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@article{Leek:2010p1819,
author = {Jeffrey T Leek and Robert B Scharpf and H{\'e}ctor Corrada Bravo and David Simcha and Benjamin Langmead and W Evan Johnson and Donald Geman and Keith Baggerly and Rafael A Irizarry}, 
journal = {Nat Rev Genet},
title = {Tackling the widespread and critical impact of batch effects in high-throughput data},
abstract = {High-throughput technologies are widely used, for example to assay genetic variants, gene and protein expression, and epigenetic modifications. One often overlooked complication with such studies is batch effects, which occur because measurements are affected by laboratory conditions, reagent lots and personnel differences. This becomes a major problem when batch effects are correlated with an outcome of interest and lead to incorrect conclusions. Using both published studies and our own analyses, we argue that batch effects (as well as other technical and biological artefacts) are widespread and critical to address. We review experimental and computational approaches for doing so.},
affiliation = {Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205-2179, USA.},
number = {10},
pages = {733--9},
volume = {11},
year = {2010},
month = {Oct},
language = {eng},
date-added = {2010-09-29 22:37:31 -0400},
date-modified = {2011-12-13 09:56:33 -0500},
doi = {10.1038/nrg2825},
pii = {nrg2825},
pmid = {20838408},
URL = {http://www.nature.com/nrg/journal/v11/n10/full/nrg2825.html},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2010/Leek/Nat%20Rev%20Genet%202010%20Leek.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p1819},
read = {Yes},
rating = {0}
}

@article{Stegle:2010p2015,
author = {Oliver Stegle and Leopold Parts and Richard Durbin and John Winn}, 
journal = {PLoS Comput Biol},
title = {A Bayesian framework to account for complex non-genetic factors in gene expression levels greatly increases power in eQTL studies},
abstract = {Gene expression measurements are influenced by a wide range of factors, such as the state of the cell, experimental conditions and variants in the sequence of regulatory regions. To understand the effect of a variable of interest, such as the genotype of a locus, it is important to account for variation that is due to confounding causes. Here, we present VBQTL, a probabilistic approach for mapping expression quantitative trait loci (eQTLs) that jointly models contributions from genotype as well as known and hidden confounding factors. VBQTL is implemented within an efficient and flexible inference framework, making it fast and tractable on large-scale problems. We compare the performance of VBQTL with alternative methods for dealing with confounding variability on eQTL mapping datasets from simulations, yeast, mouse, and human. Employing Bayesian complexity control and joint modelling is shown to result in more precise estimates of the contribution of different confounding factors resulting in additional associations to measured transcript levels compared to alternative approaches. We present a threefold larger collection of cis eQTLs than previously found in a whole-genome eQTL scan of an outbred human population. Altogether, 27% of the tested probes show a significant genetic association in cis, and we validate that the additional eQTLs are likely to be real by replicating them in different sets of individuals. Our method is the next step in the analysis of high-dimensional phenotype data, and its application has revealed insights into genetic regulation of gene expression by demonstrating more abundant cis-acting eQTLs in human than previously shown. Our software is freely available online at http://www.sanger.ac.uk/resources/software/peer/.},
affiliation = {Max Planck Institutes T{\"u}bingen, T{\"u}bingen, Germany. oliver.stegle@tuebingen.mpg.de},
number = {5},
pages = {e1000770},
volume = {6},
year = {2010},
month = {May},
language = {eng},
keywords = {Bayes Theorem, Quantitative Trait Loci, Internet, Models: Genetic, Reproducibility of Results, Databases: Genetic, Yeasts, Gene Expression, Models: Statistical, Markov Chains, Phenotype, Mice, Software, Animals, Humans}, 
date-added = {2010-11-26 12:54:54 -0500},
date-modified = {2011-03-02 14:28:52 -0500},
doi = {10.1371/journal.pcbi.1000770},
pmid = {20463871},
URL = {http://www.ploscompbiol.org/article/info%253Adoi%252F10.1371%252Fjournal.pcbi.1000770},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2010/Stegle/PLoS%20Comput%20Biol%202010%20Stegle.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p2015},
read = {Yes},
rating = {0}
}

