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1.
Background
The analysis of high-throughput data in biology is aided by integrative approaches such as gene-set analysis. Gene-sets can represent well-defined biological entities (e.g. metabolites) that interact in networks (e.g. metabolic networks), to exert their function within the cell. Data interpretation can benefit from incorporating the underlying network, but there are currently no optimal methods that link gene-set analysis and network structures.Results
Here we present Kiwi, a new tool that processes output data from gene-set analysis and integrates them with a network structure such that the inherent connectivity between gene-sets, i.e. not simply the gene overlap, becomes apparent. In two case studies, we demonstrate that standard gene-set analysis points at metabolites regulated in the interrogated condition. Nevertheless, only the integration of the interactions between these metabolites provides an extra layer of information that highlights how they are tightly connected in the metabolic network.Conclusions
Kiwi is a tool that enhances interpretability of high-throughput data. It allows the users not only to discover a list of significant entities or processes as in gene-set analysis, but also to visualize whether these entities or processes are isolated or connected by means of their biological interaction. Kiwi is available as a Python package at http://www.sysbio.se/kiwi and an online tool in the BioMet Toolbox at http://www.biomet-toolbox.org.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-014-0408-9) contains supplementary material, which is available to authorized users. 相似文献2.
Background
DAVID is the most popular tool for interpreting large lists of gene/proteins classically produced in high-throughput experiments. However, the use of DAVID website becomes difficult when analyzing multiple gene lists, for it does not provide an adequate visualization tool to show/compare multiple enrichment results in a concise and informative manner.Result
We implemented a new R-based graphical tool, BACA (Bubble chArt to Compare Annotations), which uses the DAVID web service for cross-comparing enrichment analysis results derived from multiple large gene lists. BACA is implemented in R and is freely available at the CRAN repository (http://cran.r-project.org/web/packages/BACA/).Conclusion
The package BACA allows R users to combine multiple annotation charts into one output graph by passing DAVID website.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-015-0477-4) contains supplementary material, which is available to authorized users. 相似文献3.
Background
Gene set analysis (GSA) methods test the association of sets of genes with phenotypes in gene expression microarray studies. While GSA methods on a single binary or categorical phenotype abounds, little attention has been paid to the case of a continuous phenotype, and there is no method to accommodate correlated multiple continuous phenotypes.Result
We propose here an extension of the linear combination test (LCT) to its new version for multiple continuous phenotypes, incorporating correlations among gene expressions of functionally related gene sets, as well as correlations among multiple phenotypes. Further, we extend our new method to its nonlinear version, referred as nonlinear combination test (NLCT), to test potential nonlinear association of gene sets with multiple phenotypes. Simulation study and a real microarray example demonstrate the practical aspects of the proposed methods.Conclusion
The proposed approaches are effective in controlling type I errors and powerful in testing associations between gene-sets and multiple continuous phenotypes. They are both computationally effective. Naively (univariately) analyzing a group of multiple correlated phenotypes could be dangerous. R-codes to perform LCT and NLCT for multiple continuous phenotypes are available at http://www.ualberta.ca/~yyasui/homepage.html.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2105-15-260) contains supplementary material, which is available to authorized users. 相似文献4.
5.
Background
Synthetic lethal genetic interaction analysis has been successfully applied to predicting the functions of genes and their pathway identities. In the context of synthetic lethal interaction data alone, the global similarity of synthetic lethal interaction patterns between two genes is used to predict gene function. With physical interaction data, such as protein-protein interactions, the enrichment of physical interactions within subsets of genes and the enrichment of synthetic lethal interactions between those subsets of genes are used as an indication of compensatory pathways.Result
In this paper, we propose a method of mapping genetically compensatory pathways from synthetic lethal interactions. Our method is designed to discover pairs of gene-sets in which synthetic lethal interactions are depleted among the genes in an individual set and where such gene-set pairs are connected by many synthetic lethal interactions. By its nature, our method could select compensatory pathway pairs that buffer the deleterious effect of the failure of either one, without the need of physical interaction data. By focusing on compensatory pathway pairs where genes in each individual pathway have a highly homogenous cellular function, we show that many cellular functions have genetically compensatory properties.Conclusion
We conclude that synthetic lethal interaction data are a powerful source to map genetically compensatory pathways, especially in systems lacking physical interaction information, and that the cellular function network contains abundant compensatory properties. 相似文献6.
