(DE-HGF)0420 |2 StatID |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0310 |2 StatID |b NCBI Molecular Biology Database |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0320 |2 StatID |b PubMed Central |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b BIOINFORMATICS : 2017 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0110 |2 StatID |b Science Citation Index |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |
| 915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b BIOINFORMATICS : 2017 |
| 920 | 1 | _ | |0 I:(DE-2719)7000008 |k U T4 Researchers - Bonn |l U T4 Researchers - Bonn |x 0 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-2719)7000008 |
| 980 | _ | _ | |a UNRESTRICTED |
| 999 | C | 5 | |a 10.1186/1753-6561-5-S9-S2 |9 -- missing cx lookup -- |2 Crossref |o 10.1186/1753-6561-5-S9-S2 |
| 999 | C | 5 | |a 10.1007/BF01441146 |9 -- missing cx lookup -- |2 Crossref |o 10.1007/BF01441146 |
| 999 | C | 5 | |y 1995 |2 Crossref |o Benjamini 1995 |
| 999 | C | 5 | |a 10.1159/000472383 |9 -- missing cx lookup -- |2 Crossref |o 10.1159/000472383 |
| 999 | C | 5 | |a 10.4161/fly.19695 |9 -- missing cx lookup -- |2 Crossref |o 10.4161/fly.19695 |
| 999 | C | 5 | |y 1980 |2 Crossref |o Davies 1980 |
| 999 | C | 5 | |a 10.1371/journal.pone.0048495 |9 -- missing cx lookup -- |2 Crossref |o 10.1371/journal.pone.0048495 |
| 999 | C | 5 | |a 10.1002/gepi.20643 |9 -- missing cx lookup -- |2 Crossref |o 10.1002/gepi.20643 |
| 999 | C | 5 | |a 10.1016/j.ajhg.2013.11.021 |9 -- missing cx lookup -- |2 Crossref |o 10.1016/j.ajhg.2013.11.021 |
| 999 | C | 5 | |a 10.1371/journal.pgen.1001289 |9 -- missing cx lookup -- |2 Crossref |o 10.1371/journal.pgen.1001289 |
| 999 | C | 5 | |a 10.1038/ejhg.2012.308 |9 -- missing cx lookup -- |2 Crossref |o 10.1038/ejhg.2012.308 |
| 999 | C | 5 | |a 10.1002/1098-2272(2000)19:1+<::AID-GEPI6>3.0.CO;2-M |9 -- missing cx lookup -- |2 Crossref |o 10.1002/1098-2272(2000)19:1+<::AID-GEPI6>3.0.CO;2-M |
| 999 | C | 5 | |a 10.1086/342406 |9 -- missing cx lookup -- |2 Crossref |o 10.1086/342406 |
| 999 | C | 5 | |a 10.1159/000073728 |9 -- missing cx lookup -- |2 Crossref |o 10.1159/000073728 |
| 999 | C | 5 | |a 10.1016/j.ajhg.2012.06.007 |9 -- missing cx lookup -- |2 Crossref |o 10.1016/j.ajhg.2012.06.007 |
| 999 | C | 5 | |a 10.1093/biostatistics/kxs014 |9 -- missing cx lookup -- |2 Crossref |o 10.1093/biostatistics/kxs014 |
| 999 | C | 5 | |a 10.1016/j.ajhg.2008.06.024 |9 -- missing cx lookup -- |2 Crossref |o 10.1016/j.ajhg.2008.06.024 |
| 999 | C | 5 | |a 10.1016/j.csda.2008.11.025 |9 -- missing cx lookup -- |2 Crossref |o 10.1016/j.csda.2008.11.025 |
| 999 | C | 5 | |a 10.1038/nature08494 |9 -- missing cx lookup -- |2 Crossref |o 10.1038/nature08494 |
| 999 | C | 5 | |a 10.1111/j.0006-341X.2004.00180.x |9 -- missing cx lookup -- |2 Crossref |o 10.1111/j.0006-341X.2004.00180.x |
| 999 | C | 5 | |a 10.1371/journal.pgen.1001322 |9 -- missing cx lookup -- |2 Crossref |o 10.1371/journal.pgen.1001322 |
| 999 | C | 5 | |a 10.1016/j.ajhg.2010.04.005 |9 -- missing cx lookup -- |2 Crossref |o 10.1016/j.ajhg.2010.04.005 |
| 999 | C | 5 | |a 10.1038/ng1847 |9 -- missing cx lookup -- |2 Crossref |o 10.1038/ng1847 |
| 999 | C | 5 | |a 10.1101/gr.3709305 |9 -- missing cx lookup -- |2 Crossref |o 10.1101/gr.3709305 |
| 999 | C | 5 | |y 2011 |2 Crossref |o Shi 2011 |
| 999 | C | 5 | |y 1993 |2 Crossref |o Spielman 1993 |
| 999 | C | 5 | |a 10.1086/519497 |9 -- missing cx lookup -- |2 Crossref |o 10.1086/519497 |
| 999 | C | 5 | |a 10.1016/j.ajhg.2010.01.001 |9 -- missing cx lookup -- |2 Crossref |o 10.1016/j.ajhg.2010.01.001 |
| 999 | C | 5 | |a 10.1002/gepi.21638 |9 -- missing cx lookup -- |2 Crossref |o 10.1002/gepi.21638 |
| 999 | C | 5 | |a 10.1038/ng1582 |9 -- missing cx lookup -- |2 Crossref |o 10.1038/ng1582 |
| 999 | C | 5 | |a 10.1002/gepi.20341 |9 -- missing cx lookup -- |2 Crossref |o 10.1002/gepi.20341 |
| 999 | C | 5 | |a 10.1002/sim.5865 |9 -- missing cx lookup -- |2 Crossref |o 10.1002/sim.5865 |
| 999 | C | 5 | |a 10.1371/journal.pgen.1000741 |9 -- missing cx lookup -- |2 Crossref |o 10.1371/journal.pgen.1000741 |
| 999 | C | 5 | |a 10.1016/j.ajhg.2011.05.029 |9 -- missing cx lookup -- |2 Crossref |o 10.1016/j.ajhg.2011.05.029 |
| 999 | C | 5 | |a 10.1038/ng.823 |9 -- missing cx lookup -- |2 Crossref |o 10.1038/ng.823 |
| 999 | C | 5 | |a 10.1016/j.ajhg.2012.04.022 |9 -- missing cx lookup -- |2 Crossref |o 10.1016/j.ajhg.2012.04.022 |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|