419 related articles for article (PubMed ID: 33733355)
1. Protocol for Construction of Genome-Wide Epistatic SNP Networks Using WISH-R Package.
Kadarmideen HN; Carmelo VAO
Methods Mol Biol; 2021; 2212():155-168. PubMed ID: 33733355
[TBL] [Abstract][Full Text] [Related]
2. WISH-R- a fast and efficient tool for construction of epistatic networks for complex traits and diseases.
Carmelo VAO; Kogelman LJA; Madsen MB; Kadarmideen HN
BMC Bioinformatics; 2018 Jul; 19(1):277. PubMed ID: 30064383
[TBL] [Abstract][Full Text] [Related]
3. Weighted Interaction SNP Hub (WISH) network method for building genetic networks for complex diseases and traits using whole genome genotype data.
Kogelman LJ; Kadarmideen HN
BMC Syst Biol; 2014; 8 Suppl 2(Suppl 2):S5. PubMed ID: 25032480
[TBL] [Abstract][Full Text] [Related]
4. Two-Stage Testing for Epistasis: Screening and Verification.
Pecanka J; Jonker MA
Methods Mol Biol; 2021; 2212():69-92. PubMed ID: 33733351
[TBL] [Abstract][Full Text] [Related]
5. Phenotype Prediction Under Epistasis.
Vojgani E; Pook T; Simianer H
Methods Mol Biol; 2021; 2212():105-120. PubMed ID: 33733353
[TBL] [Abstract][Full Text] [Related]
6. The Combined Analysis of Pleiotropy and Epistasis (CAPE).
Tyler AL; Emerson J; El Kassaby B; Wells AE; Philip VM; Carter GW
Methods Mol Biol; 2021; 2212():55-67. PubMed ID: 33733350
[TBL] [Abstract][Full Text] [Related]
7. Protocol for Epistasis Detection with Machine Learning Using GenEpi Package.
Petinrin OO; Wong KC
Methods Mol Biol; 2021; 2212():291-305. PubMed ID: 33733363
[TBL] [Abstract][Full Text] [Related]
8. Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies.
Ma L; Runesha HB; Dvorkin D; Garbe JR; Da Y
BMC Bioinformatics; 2008 Jul; 9():315. PubMed ID: 18644146
[TBL] [Abstract][Full Text] [Related]
9. Leveraging the genetic correlation between traits improves the detection of epistasis in genome-wide association studies.
Stamp J; DenAdel A; Weinreich D; Crawford L
G3 (Bethesda); 2023 Aug; 13(8):. PubMed ID: 37243672
[TBL] [Abstract][Full Text] [Related]
10. EPIQ-efficient detection of SNP-SNP epistatic interactions for quantitative traits.
Arkin Y; Rahmani E; Kleber ME; Laaksonen R; März W; Halperin E
Bioinformatics; 2014 Jun; 30(12):i19-25. PubMed ID: 24931983
[TBL] [Abstract][Full Text] [Related]
11. Epi2Loc: an R package to investigate two-locus epistatic models.
Walters RK; Laurin C; Lubke GH
Twin Res Hum Genet; 2014 Aug; 17(4):272-8. PubMed ID: 24983251
[TBL] [Abstract][Full Text] [Related]
12. PEPIS: A Pipeline for Estimating Epistatic Effects in Quantitative Trait Locus Mapping and Genome-Wide Association Studies.
Zhang W; Dai X; Wang Q; Xu S; Zhao PX
PLoS Comput Biol; 2016 May; 12(5):e1004925. PubMed ID: 27224861
[TBL] [Abstract][Full Text] [Related]
13. A Bayesian model for detection of high-order interactions among genetic variants in genome-wide association studies.
Wang J; Joshi T; Valliyodan B; Shi H; Liang Y; Nguyen HT; Zhang J; Xu D
BMC Genomics; 2015 Nov; 16():1011. PubMed ID: 26607428
[TBL] [Abstract][Full Text] [Related]
14. Leveraging input and output structures for joint mapping of epistatic and marginal eQTLs.
Lee S; Xing EP
Bioinformatics; 2012 Jun; 28(12):i137-46. PubMed ID: 22689753
[TBL] [Abstract][Full Text] [Related]
15. Gene, pathway and network frameworks to identify epistatic interactions of single nucleotide polymorphisms derived from GWAS data.
Liu Y; Maxwell S; Feng T; Zhu X; Elston RC; Koyutürk M; Chance MR
BMC Syst Biol; 2012; 6 Suppl 3(Suppl 3):S15. PubMed ID: 23281810
[TBL] [Abstract][Full Text] [Related]
16. Genetic architecture of growth traits in Populus revealed by integrated quantitative trait locus (QTL) analysis and association studies.
Du Q; Gong C; Wang Q; Zhou D; Yang H; Pan W; Li B; Zhang D
New Phytol; 2016 Feb; 209(3):1067-82. PubMed ID: 26499329
[TBL] [Abstract][Full Text] [Related]
17. Epistatic Networks Jointly Influence Phenotypes Related to Metabolic Disease and Gene Expression in Diversity Outbred Mice.
Tyler AL; Ji B; Gatti DM; Munger SC; Churchill GA; Svenson KL; Carter GW
Genetics; 2017 Jun; 206(2):621-639. PubMed ID: 28592500
[TBL] [Abstract][Full Text] [Related]
18. Genome-wide association mapping reveals epistasis and genetic interaction networks in sugar beet.
Würschum T; Maurer HP; Schulz B; Möhring J; Reif JC
Theor Appl Genet; 2011 Jun; 123(1):109-18. PubMed ID: 21448808
[TBL] [Abstract][Full Text] [Related]
19. MatrixEpistasis: ultrafast, exhaustive epistasis scan for quantitative traits with covariate adjustment.
Zhu S; Fang G
Bioinformatics; 2018 Jul; 34(14):2341-2348. PubMed ID: 29509873
[TBL] [Abstract][Full Text] [Related]
20. Mapping the genetic architecture of complex traits in experimental populations.
Yang J; Zhu J; Williams RW
Bioinformatics; 2007 Jun; 23(12):1527-36. PubMed ID: 17459962
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]