Background
Large amounts of microarray expression data have been generated for the Apicomplexan parasite Toxoplasma gondii in an effort to identify genes critical for virulence or developmental transitions. However, researchers’ ability to analyze this data is limited by the large number of unannotated genes, including many that appear to be conserved hypothetical proteins restricted to Apicomplexa. Further, differential expression of individual genes is not always informative and often relies on investigators to draw big-picture inferences without the benefit of context. We hypothesized that customization of gene set enrichment analysis (GSEA) to T. gondii would enable us to rigorously test whether groups of genes serving a common biological function are co-regulated during the developmental transition to the latent bradyzoite form.Results
Using publicly available T. gondii expression microarray data, we created Toxoplasma gene sets related to bradyzoite differentiation, oocyst sporulation, and the cell cycle. We supplemented these with lists of genes derived from community annotation efforts that identified contents of the parasite-specific organelles, rhoptries, micronemes, dense granules, and the apicoplast. Finally, we created gene sets based on metabolic pathways annotated in the KEGG database and Gene Ontology terms associated with gene annotations available at http://www.toxodb.org. These gene sets were used to perform GSEA analysis using two sets of published T. gondii expression data that characterized T. gondii stress response and differentiation to the latent bradyzoite form.Conclusions
GSEA provides evidence that cell cycle regulation and bradyzoite differentiation are coupled. Δgcn5A mutants unable to induce bradyzoite-associated genes in response to alkaline stress have different patterns of cell cycle and bradyzoite gene expression from stressed wild-type parasites. Extracellular tachyzoites resemble a transitional state that differs in gene expression from both replicating intracellular tachyzoites and in vitro bradyzoites by expressing genes that are enriched in bradyzoites as well as genes that are associated with the G1 phase of the cell cycle. The gene sets we have created are readily modified to reflect ongoing research and will aid researchers’ ability to use a knowledge-based approach to data analysis facilitating the development of new insights into the intricate biology of Toxoplasma gondii.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-515) contains supplementary material, which is available to authorized users. 相似文献7.
Fei Gu Mark S. Doderer Yi-Wen Huang Juan C. Roa Paul J. Goodfellow E. Lynette Kizer Tim H. M. Huang Yidong Chen 《PloS one》2013,8(4)
Background
DNA methylation of promoter CpG islands is associated with gene suppression, and its unique genome-wide profiles have been linked to tumor progression. Coupled with high-throughput sequencing technologies, it can now efficiently determine genome-wide methylation profiles in cancer cells. Also, experimental and computational technologies make it possible to find the functional relationship between cancer-specific methylation patterns and their clinicopathological parameters.Methodology/Principal Findings
Cancer methylome system (CMS) is a web-based database application designed for the visualization, comparison and statistical analysis of human cancer-specific DNA methylation. Methylation intensities were obtained from MBDCap-sequencing, pre-processed and stored in the database. 191 patient samples (169 tumor and 22 normal specimen) and 41 breast cancer cell-lines are deposited in the database, comprising about 6.6 billion uniquely mapped sequence reads. This provides comprehensive and genome-wide epigenetic portraits of human breast cancer and endometrial cancer to date. Two views are proposed for users to better understand methylation structure at the genomic level or systemic methylation alteration at the gene level. In addition, a variety of annotation tracks are provided to cover genomic information. CMS includes important analytic functions for interpretation of methylation data, such as the detection of differentially methylated regions, statistical calculation of global methylation intensities, multiple gene sets of biologically significant categories, interactivity with UCSC via custom-track data. We also present examples of discoveries utilizing the framework.Conclusions/Significance
CMS provides visualization and analytic functions for cancer methylome datasets. A comprehensive collection of datasets, a variety of embedded analytic functions and extensive applications with biological and translational significance make this system powerful and unique in cancer methylation research. CMS is freely accessible at: http://cbbiweb.uthscsa.edu/KMethylomes/. 相似文献8.
