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Alternative splicing is a process by which multiple messenger RNAs (mRNAs) can be generated by joining exons together in different combinations. This process is used to both increase protein diversity and to regulate gene expression (Nilsen and Graveley 2010). Approximately 95% of human genes contain introns and therefore have the potential to be alternatively spliced. Recent deep sequencing surveys of 10 human tissues found that nearly all (95%–98%) multi-exon human genes are alternatively spliced (Pan et al. 2008; Wang et al. 2008). Given the ubiquity of alternative splicing and the key roles it plays in the control of gene expression, it is important to develop a complete understanding of the mechanisms by which alternative splicing is regulated. Alternative splicing is most commonly controlled by RNA binding proteins that bind to sequence elements called enhancers and silencers (Nilsen and Graveley 2010). Splicing regulators bound to these enhancers or silencers are thought to either recruit or inhibit assembly or activity of spliceosomal components at nearby splice sites. The best-characterized splicing regulator proteins are the SR and hnRNP protein families. SR proteins primarily bind to enhancer sequences in exons where they activate adjacent splice sites, while hnRNPs have mostly been shown to suppress splicing when bound to intronic silencers. In addition to SR and hnRNPs proteins, several other splicing regulators have been identified that function in a tissue specific manner (Chen and Manley 2009). The mammalian proteins NOVA1 and NOVA2 (collectively named here as NOVA) are perhaps the best-characterized splicing regulators to date. NOVA1/2 encode RNA binding proteins with three KH-domains that recognize clusters of YCAY repeats. Over the past decade, several hundred splicing events have been shown to be regulated by NOVA1/2 (Ule et al. 2005, 2006; Licatalosi et al. 2008). A comparison of the locations of the NOVA1/2 binding sites with NOVA-regulated splicing events has revealed a stereotypical “RNA map” for NOVA1/2. Specifically, regions upstream of exons where NOVA inhibits splicing and regions downstream from exons where NOVA activates splicing were enriched with NOVA binding sites (Ule et al. 2006; Licatalosi et al. 2008). Similar “RNA maps” that link the position of binding sites to typical activities of the regulatory proteins have also been developed for mammalian FOX1/2 (Zhang et al. 2008; Yeo et al. 2009), PTB (Xue et al. 2009), and four D. melanogaster hnRNP proteins (Blanchette et al. 2009). Such maps, splicing expression data, and RNA sequence motifs have recently been used to predict regulated tissue-specific splicing changes in mouse, strongly supporting the existence of a splicing code (Wang and Burge 2008; Barash et al. 2010; Zhang et al. 2010), a decipherable sequence-based information system that dictates the splicing pattern of a given pre-mRNA under a specific condition. Though considerable progress has been made, interpreting this code remains a formidable task in the field. In particular, it is unclear how the mouse splicing code can be applied to different species, especially distantly related organisms such as Drosophila. Moreover, the extent to which the RNA maps of individual splicing regulators are static or plastic throughout evolution has been unknown. We were interested in exploring the conservation of the splicing code between distantly related organisms. As a first step in this process, we sought to generate an RNA map of Pasilla (PS) (Seshaiah et al. 2001), the D. melanogaster ortholog of NOVA1/2. To identify PS-regulated exons, we used RNA-seq (Wold and Myers 2008) to identify splicing events that changed upon depletion of PS by RNAi. We conclude that the RNA map of PS and NOVA1/2 is highly conserved between mammals and insects.

Analysis of Hi-C data has shown that the genome can be divided into two compartments called A/B compartments. These compartments are cell-type specific and are associated with open and closed chromatin. We show that A/B compartments can be reliably estimated using epigenetic data from several different platforms, the Illumina 450k DNA methylation microarray, DNase hypersensitivity sequencing, single-cell ATAC sequencing and single-cell whole-genome bisulfite sequencing. We do this by exploiting the fact that the structure of long range correlations differs between open and closed compartments. This work makes A/B compartments readily available in a wide variety of cell types, including many human cancers.