@article{Petretto:2010p2678,
author = {Enrico Petretto and Leonardo Bottolo and Sarah R Langley and Matthias Heinig and Chris McDermott-Roe and Rizwan Sarwar and Michal Pravenec and Norbert H{\"u}bner and Timothy J Aitman and Stuart A Cook and Sylvia Richardson}, 
journal = {PLoS Comput Biol},
title = {New insights into the genetic control of gene expression using a Bayesian multi-tissue approach},
abstract = {The majority of expression quantitative trait locus (eQTL) studies have been carried out in single tissues or cell types, using methods that ignore information shared across tissues. Although global analysis of RNA expression in multiple tissues is now feasible, few integrated statistical frameworks for joint analysis of gene expression across tissues combined with simultaneous analysis of multiple genetic variants have been developed to date. Here, we propose Sparse Bayesian Regression models for mapping eQTLs within individual tissues and simultaneously across tissues. Testing these on a set of 2,000 genes in four tissues, we demonstrate that our methods are more powerful than traditional approaches in revealing the true complexity of the eQTL landscape at the systems-level. Highlighting the power of our method, we identified a two-eQTL model (cis/trans) for the Hopx gene that was experimentally validated and was not detected by conventional approaches. We showed common genetic regulation of gene expression across four tissues for approximately 27% of transcripts, providing >5 fold increase in eQTLs detection when compared with single tissue analyses at 5% FDR level. These findings provide a new opportunity to uncover complex genetic regulatory mechanisms controlling global gene expression while the generality of our modelling approach makes it adaptable to other model systems and humans, with broad application to analysis of multiple intermediate and whole-body phenotypes.},
affiliation = {Medical Research Council Clinical Sciences Centre, Faculty of Medicine, Imperial College London, London, United Kingdom.},
number = {4},
pages = {e1000737},
volume = {6},
year = {2010},
month = {Apr},
language = {eng},
keywords = {Models: Genetic, Gene Regulatory Networks, Heart Ventricles, Reproducibility of Results, Sensitivity and Specificity, Animals, Adrenal Glands, Algorithms, Humans, Adipose Tissue, Bayes Theorem, Regression Analysis, Kidney, Gene Expression Regulation, Quantitative Trait Loci, Gene Expression Profiling}, 
date-added = {2011-03-05 22:43:54 -0500},
date-modified = {2011-03-05 22:44:21 -0500},
doi = {10.1371/journal.pcbi.1000737},
pmid = {20386736},
URL = {http://www.ploscompbiol.org/article/info%253Adoi%252F10.1371%252Fjournal.pcbi.1000737},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2010/Petretto/PLoS%20Comput%20Biol%202010%20Petretto.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p2678},
read = {Yes},
rating = {0}
}

@article{CoulombeHuntington:2009p3145,
author = {Jasmin Coulombe-Huntington and Kevin C L Lam and Christel Dias and Jacek Majewski}, 
journal = {PLoS Genet},
title = {Fine-scale variation and genetic determinants of alternative splicing across individuals},
abstract = {Recently, thanks to the increasing throughput of new technologies, we have begun to explore the full extent of alternative pre-mRNA splicing (AS) in the human transcriptome. This is unveiling a vast layer of complexity in isoform-level expression differences between individuals. We used previously published splicing sensitive microarray data from lymphoblastoid cell lines to conduct an in-depth analysis on splicing efficiency of known and predicted exons. By combining publicly available AS annotation with a novel algorithm designed to search for AS, we show that many real AS events can be detected within the usually unexploited, speculative majority of the array and at significance levels much below standard multiple-testing thresholds, demonstrating that the extent of cis-regulated differential splicing between individuals is potentially far greater than previously reported. Specifically, many genes show subtle but significant genetically controlled differences in splice-site usage. PCR validation shows that 42 out of 58 (72%) candidate gene regions undergo detectable AS, amounting to the largest scale validation of isoform eQTLs to date. Targeted sequencing revealed a likely causative SNP in most validated cases. In all 17 incidences where a SNP affected a splice-site region, in silico splice-site strength modeling correctly predicted the direction of the micro-array and PCR results. In 13 other cases, we identified likely causative SNPs disrupting predicted splicing enhancers. Using Fst and REHH analysis, we uncovered significant evidence that 2 putative causative SNPs have undergone recent positive selection. We verified the effect of five SNPs using in vivo minigene assays. This study shows that splicing differences between individuals, including quantitative differences in isoform ratios, are frequent in human populations and that causative SNPs can be identified using in silico predictions. Several cases affected disease-relevant genes and it is likely some of these differences are involved in phenotypic diversity and susceptibility to complex diseases.},
affiliation = {Department of Human Genetics, McGill University, Montreal, Qu{\'e}bec, Canada.},
number = {12},
pages = {e1000766},
volume = {5},
year = {2009},
month = {Dec},
language = {eng},
keywords = {Alternative Splicing, Polymerase Chain Reaction, Genetic Predisposition to Disease, Oligonucleotide Array Sequence Analysis, Humans, RNA: Messenger, Polymorphism: Single Nucleotide}, 
date-added = {2011-05-16 15:33:54 -0400},
date-modified = {2011-05-16 15:33:54 -0400},
doi = {10.1371/journal.pgen.1000766},
pmid = {20011102},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2009/Coulombe-Huntington/PLoS%20Genet%202009%20Coulombe-Huntington.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p3145},
read = {Yes},
rating = {0}
}