Philippe Bardou Jér?me Mariette Frédéric Escudié Christophe Djemiel Christophe Klopp 《BMC bioinformatics》2014,15(1)
Background
Venn diagrams are commonly used to display list comparison. In biology, they are widely used to show the differences between gene lists originating from different differential analyses, for instance. They thus allow the comparison between different experimental conditions or between different methods. However, when the number of input lists exceeds four, the diagram becomes difficult to read. Alternative layouts and dynamic display features can improve its use and its readability.Results
jvenn is a new JavaScript library. It processes lists and produces Venn diagrams. It handles up to six input lists and presents results using classical or Edwards-Venn layouts. User interactions can be controlled and customized. Finally, jvenn can easily be embeded in a web page, allowing to have dynamic Venn diagrams.Conclusions
jvenn is an open source component for web environments helping scientists to analyze their data. The library package, which comes with full documentation and an example, is freely available at http://bioinfo.genotoul.fr/jvenn. 相似文献9.
10.
Sandrine Roisin Christine Laurent Olivier Denis Michèle Dramaix Claire Nonhoff Marie Hallin Baudouin Byl Marc J. Struelens 《PloS one》2014,9(5)
Design
Cluster randomised crossover trial with seven wards randomly allocated to intervention or control arm.Setting
Medical and surgical wards of a university hospital with active MRSA control programme.Participants
All patients hospitalized >48 h in study wards and screened for MRSA on admission and discharge Intervention: Rapid PCR-based screening test for MRSA compared with control screening test by enrichment culture using chromogenic agar.Objective
We determined the benefit of PCR-detection versus culture-based detection of MRSA colonisation upon patient admission on early implementation of isolation precautions and reduction of hospital transmission of MRSA.Main outcome
Cumulative rate of MRSA hospital acquisition of in patients screened negative on admission.Randomization
The sequential order of inclusion of study wards in each arm was randomised by assigning a number to each ward and using a computer generated list of random numbers.Findings
Of 3704 eligible patients, 67.8% were evaluable for the study. Compared with culture, PCR-screening reduced the median test reporting time from admission from 88 to 11 hours (p<0.001) and the median time from admission to isolation from 96 to 25 hours (p<0.001). MRSA acquisition was detected in 36 patients (3.2%) in the control arm and 34 (3.2%) in the intervention arm. The incidence density rate of hospital acquired MRSA was 2.82 and 2.57/1,000 exposed patient-days in the control and intervention arm, respectively (risk ratio 0.91 (95% confidence interval, 0.60–1.39). Poisson regression model adjusted for colonisation pressure, compliance with hand hygiene and antibiotic use indicated a RR 0.99 (95% CI, 0.69 to 1.44).Interpretation
Universal PCR screening for MRSA on admission to medical and surgical wards in an endemic setting shortened the time to implement isolation precautions but did not reduce nosocomial acquisition of MRSA.Trial registration
clinicaltrials.gov NCT00846105 相似文献11.