Background Aging and sun exposure are the leading causes of skin cancer. It has been shown that epigenetic changes, such as DNA methylation, are well established mechanisms for cancer, and also have emerging roles in aging and common disease. Here, we directly ask whether DNA methylation is altered following skin aging and/or chronic sun exposure in humans. Results We compare epidermis and dermis of both sun-protected and sun-exposed skin derived from younger subjects (under 35 years old) and older subjects (over 60 years old), using the Infinium HumanMethylation450 array and whole genome bisulfite sequencing. We observe large blocks of the genome that are hypomethylated in older, sun-exposed epidermal samples, with the degree of hypomethylation associated with clinical measures of photo-aging. We replicate these findings using whole genome bisulfite sequencing, comparing epidermis from an additional set of younger and older subjects. These blocks largely overlap known hypomethylated blocks in colon cancer and we observe that these same regions are similarly hypomethylated in squamous cell carcinoma samples. Conclusions These data implicate large scale epigenomic change in mediating the effects of environmental damage with photo-aging. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0644-y) contains supplementary material, which is available to authorized users.

DNA methylation is thought to be robust to environmental perturbations on a short time scale. Here, we challenge that view by demonstrating that the infection of human dendritic cells (DCs) with a pathogenic bacteria is associated with rapid changes in methylation at thousands of loci. Infection-induced changes in methylation occur primarily at distal enhancer elements, including those associated with the activation of key immune transcription factors and genes involved in the crosstalk between DCs and adaptive immunity. Active demethylation is associated with extensive epigenetic remodeling and is strongly predictive of changes in the expression levels of nearby genes. Collectively, our observations show that rapid changes in methylation play a previously unappreciated role in regulating the transcriptional response of DCs to infection.

Food allergy (FA) affects 2%-10% of US children and is a growing clinical and public health problem. Here we conduct the first genome-wide association study of well-defined FA, including specific subtypes (peanut, milk and egg) in 2,759 US participants (1,315 children and 1,444 parents) from the Chicago Food Allergy Study, and identify peanut allergy (PA)-specific loci in the HLA-DR and -DQ gene region at 6p21.32, tagged by rs7192 (P=5.5 × 10(-8)) and rs9275596 (P=6.8 × 10(-10)), in 2,197 participants of European ancestry. We replicate these associations in an independent sample of European ancestry. These associations are further supported by meta-analyses across the discovery and replication samples. Both single-nucleotide polymorphisms (SNPs) are associated with differential DNA methylation levels at multiple CpG sites (P

The present study was undertaken to assess the impact of reproductive behavior on the social class gradient in breast cancer occurrence in Denmark. Objectives were to study whether the gradient across socioeconomic groups could be explained by fertility differences, whether the gradient across educational groups could be explained by fertility differences and whether the effect of socioeconomic group on breast cancer incidence and mortality could be explained by education and vice versa. We studied 674,084 women aged 20–39 at the census on 9 November 1970 for whom we had complete data on fertility history. The cohort was followed up for breast cancer incidence and mortality until 8 November 1998. Fertility history varied considerably across socioeconomic group, where 38% of the academics were childless at the age of 30, in contrast to only 8% of women in agriculture. The academics had the highest risk of breast cancer and women in agriculture had the lowest risk. For incidence, the gradient in the relative risks was 1.74, which changed to 1.49 when fertility history was incorporated and to 1.29 when school education was also taken into account. For school education, women with ≥ 12 years of schooling had the highest risk and women with ≤ 7 years of schooling had the lowest risk. For incidence, the gradient in the relative risk was 1.38, which changed to 1.26 when fertility history was incorporated and to 1.22 when socioeconomic group was also taken into account. © 2004 Wiley-Liss, Inc.

In honeybee societies, distinct caste phenotypes are created from the same genotype, suggesting a role for epigenetics in deriving these behaviorally different phenotypes. We found no differences in DNA methylation between irreversible worker and queen castes, but substantial differences between nurses and forager subcastes. Reverting foragers back to nurses reestablished methylation levels for a majority of genes and provides, to the best of our knowledge, the first evidence in any organism of reversible epigenetic changes associated with behavior.