@article{Montgomery:2010p1661,
author = {Stephen B Montgomery and Micha Sammeth and Maria Gutierrez-Arcelus and Radoslaw P Lach and Catherine Ingle and James Nisbett and Roderic Guigo and Emmanouil T Dermitzakis}, 
journal = {Nature},
title = {Transcriptome genetics using second generation sequencing in a Caucasian population},
abstract = {Gene expression is an important phenotype that informs about genetic and environmental effects on cellular state. Many studies have previously identified genetic variants for gene expression phenotypes using custom and commercially available microarrays. Second generation sequencing technologies are now providing unprecedented access to the fine structure of the transcriptome. We have sequenced the mRNA fraction of the transcriptome in 60 extended HapMap individuals of European descent and have combined these data with genetic variants from the HapMap3 project. We have quantified exon abundance based on read depth and have also developed methods to quantify whole transcript abundance. We have found that approximately 10 million reads of sequencing can provide access to the same dynamic range as arrays with better quantification of alternative and highly abundant transcripts. Correlation with SNPs (small nucleotide polymorphisms) leads to a larger discovery of eQTLs (expression quantitative trait loci) than with arrays. We also detect a substantial number of variants that influence the structure of mature transcripts indicating variants responsible for alternative splicing. Finally, measures of allele-specific expression allowed the identification of rare eQTLs and allelic differences in transcript structure. This analysis shows that high throughput sequencing technologies reveal new properties of genetic effects on the transcriptome and allow the exploration of genetic effects in cellular processes.},
affiliation = {Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, 1211 Switzerland. stephen.montgomery@unige.ch},
number = {7289},
pages = {773--7},
volume = {464},
year = {2010},
month = {Apr},
language = {eng},
date-added = {2010-05-05 10:00:12 -0400},
date-modified = {2011-03-28 13:34:23 -0400},
doi = {10.1038/nature08903},
pii = {nature08903},
pmid = {20220756},
URL = {http://www.nature.com/nature/journal/v464/n7289/full/nature08903.html},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2010/Montgomery/Nature%202010%20Montgomery.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p1661},
read = {Yes},
rating = {0}
}

@article{Cheung:2005p446,
author = {Vivian G Cheung and Richard S Spielman and Kathryn G Ewens and Teresa M Weber and Michael Morley and Joshua T Burdick}, 
journal = {Nature},
title = {Mapping determinants of human gene expression by regional and genome-wide association},
abstract = {To study the genetic basis of natural variation in gene expression, we previously carried out genome-wide linkage analysis and mapped the determinants of approximately 1,000 expression phenotypes. In the present study, we carried out association analysis with dense sets of single-nucleotide polymorphism (SNP) markers from the International HapMap Project. For 374 phenotypes, the association study was performed with markers only from regions with strong linkage evidence; these regions all mapped close to the expressed gene. For a subset of 27 phenotypes, analysis of genome-wide association was performed with >770,000 markers. The association analysis with markers under the linkage peaks confirmed the linkage results and narrowed the candidate regulatory regions for many phenotypes with strong linkage evidence. The genome-wide association analysis yielded highly significant results that point to the same locations as the genome scans for about 50% of the phenotypes. For one candidate determinant, we carried out functional analyses and confirmed the variation in cis-acting regulatory activity. Our findings suggest that association studies with dense SNP maps will identify susceptibility loci or other determinants for some complex traits or diseases.},
affiliation = {Department of Pediatrics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA. vcheung@mail.med.upenn.edu},
number = {7063},
pages = {1365--9},
volume = {437},
year = {2005},
month = {Oct},
language = {eng},
keywords = {RNA Polymerase II, Gene Expression Regulation, Alleles, Polymorphism: Single Nucleotide, Humans, Phenotype, Chromatin Immunoprecipitation, Genome: Human, Haplotypes, Genetic Markers, Genetic Predisposition to Disease}, 
date-added = {2009-07-06 09:26:47 -0400},
date-modified = {2010-12-02 22:35:13 -0500},
doi = {10.1038/nature04244},
pii = {nature04244},
pmid = {16251966},
URL = {http://192.168.100.1:5280/?redirect=http%253A//eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2005/Cheung/Nature%202005%20Cheung.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p446},
read = {Yes},
rating = {0}
}

