### Citations

3993 | Regression shrinkage and selection via the lasso
- TIBSHIRANI
- 1996
(Show Context)
Citation Context ...ysis of eQTLs with epistatic and marginal effects in yeast. 2 BACKGROUND: LINEAR REGRESSION WITH STRUCTURED SPARSITY We begin with a brief review on regularized regression approaches including lasso (=-=Tibshirani, 1996-=-), group lasso (Yuan and Lin, 2006) and multitask lasso (Obozinski et al., 2006). 2.1 Notation for matrix operations Given a matrix B∈R K×J , we denote the k-th row by βk, the j-th column by βj , and ... |

1819 | PLINK: a tool set for whole-genome association and populationbased linkage analyses - Purcell, Neale, et al. - 2007 |

1126 | Model selection and estimation in regression with grouped variables
- Yuan, Lin
- 2007
(Show Context)
Citation Context ... marginal effects in yeast. 2 BACKGROUND: LINEAR REGRESSION WITH STRUCTURED SPARSITY We begin with a brief review on regularized regression approaches including lasso (Tibshirani, 1996), group lasso (=-=Yuan and Lin, 2006-=-) and multitask lasso (Obozinski et al., 2006). 2.1 Notation for matrix operations Given a matrix B∈R K×J , we denote the k-th row by βk, the j-th column by βj , and the (k,j) element by β j k . ‖·‖F ... |

914 | Ridge regression: biased estimation for nonorthogonal problems - Hoerl, Kennard - 1970 |

577 | Sparse inverse covariance estimation with the graphical lasso - Friedman, Hastie, et al. - 2008 |

529 | BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks - Maere, Heymans, et al. - 2005 |

321 |
An automated method for finding molecular complexes in large protein interaction networks
- Bader, Hogue
- 2003
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Citation Context ...teps. In the first step, we find highly interconnected subgraphs (or clusters) from the genetic interaction network using any graph clustering algorithms. In our experiments, we used MCODE algorithm (=-=Bader and Hogue, 2003-=-) for clustering the network. The clusters consist of genes, and the members in each cluster are likely to interact with each other. In the second step, we group all the SNPs or SNP pairs that are lin... |

238 | Global mapping of the yeast genetic interaction network - Tong, Lesage, et al. - 2004 |

168 | The genetic landscape of a cell - Costanzo, Baryshnikova, et al. - 2010 |

157 | Pathway-based approaches for analysis of genomewide association studies - Wang, Li, et al. - 2007 |

145 | Circos: an information aesthetic for comparative genomics - Krzywinski, I, et al. - 2009 |

142 | Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature Reviews Genetics - McCarthy, Abecasis, et al. - 2008 |

141 |
Catalysis of ATP-dependent homologous DNA pairing and strand exchange by yeast RAD51 protein. Science 265:1241–1243
- Sung
- 1994
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Citation Context ...genesis. We further investigated the mechanism of this significant SNP–SNP interaction. In our literature survey, RAD51 (RADiation sensitive) is strand exchange protein involved in DNA repair system (=-=Sung, 1994-=-), and NUP60 (NUclear Pore) is the subunit of the nuclear pore complex involved in nuclear export system (Denning et al., 2001). Also, it has been reported that yeast cells are excessively sensitive t... |

110 | Tree-guided group lasso for multi-task regression with structured sparsity
- Kim, Xing
- 2010
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Citation Context ...lasso is proposed to consider the groups of traits with many regulatory features in the genome (Lee et al., 2010). Graph-guided fused lasso (GFlasso) (Kim and Xing, 2009) and tree-guided group lasso (=-=Kim and Xing, 2010-=-) are developed to incorporate graph and tree structures on output sides, respectively. Recently, Curtis et al. (2012) proposed graph–graphguided fused lasso (gGFlasso) which attempted to use input st... |

96 | Exploring genetic interactions and networks with yeast - Boone - 2007 |

79 | High dimensional variable selection
- WASSERMAN, ROEDER
- 2009
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Citation Context ...ignificance of the non-zero coefficients and control false discovery rate. For high-dimensional regression problems, a few approaches have been proposed to compute P-values (Meinshausen et al., 2009; =-=Wasserman and Roeder, 2009-=-). We can use these techniques to compute P-values for the covariates (SNPs or SNP pairs) selected by our method. Here, we briefly describe ‘screen and clean’ procedure proposed by (Wasserman and Roed... |

78 |
The landscape of genetic complexity across 5,700 gene expression traits
- Brem, Kruglyak
- 2005
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Citation Context ...ther competitors in terms of recall and precision rates in finding true eQTLs with marginal and epistatic effects. Also, applying our model with the genetic interaction network to yeast eQTL dataset (=-=Brem and Kruglyak, 2005-=-), we detected SNPs having marginal and epistatic effects in yeast genome. Interestingly, we found a novel SNP pair (chr1:154328 and chr5:350744) with interaction effects that affects >400 traits rela... |