Kabuki syndrome is caused by haploinsufficiency for either of two genes that promote the opening of chromatin. If an imbalance between open and closed chromatin is central to the pathogenesis of Kabuki syndrome, agents that promote chromatin opening might have therapeutic potential. We have characterized a mouse model of Kabuki syndrome with a heterozygous deletion in the gene encoding the lysine-specific methyltransferase 2D (Kmt2d), leading to impairment of methyltransferase function. In vitro reporter alleles demonstrated a reduction in histone 4 acetylation and histone 3 lysine 4 trimethylation (H3K4me3) activity in mouse embryonic fibroblasts from Kmt2d(+/βGeo) mice. These activities were normalized in response to AR-42, a histone deacetylase inhibitor. In vivo, deficiency of H3K4me3 in the dentate gyrus granule cell layer of Kmt2d(+/βGeo) mice correlated with reduced neurogenesis and hippocampal memory defects. These abnormalities improved upon postnatal treatment with AR-42. Our work suggests that a reversible deficiency in postnatal neurogenesis underlies intellectual disability in Kabuki syndrome.

We present shinyMethyl, a Bioconductor package for interactive quality control of DNA methylation data from Illumina 450k arrays. The package summarizes 450k experiments into small exportable R objects from which an interactive interface is launched. Reactive plots allow fast and intuitive quality control assessment of the samples. In addition, exploration of the phenotypic associations is possible through coloring and principal component analysis. Altogether, the package makes it easy to perform quality assessment of large-scale methylation datasets, such as epigenome-wide association studies or the datasets available through The Cancer Genome Atlas portal. The shinyMethyl package is implemented in R and available via Bioconductor. Its development repository is at https://github.com/jfortin1/shinyMethyl.

Motivation: The recently released Infinium HumanMethylation450 array (the ‘450k’ array) provides a high-throughput assay to quantify DNA methylation (DNAm) at ∼450 000 loci across a range of genomic features. Although less comprehensive than high-throughput sequencing-based techniques, this product is more cost-effective and promises to be the most widely used DNAm high-throughput measurement technology over the next several years. Results: Here we describe a suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data. The software is structured to easily adapt to future versions of the technology. We include methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale. We show how our software provides a powerful and flexible development platform for future methods. We also illustrate how our methods empower the technology to make discoveries previously thought to be possible only with sequencing-based methods. Availability and implementation: http://bioconductor.org/packages/release/bioc/html/minfi.html. Contact: khansen@jhsph.edu; rafa@jimmy.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online.

RNA-sequencing (RNA-seq) is a flexible technology for measuring genome-wide expression that is rapidly replacing microarrays as costs become comparable. Current differential expression analysis methods for RNA-seq data fall into two broad classes: (1) methods that quantify expression within the boundaries of genes previously published in databases and (2) methods that attempt to reconstruct full length RNA transcripts. The first class cannot discover differential expression outside of previously known genes. While the second approach does possess discovery capabilities, statistical analysis of differential expression is complicated by the ambiguity and variability incurred while assembling transcripts and estimating their abundances. Here, we propose a novel method that first identifies differentially expressed regions (DERs) of interest by assessing differential expression at each base of the genome. The method then segments the genome into regions comprised of bases showing similar differential expression signal, and then assigns a measure of statistical significance to each region. Optionally, DERs can be annotated using a reference database of genomic features. We compare our approach with leading competitors from both current classes of differential expression methods and highlight the strengths and weaknesses of each. A software implementation of our method is available on github (https://github.com/alyssafrazee/derfinder).

Whole genome bisulfite sequencing (WGBS) allows genome-wide DNA methylation profiling but the associated high sequencing costs continue to limit its widespread application. We utilized several high coverage reference data sets to experimentally determine minimal sequencing requirements. Here, we present data derived recommendations for minimum sequencing depth for WGBS libraries, highlight what is gained with increasing coverage and discuss the trade off between sequencing depth and number of assayed replicates.

The IDAT file format is used to store BeadArray data from the myriad of genomewide profiling platforms on offer from Illumina Inc. This proprietary format is output directly from the scanner and stores summary intensities for each probe-type on an array in a compact manner. A lack of open source tools to process IDAT files has hampered their uptake by the research community beyond the standard step of using the vendor’s software to extract the data they contain in a human readable text format. To fill this void, we have developed the illuminaio package that parses IDAT files from any BeadArray platform, including the decryption of files from Illumina’s gene expression arrays. illuminaio provides the first open-source package for this task, and will promote wider uptake of the IDAT format as a standard for sharing Illumina BeadArray data in public databases, in the same way that the CEL file serves as the standard for the Affymetrix platform.