@article{Williams:2007p21,
author = {R. B.H Williams and E. K.F Chan and M. J Cowley and P. F.R Little}, 
journal = {Genome Research},
title = {The influence of genetic variation on gene expression},
number = {12},
pages = {1707--1716},
volume = {17},
year = {2007},
month = {Dec},
date-added = {2009-06-01 12:30:54 -0400},
date-modified = {2009-07-22 16:12:35 -0400},
doi = {10.1101/gr.6981507},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2007/Williams/Genome%20Research%202007%20Williams.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p21},
read = {Yes},
rating = {0}
}

@article{Pandit:2008p3187,
author = {Shatakshi Pandit and Dong Wang and Xiang-Dong Fu}, 
journal = {Curr Opin Cell Biol},
title = {Functional integration of transcriptional and RNA processing machineries},
abstract = {Cotranscriptional RNA processing not only permits temporal RNA processing before the completion of transcription but also allows sequential recognition of RNA processing signals on nascent transcripts threading out from the elongating RNA polymerase II (RNAPII) complex. Rapid progress in recent years has established multiple contacts that physically connect the transcription and RNA processing machineries, which centers on the C-terminal domain (CTD) of the largest subunit of RNAPII. Although cotranscriptional RNA processing has been substantiated, the evidence for 'reciprocal' coupling starts to emerge, which emphasizes functional integration of transcription and RNA processing machineries in a mutually beneficial manner for efficient and regulated gene expression.},
affiliation = {Department of Cellular and Molecular Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0651, United States.},
number = {3},
pages = {260--5},
volume = {20},
year = {2008},
month = {Jun},
language = {eng},
keywords = {Humans, Animals, Regulatory Elements: Transcriptional, RNA: Messenger, Transcription: Genetic, RNA Polymerase II, Transcription Factors, Gene Expression Regulation, RNA Splicing, Protein Structure: Tertiary, RNA Precursors}, 
date-added = {2011-05-16 15:56:44 -0400},
date-modified = {2011-05-16 15:56:44 -0400},
doi = {10.1016/j.ceb.2008.03.001},
pii = {S0955-0674(08)00033-1},
pmid = {18436438},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2008/Pandit/Curr%20Opin%20Cell%20Biol%202008%20Pandit.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p3187},
read = {Yes},
rating = {0}
}

@article{Stranger:2007p114,
author = {Barbara E Stranger and Alexandra C Nica and Matthew S Forrest and Antigone Dimas and Christine P Bird and Claude Beazley and Catherine E Ingle and Mark Dunning and Paul Flicek and Daphne Koller and Stephen Montgomery and Simon Tavar{\'e} and Panos Deloukas and Emmanouil T Dermitzakis}, 
journal = {Nat Genet},
title = {Population genomics of human gene expression},
number = {10},
pages = {1217--1224},
volume = {39},
year = {2007},
month = {Oct},
date-added = {2009-06-01 12:30:34 -0400},
date-modified = {2009-07-22 16:12:34 -0400},
doi = {10.1038/ng2142},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2007/Stranger/Nat%20Genet%202007%20Stranger.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p114},
read = {Yes},
rating = {0}
}

@article{Cooper:2010p3191,
author = {David N Cooper}, 
journal = {Hum Genomics},
title = {Functional intronic polymorphisms: Buried treasure awaiting discovery within our genes},
number = {5},
pages = {284--8},
volume = {4},
year = {2010},
month = {Jun},
language = {eng},
keywords = {Polymorphism: Genetic, RNA Splice Sites, Introns, Genes, Mutation, Humans, Polymorphism: Single Nucleotide, Base Pairing}, 
date-added = {2011-05-16 16:00:50 -0400},
date-modified = {2011-05-16 16:00:50 -0400},
pii = {0775233071626844},
pmid = {20650817},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2010/Cooper/Hum%20Genomics%202010%20Cooper.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p3191},
read = {Yes},
rating = {0}
}