52 | A note on the group lasso and a sparse group lasso. Arxiv preprint arXiv:1001.0736 - Friedman, Hastie, et al. - 2010 |

49 |
PC: Epistasis-the essential role of gene interactions in the structure and evolution of genetic systems
- Phillips
(Show Context)
Citation Context ...et al., 2009). Unlike linear effects of eQTLs, detecting non-linear SNP–SNP interactions is still in its infancy due to a very large number of possible interactions between SNPs [we refer readers to (=-=Phillips, 2008-=-) for the meanings of SNP–SNP interactions or epistasis]. For example, a typical association analysis often involves up to millions of SNPs; with J ∼ 10 6 SNPs, the number of candidates of SNP pairs f... |

42 | Genetic interactions between polymorphisms that affect gene expression in yeast. Nature 436 - Brem, Storey, et al. - 2005 |

39 | Statistical estimation of correlated genome associations to a quantitative trait network
- Kim, Xing
(Show Context)
Citation Context ...guided fused lasso analyzed multiple traits simultaneously by considering a network of multiple traits to find genetic markers with pleiotropic effects that affect multiple-correlated traits jointly (=-=Kim and Xing, 2009-=-). Another approach, Lirnet, was proposed to make use of prior knowledge on regulatory features, such as conservation scores for a more informed search of association SNPs (Lee et al., 2009). Unlike l... |

36 | P-values for high-dimensional regression - Meinshausen, Meier, et al. - 2009 |

31 | Multiple locus linkage analysis of genomewide expression in yeast - Storey, Akey, et al. - 2005 |

28 | A global view of pleiotropy and phenotypically derived gene function in yeast - Dudley |

28 | Simultaneous support recovery in highdimensional regression: Benefits and perils of L1-L∞-regularization
- Negahban, Wainwright
- 2011
(Show Context)
Citation Context ...they are set to zero. Second, taking advantage of the output groups, we can share information across the correlated outputs, and it decreases the sample size required for successful support recovery (=-=Negahban and Wainwright, 2011-=-). Overall, to detect causal SNPs having small effects, our model increases signal-to-noise ratio by grouping the SNPs, and simultaneously decreases the required number of samples by grouping phenotyp... |

27 | Learning a prior on regulatory potential from eQTL data - Lee, Dudley, et al. - 2009 |

26 | Efficient methods for overlapping group lasso - Yuan, Liu, et al. - 2011 |

22 | The nucleoporin Nup60p functions as a Gsp1p-GTP-sensitive tether for Nup2p at the nuclear pore complex - Denning, Mykytka, et al. - 2001 |

21 | Functional targeting of DNA damage to a nuclear pore-associated SUMO-dependent ubiquitin ligase - Nagai, Dubrana, et al. - 2008 |

17 | Using biological networks to search for interacting loci in genome-wide association studies - Emily, Mailund, et al. - 2009 |

17 | Adatpive multi-task lasso: with applications to eqtl detection - Lee, Zhu, et al. - 2010 |

15 | Joint covariate selection for grouped classification - Obozinski - 2006 |

11 |
The genetics of phenotypic plasticity. VI. Theoretical predictions for directional selection
- Gavrilets, Scheiner
- 1993
(Show Context)
Citation Context ...task regression’, we propose ‘structured polynomial multitask regression’ to detect epistatic effects as well as marginal effects of SNPs in the genome. In this model, we adopt polynomial regression (=-=Gavrilets and Scheiner, 1993-=-) and include additional regressors for higher order terms. However, in genome-wide association studies, considering all pairs of SNPs is infeasible even for second-order polynomial regression because... |

11 | Drygin: a database of quantitative genetic interaction networks in yeast - Koh, Ding, et al. |

6 | Analysis of multilocus models of association - Devlin - 2003 |

5 |
Comparative Genomics: Using Fungi as Models
- Axelson-Fisk, Sunnerhagen
(Show Context)
Citation Context ...umed that a SNP is linked to a gene if the distance between them is <500 bp. We consider it a reasonable choice for cis-effect as the size of intergene regions for S. cerevisiae is 515 bp on average (=-=Sunnerhagen and Piskur, 2006-=-). As a result, we included 982 interaction terms from the interaction network in X with 1260 individual SNPs. The number SNP pairs from two-locus epistasis test was different depending on the trait. ... |

2 |
Adjusting for multiple testing − when and how
- Bendera, Langeb
- 2001
(Show Context)
Citation Context ...rwise interactions becomes J 2 which is clearly pushing the limit of practical computing resources. More importantly, it also carries a serious statistical issue that is the multiple testing problem (=-=Bendera and Langeb, 2001-=-). If we test all SNP pairs to find epistatic effects, only a handful of SNP pairs may be left after correcting for multiple hypothesis testing. To cope with the problem, previous methods attempted to... |

2 | Finding genome-transcriptome-phenome association with structured association mapping and visualization in genamap - Curtis - 2012 |