Bioconductor (bioconductor.org) is a rich source of software and know-how for the integrative analysis of genomic data. The Bioconductor channel in F1000Research provides a forum for task-oriented workflows that each cover a solution to a current, important problem in genome-scale data analysis from end to end, invoking resources from several packages by different authors, often combining multiple `omics data types, and demonstrating integrative analysis and modelling techniques.

Variation in the social environment is a fundamental component of many vertebrate societies. In humans and other primates, adverse social environments often translate into lasting physiological costs. The biological mechanisms associated with these effects are therefore of great interest, both for understanding the evolutionary impacts of social behavior and in the context of human health. However, large gaps remain in our understanding of the mechanisms that mediate these effects at the molecular level. Here we addressed these questions by leveraging the power of an experimental system that consisted of 10 social groups of female macaques, in which each individual's social status (i.e., dominance rank) could be experimentally controlled. Using this paradigm, we show that dominance rank results in a widespread, yet plastic, imprint on gene regulation, such that peripheral blood mononuclear cell gene expression data alone predict social status with 80% accuracy. We investigated the mechanistic basis of these effects using cell type-specific gene expression profiling and glucocorticoid resistance assays, which together contributed to rank effects on gene expression levels for 694 (70%) of the 987 rank-related genes. We also explored the possible contribution of DNA methylation levels to these effects, and identified global associations between dominance rank and methylation profiles that suggest epigenetic flexibility in response to status-related behavioral cues. Together, these results illuminate the importance of the molecular response to social conditions, particularly in the immune system, and demonstrate a key role for gene regulation in linking the social environment to individual physiology.

As sequencing throughput approaches dozens of gigabases per day, there is a growing need for efficient software for analysis of transcriptome sequencing (RNA-Seq) data. Myrna is a cloud-computing pipeline for calculating differential gene expression in large RNA-Seq datasets. We apply Myrna to the analysis of publicly available data sets and assess the goodness of fit of standard statistical models. Myrna is available from http://bowtie-bio.sf.net/myrna.

Alternative mRNA splicing adds a layer of regulation to the expression of thousands of genes in Drosophila melanogaster. Not all alternative splicing results in functional protein; it can also yield mRNA isoforms with premature stop codons that are degraded by the nonsense-mediated mRNA decay (NMD) pathway. This coupling of alternative splicing and NMD provides a mechanism for gene regulation that is highly conserved in mammals. NMD is also active in Drosophila, but its effect on the repertoire of alternative splice forms has been unknown, as has the mechanism by which it recognizes targets. Here, we have employed a custom splicing-sensitive microarray to globally measure the effect of alternative mRNA processing and NMD on Drosophila gene expression. We have developed a new algorithm to infer the expression change of each mRNA isoform of a gene based on the microarray measurements. This method is of general utility for interpreting splicing-sensitive microarrays and high-throughput sequence data. Using this approach, we have identified a high-confidence set of 45 genes where NMD has a differential effect on distinct alternative isoforms, including numerous RNA–binding and ribosomal proteins. Coupled alternative splicing and NMD decrease expression of these genes, which may in turn have a downstream effect on expression of other genes. The NMD–affected genes are enriched for roles in translation and mitosis, perhaps underlying the previously observed role of NMD factors in cell cycle progression. Our results have general implications for understanding the NMD mechanism in fly. Most notably, we found that the NMD–target mRNAs had significantly longer 3′ untranslated regions (UTRs) than the nontarget isoforms of the same genes, supporting a role for 3′ UTR length in the recognition of NMD targets in fly., Author Summary A gene can be processed into multiple mRNAs through alternative splicing. Alternative splicing increases the number of proteins encoded by the genome, but not all alternative mRNAs produce protein. Instead, some are degraded by nonsense-mediated mRNA decay (NMD), a surveillance system that was originally identified as a means of clearing the cell of mRNAs with nonsense, or stop codon, mutations. Alternative splicing that introduces early stop codons will lead to NMD, offering a way for the cell to down-regulate gene expression after a gene has been transcribed. In this paper, we have developed a new analysis method to study the combined effect of alternative splicing and degradation in the fruit fly Drosophila melanogaster using microarrays. We have found a stringently defined set of 45 genes that can be spliced either into an mRNA that encodes a protein or into an mRNA that is degraded by NMD, down-regulating the overall gene expression. The affected genes include a number that are central to the cell's regulatory processes, including translation, RNA splicing, and cell cycle progression. Our results also help shed light on how NMD determines whether a stop codon is premature, and thus whether to target an mRNA for degradation.