@article{Cheung:2010p3036,
author = {Vivian G Cheung and Renuka R Nayak and Isabel Xiaorong Wang and Susannah Elwyn and Sarah M Cousins and Michael Morley and Richard S Spielman}, 
journal = {PLoS Biol},
title = {Polymorphic cis- and trans-regulation of human gene expression},
abstract = {Expression levels of human genes vary extensively among individuals. This variation facilitates analyses of expression levels as quantitative phenotypes in genetic studies where the entire genome can be scanned for regulators without prior knowledge of the regulatory mechanisms, thus enabling the identification of unknown regulatory relationships. Here, we carried out such genetic analyses with a large sample size and identified cis- and trans-acting polymorphic regulators for about 1,000 human genes. We validated the cis-acting regulators by demonstrating differential allelic expression with sequencing of transcriptomes (RNA-Seq) and the trans-regulators by gene knockdown, metabolic assays, and chromosome conformation capture analysis. The majority of the regulators act in trans to the target (regulated) genes. Most of these trans-regulators were not known to play a role in gene expression regulation. The identification of these regulators enabled the characterization of polymorphic regulation of human gene expression at a resolution that was unattainable in the past.},
affiliation = {Howard Hughes Medical Institute, Philadelphia, Pennsylvania, USA. vcheung@mail.med.upenn.edu},
number = {9},
volume = {8},
year = {2010},
month = {Jan},
language = {eng},
keywords = {Alleles, Humans, Gene Expression Regulation, Genetic Linkage, Polymorphism: Genetic}, 
date-added = {2011-05-16 12:33:35 -0400},
date-modified = {2011-05-16 12:50:19 -0400},
doi = {10.1371/journal.pbio.1000480},
pmid = {20856902},
URL = {http://www.plosbiology.org/article/info%253Adoi%252F10.1371%252Fjournal.pbio.1000480},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2010/Cheung/PLoS%20Biol%202010%20Cheung-1.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p3036},
read = {Yes},
rating = {0}
}

@article{Majewski:2011p3139,
author = {Jacek Majewski and Tomi Pastinen}, 
journal = {Trends Genet},
title = {The study of eQTL variations by RNA-seq: from SNPs to phenotypes},
abstract = {Common DNA variants alter the expression levels and patterns of many human genes. Loci responsible for this genetic control are known as expression quantitative trait loci (eQTLs). The resulting variation of gene expression across individuals has been postulated to be a determinant of phenotypic variation and susceptibility to complex disease. In the past, the application of expression microarray and genetic variation data to study populations enabled the rapid identification of eQTLs in model organisms and humans. Now, a new technology promises to revolutionize the field. Massively parallel RNA sequencing (RNA-seq) provides unprecedented resolution, allowing us to accurately monitor not only the expression output of each genomic locus but also reconstruct and quantify alternatively spliced transcripts. RNA-seq also provides new insights into the regulatory mechanisms underlying eQTLs. Here, we discuss the major advances introduced by RNA-seq and summarize current progress towards understanding the role of eQTLs in determining human phenotypic diversity.},
affiliation = {Department of Human Genetics, McGill University and Genome Quebec Innovation Centre, 740 Dr. Penfield Avenue, Rm 7210, Montreal, Quebec, H3A 1A4, Canada. jacek.majewski@mcgill.ca},
number = {2},
pages = {72--9},
volume = {27},
year = {2011},
month = {Feb},
language = {eng},
keywords = {Phenotype, Quantitative Trait Loci, Polymorphism: Single Nucleotide, Transcription: Genetic, Gene Expression Regulation, Animals, Sequence Analysis: RNA, Humans}, 
date-added = {2011-05-16 13:05:06 -0400},
date-modified = {2011-05-16 13:05:06 -0400},
doi = {10.1016/j.tig.2010.10.006},
pii = {S0168-9525(10)00212-X},
pmid = {21122937},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2011/Majewski/Trends%20Genet%202011%20Majewski.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p3139},
read = {Yes},
rating = {0}
}