A complete description of the transcriptome of an organism is crucial for a comprehensive understanding of how it functions and how its transcriptional networks are controlled, and may provide insights into the organism's evolution. Despite the status of Saccharomyces cerevisiae as arguably the most well-studied model eukaryote, we still do not have a full catalog or understanding of all its genes. In order to interrogate the transcriptome of S. cerevisiae for low abundance or rapidly turned over transcripts, we deleted elements of the RNA degradation machinery with the goal of preferentially increasing the relative abundance of such transcripts. We then used high-resolution tiling microarrays and ultra high–throughput sequencing (UHTS) to identify, map, and validate unannotated transcripts that are more abundant in the RNA degradation mutants relative to wild-type cells. We identified 365 currently unannotated transcripts, the majority presumably representing low abundance or short-lived RNAs, of which 185 are previously unknown and unique to this study. It is likely that many of these are cryptic unstable transcripts (CUTs), which are rapidly degraded and whose function(s) within the cell are still unclear, while others may be novel functional transcripts. Of the 185 transcripts we identified as novel to our study, greater than 80 percent come from regions of the genome that have lower conservation scores amongst closely related yeast species than 85 percent of the verified ORFs in S. cerevisiae. Such regions of the genome have typically been less well-studied, and by definition transcripts from these regions will distinguish S. cerevisiae from these closely related species., Author Summary The budding yeast Saccharomyces cerevisiae, because of the relative ease of its genetic manipulation and its ease of handling in the laboratory, has long served as a model on which studies in higher organisms have been based. To more fully understand how eukaryotic cells express their genomes, we sought to identify RNA species that are transcribed at very low levels or that are rapidly degraded. We created mutants deficient in the ability to degrade RNA, with the expectation that this would increase the relative abundance of such RNAs, and then used high-resolution microarrays and sequencing technologies to locate and identify from where these RNAs are transcribed. Using this approach, we have identified 365 transcripts that do not appear in the most current list of annotated S. cerevisiae RNA transcripts; of these, 185 are unique to our study. Many of these novel transcripts derive from regions of the genome that are poorly conserved between S. cerevisiae and other closely related yeast species, suggesting that these RNAs may play an important role in the divergent microevolution of S. cerevisiae.

Udgivelsesdato: 2007-Aug-6 BACKGROUND: Computer use is one of the commonest work place exposures in modern society. An adverse effect on musculoskeletal outcomes has been claimed for decades, mainly on the basis of self reports of exposure. The purpose of this study was to assess the risk of neck and shoulder pain associated with objectively recorded professional computer use. METHODS: A computer programme was used to collect data on mouse and keyboard usage and weekly reports of neck and shoulder pain for up to 52 weeks among 2146 technical assistants. Questionnaires were also completed at baseline and at 12 months. There were three outcome measures for each region 1) acute pain, measured as weekly pain, 2) prolonged pain, defined as participants with no or minor pain in the neck and shoulder region over 4 consecutive weeks followed by 3 consecutive weeks with a high pain score, and 3) chronic pain was defined as participants who reported pain or discomfort lasting more than 30 days and had experienced at least 'quite a lot of trouble' during the past 12 months. RESULTS: Risk for acute neck pain and shoulder pain increased linearly by 4% and 10% respectively for each quartile increase in weekly mouse usage time. Mouse and keyboard usage time did not predict the onset of prolonged or chronic pain in the neck or shoulder. Women had higher risks for neck and shoulder pain. Number of keystrokes and mouse clicks, length of the average activity period, and micro pauses did not influence reports of acute or prolonged pain. A few psychosocial factors predicted the risk of prolonged pain. CONCLUSIONS: From the NUDATA-study we can conclude that most computer workers have no or minor neck and shoulder pain, few experience prolonged pain, and even fewer, chronic neck and shoulder pain.

Udgivelsesdato: 2004-Dec-15 A possible detrimental paternal age effect on offspring health due to mutations of paternal origin should be reflected in an association between paternal age and fetal loss. The authors used data from a prospective study of 23,821 pregnant women recruited consecutively to the Danish National Birth Cohort from 1997 to 1999 to assess the association between paternal age and fetal death. Fathers of the pregnancies were identified by record linkage to population registers. The paternal age-related risks of fetal death and its components, early and late fetal loss, were estimated using survival analysis. Pregnancies fathered by a man aged 50 or more years (n = 124) had almost twice the risk of ending in a fetal loss compared with pregnancies with younger fathers (hazard ratio = 1.88, 95% confidence interval: 0.93, 3.82), after adjustment for maternal age, reproductive history, and maternal lifestyle during pregnancy. Various approaches to adjustment for potential residual confounding of the relation by maternal age did not affect the relative risk estimates. The paternal age-related risk of late fetal death was higher than the risk of early fetal death and started to increase from the age of 45 years. It should, however, be interpreted cautiously because of the restricted number of fetal deaths.

RNA sequencing has generated much excitement for the advantages offered over microarrays. This excitement has led to a barrage of publications discounting the importance of biological variability; as microarray publications did in the 1990s. By comparing microarray and sequencing data, we demonstrate that expression measurements exhibit biological variability across individuals irrespective of measurement technology. Our analysis suggests RNA-sequencing experiments designed to estimate biological variability are more likely to produce reproducible results.

DNA methylation is an important epigenetic modification involved in gene regulation, which can now be measured using whole-genome bisulfite sequencing. However, cost, complexity of the data, and lack of comprehensive analytical tools are major challenges that keep this technology from becoming widely applied. Here we present BSmooth, an alignment, quality control and analysis pipeline that provides accurate and precise results even with low coverage data, appropriately handling biological replicates. BSmooth is open source software, and can be downloaded from http://rafalab.jhsph.edu/bsmooth.

Generation of cDNA using random hexamer priming induces biases in the nucleotide composition at the beginning of transcriptome sequencing reads from the Illumina Genome Analyzer. The bias is independent of organism and laboratory and impacts the uniformity of the reads along the transcriptome. We provide a read count reweighting scheme, based on the nucleotide frequencies of the reads, that mitigates the impact of the bias.

Background: Modern epidemiology increasingly uses data on families. The authors constructed an extended fertility database for women born in Denmark from 1930 onwards by supplementing the existing Fertility Database with household data from the 1970 census. Methods: A fertility history was constructed for all women participating in the 1970 census, but aiming for complete data only for women aged 20 - 39. The fertility history of these women prior to the 1970 census was constructed from the census data including 1,648,813 persons coded as children. An algorithm was used transforming household information into fertility history data by matching women and children according to family position. Children for whom the algorithm gave no match were searched for in the Fertility Database; children not found in the Fertility Database either were searched for manually. The fertility history after the 1970 census was retrieved from the Fertility Database. Results: Using data from the census 1970, 98.5% of the children were linked to a mother, and 99.6% of these links were estimated to be correct, corresponding to 98.1% of the children being linked correctly. In total, 964,720 children of women aged 20 - 39 in 1970 were identified, which was equivalent to 96.6% of the expected live-born children, and to 99.1% of the expected surviving children. Conclusion: Census household data proved to be an excellent data source for construction of fertility histories.

Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes., Phenotypic variation and diseases are influenced by factors such as genetic variants and gene expression. Here, Barbeira et al. develop S-PrediXcan to compute PrediXcan results using summary data, and investigate the effects of gene expression variation on human phenotypes in 44 GTEx tissues and >100 phenotypes.

We propose an extension to quantile normalization that removes unwanted technical variation using control probes. We adapt our algorithm, functional normalization, to the Illumina 450k methylation array and address the open problem of normalizing methylation data with global epigenetic changes, such as human cancers. Using data sets from The Cancer Genome Atlas and a large case–control study, we show that our algorithm outperforms all existing normalization methods with respect to replication of results between experiments, and yields robust results even in the presence of batch effects. Functional normalization can be applied to any microarray platform, provided suitable control probes are available. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0503-2) contains supplementary material, which is available to authorized users.