@article{Veyrieras:2008p1582,
author = {Jean-Baptiste Veyrieras and Sridhar Kudaravalli and Su Yeon Kim and Emmanouil T Dermitzakis and Yoav Gilad and Matthew Stephens and Jonathan K Pritchard}, 
journal = {PLoS Genet},
title = {High-resolution mapping of expression-QTLs yields insight into human gene regulation},
abstract = {Recent studies of the HapMap lymphoblastoid cell lines have identified large numbers of quantitative trait loci for gene expression (eQTLs). Reanalyzing these data using a novel Bayesian hierarchical model, we were able to create a surprisingly high-resolution map of the typical locations of sites that affect mRNA levels in cis. Strikingly, we found a strong enrichment of eQTLs in the 250 bp just upstream of the transcription end site (TES), in addition to an enrichment around the transcription start site (TSS). Most eQTLs lie either within genes or close to genes; for example, we estimate that only 5% of eQTLs lie more than 20 kb upstream of the TSS. After controlling for position effects, SNPs in exons are approximately 2-fold more likely than SNPs in introns to be eQTLs. Our results suggest an important role for mRNA stability in determining steady-state mRNA levels, and highlight the potential of eQTL mapping as a high-resolution tool for studying the determinants of gene regulation.},
affiliation = {Department of Human Genetics, The University of Chicago, Chicago, IL, USA. jb.veyrieras@gmail.com},
number = {10},
pages = {e1000214},
volume = {4},
year = {2008},
month = {Oct},
language = {eng},
keywords = {Bayes Theorem, Polymorphism: Single Nucleotide, Databases: Genetic, Transcription Initiation Site, Models: Genetic, Genome: Human, Terminator Regions: Genetic, RNA: Messenger, RNA Stability, Gene Expression Regulation, Genetic Complementation Test, Introns, Humans, Chromosome Mapping, Quantitative Trait Loci}, 
date-added = {2010-01-29 04:40:30 -0500},
date-modified = {2010-01-29 04:40:30 -0500},
doi = {10.1371/journal.pgen.1000214},
pmid = {18846210},
URL = {http://www.plosgenetics.org/article/info%253Adoi%252F10.1371%252Fjournal.pgen.1000214},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2008/Veyrieras/PLoS%20Genet%202008%20Veyrieras-1.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p1582},
read = {Yes},
rating = {0}
}


%% This BibTeX bibliography file in UTF-8 format was created using Papers.
%% http://mekentosj.com/papers/

@article{Bourgon:2010p1763,
author = {Richard Bourgon and Robert Gentleman and Wolfgang Huber}, 
journal = {Proc Natl Acad Sci USA},
title = {Independent filtering increases detection power for high-throughput experiments},
abstract = {With high-dimensional data, variable-by-variable statistical testing is often used to select variables whose behavior differs across conditions. Such an approach requires adjustment for multiple testing, which can result in low statistical power. A two-stage approach that first filters variables by a criterion independent of the test statistic, and then only tests variables which pass the filter, can provide higher power. We show that use of some filter/test statistics pairs presented in the literature may, however, lead to loss of type I error control. We describe other pairs which avoid this problem. In an application to microarray data, we found that gene-by-gene filtering by overall variance followed by a t-test increased the number of discoveries by 50%. We also show that this particular statistic pair induces a lower bound on fold-change among the set of discoveries. Independent filtering-using filter/test pairs that are independent under the null hypothesis but correlated under the alternative-is a general approach that can substantially increase the efficiency of experiments.},
affiliation = {European Bioinformatics Institute, Cambridge CB10 1SD, UK.},
number = {21},
pages = {9546--51},
volume = {107},
year = {2010},
month = {May},
language = {eng},
keywords = {Algorithms, Computational Biology, Biometry, Models: Genetic}, 
date-added = {2010-07-09 16:24:45 -0400},
date-modified = {2010-07-09 16:24:45 -0400},
doi = {10.1073/pnas.0914005107},
pii = {0914005107},
pmid = {20460310},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2010/Bourgon/Proc%20Natl%20Acad%20Sci%20USA%202010%20Bourgon.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p1763},
read = {Yes},
rating = {0}
}


%% This BibTeX bibliography file in UTF-8 format was created using Papers.
%% http://mekentosj.com/papers/

@article{Buzkova:2011p3368,
author = {Petra B{\r u}{\v z}kov{\'a} and Thomas Lumley and Kenneth Rice}, 
journal = {Ann Hum Genet},
title = {Permutation and parametric bootstrap tests for gene-gene and gene-environment interactions},
abstract = {Permutation tests are widely used in genomic research as a straightforward way to obtain reliable statistical inference without making strong distributional assumptions. However, in this paper we show that in genetic association studies it is not typically possible to construct exact permutation tests of gene-gene or gene-environment interaction hypotheses. We describe an alternative to the permutation approach in testing for interaction, a parametric bootstrap approach. Using simulations, we compare the finite-sample properties of a few often-used permutation tests and the parametric bootstrap. We consider interactions of an exposure with single and multiple polymorphisms. Finally, we address when permutation tests of interaction will be approximately valid in large samples for specific test statistics.},
affiliation = {Department of Biostatistics, University of Washington, Seattle, USA. buzkova@u.washington.edu},
number = {1},
pages = {36--45},
volume = {75},
year = {2011},
month = {Jan},
language = {eng},
keywords = {Animals, Humans, Polymorphism: Genetic, Models: Genetic, Epistasis: Genetic, Models: Statistical, Computer Simulation, Genetic Association Studies, Environment}, 
date-added = {2011-09-21 14:56:38 -0400},
date-modified = {2011-09-21 14:56:38 -0400},
doi = {10.1111/j.1469-1809.2010.00572.x},
pii = {AHG572},
pmid = {20384625},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2011/B%C5%AF%C5%BEkov%C3%A1/Ann%20Hum%20Genet%202011%20B%C5%AF%C5%BEkov%C3%A1.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p3368},
read = {Yes},
rating = {0}
}


%% This BibTeX bibliography file in UTF-8 format was created using Papers.
%% http://mekentosj.com/papers/

@article{Leek:2007p1723,
author = {Jeffrey T Leek and John D Storey}, 
journal = {PLoS Genet},
title = {Capturing heterogeneity in gene expression studies by surrogate variable analysis},
abstract = {It has unambiguously been shown that genetic, environmental, demographic, and technical factors may have substantial effects on gene expression levels. In addition to the measured variable(s) of interest, there will tend to be sources of signal due to factors that are unknown, unmeasured, or too complicated to capture through simple models. We show that failing to incorporate these sources of heterogeneity into an analysis can have widespread and detrimental effects on the study. Not only can this reduce power or induce unwanted dependence across genes, but it can also introduce sources of spurious signal to many genes. This phenomenon is true even for well-designed, randomized studies. We introduce "surrogate variable analysis" (SVA) to overcome the problems caused by heterogeneity in expression studies. SVA can be applied in conjunction with standard analysis techniques to accurately capture the relationship between expression and any modeled variables of interest. We apply SVA to disease class, time course, and genetics of gene expression studies. We show that SVA increases the biological accuracy and reproducibility of analyses in genome-wide expression studies.},
affiliation = {Department of Biostatistics, University of Washington, Seattle, Washington, USA.},
number = {9},
pages = {1724--35},
volume = {3},
year = {2007},
month = {Sep},
language = {eng},
keywords = {Mutation, Breast Neoplasms, Genome: Human, Saccharomyces cerevisiae, Gene Expression, Time Factors, Linkage (Genetics), Algorithms, Genes: BRCA2, Oligonucleotide Array Sequence Analysis, Female, Linear Models, Genome: Fungal, Humans, Quantitative Trait: Heritable, Epigenesis: Genetic, Reproducibility of Results, Genes: BRCA1, Kidney, Data Interpretation: Statistical, Genetic Heterogeneity, Computer Simulation}, 
date-added = {2010-05-27 12:10:21 -0400},
date-modified = {2010-05-27 12:10:39 -0400},
doi = {10.1371/journal.pgen.0030161},
pii = {07-PLGE-RA-0237},
pmid = {17907809},
URL = {http://www.plosgenetics.org/article/info%253Adoi%252F10.1371%252Fjournal.pgen.0030161},
local-url = {file://localhost/Users/stvjc/Documents/Papers/2007/Leek/PLoS%20Genet%202007%20Leek.pdf},
uri = {papers://C760FBA3-C68E-4E3E-8645-15A5D6D0F91F/Paper/p1723},
read = {Yes},
rating = {0}
}