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Wendy T. M. Pots Peter A. M. Meulenbeek Martine M. Veehof Jorinde Klungers Ernst T. Bohlmeijer 《PloS one》2014,9(10)
Objective
Although there has been growing evidence for the efficacy of mindfulness-based cognitive therapy (MBCT) for different clinical populations, its effectiveness as a public mental health intervention has not been studied. The present study evaluates a community-based MBCT intervention for adults with mild to moderate depressive symptomatology in a large multi-site, pragmatic randomized controlled trial.Method
The participants with mild to moderate depressive symptomatology were recruited from the general population and randomized to the MBCT intervention (n = 76) or to a waiting list control group (n = 75). Participants completed measures before and after the intervention. Participants in the experimental condition also completed these measures at a 3-month follow-up.Results
In the experimental condition significant reductions in depression, anxiety, and experiential avoidance, and improvements in mindfulness and emotional- and psychological mental health were found, compared to the waiting list (effect sizes Cohen''s d = 0.31–0.56). These effects were sustained at the 3-month follow-up. The likelihood of a clinically significant change in depressive symptoms was significantly higher for the MBCT group [odds ratio (OR) 3.026, p<0.01 at post-treatment; NNT = 5.10].Discussion
MBCT as a public mental health intervention for adults with mild to moderate depressive symptoms seems effective and applicable in a natural setting.Trial Registration
Nederlands Trial Register NTR2096 相似文献14.
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Marion Ouedraogo Charles Bettembourg Anthony Bretaudeau Olivier Sallou Christian Diot Olivier Demeure Frédéric Lecerf 《PloS one》2012,7(11)
Background
There has been a surge in studies linking genome structure and gene expression, with special focus on duplicated genes. Although initially duplicated from the same sequence, duplicated genes can diverge strongly over evolution and take on different functions or regulated expression. However, information on the function and expression of duplicated genes remains sparse. Identifying groups of duplicated genes in different genomes and characterizing their expression and function would therefore be of great interest to the research community. The ‘Duplicated Genes Database’ (DGD) was developed for this purpose.Methodology
Nine species were included in the DGD. For each species, BLAST analyses were conducted on peptide sequences corresponding to the genes mapped on a same chromosome. Groups of duplicated genes were defined based on these pairwise BLAST comparisons and the genomic location of the genes. For each group, Pearson correlations between gene expression data and semantic similarities between functional GO annotations were also computed when the relevant information was available.Conclusions
The Duplicated Gene Database provides a list of co-localised and duplicated genes for several species with the available gene co-expression level and semantic similarity value of functional annotation. Adding these data to the groups of duplicated genes provides biological information that can prove useful to gene expression analyses. The Duplicated Gene Database can be freely accessed through the DGD website at http://dgd.genouest.org. 相似文献16.
17.
?zgün Babur Ugur Dogrusoz Merve ?ak?r Bülent Arman Aksoy Nikolaus Schultz Chris Sander Emek Demir 《BMC genomics》2014,15(1)
Background
Dynamic visual exploration of detailed pathway information can help researchers digest and interpret complex mechanisms and genomic datasets.Results
ChiBE is a free, open-source software tool for visualizing, querying, and analyzing human biological pathways in BioPAX format. The recently released version 2 can search for neighborhoods, paths between molecules, and common regulators/targets of molecules, on large integrated cellular networks in the Pathway Commons database as well as in local BioPAX models. Resulting networks can be automatically laid out for visualization using a graphically rich, process-centric notation. Profiling data from the cBioPortal for Cancer Genomics and expression data from the Gene Expression Omnibus can be overlaid on these networks.Conclusions
ChiBE’s new capabilities are organized around a genomics-oriented workflow and offer a unique comprehensive pathway analysis solution for genomics researchers. The software is freely available at http://code.google.com/p/chibe. 相似文献18.
19.
Pablo Moreno Stephan Beisken Bhavana Harsha Venkatesh Muthukrishnan Ilinca Tudose Adriano Dekker Stefanie Dornfeldt Franziska Taruttis Ivo Grosse Janna Hastings Steffen Neumann Christoph Steinbeck 《BMC bioinformatics》2015,16(1)
Background
Ontology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biological entities, enrichment analysis methods assess whether there is a significant over or under representation of entities for ontology classes. While many tools exist that run enrichment analysis for protein sets annotated with the Gene Ontology, there are only a few that can be used for small molecules enrichment analysis.Results
We describe BiNChE, an enrichment analysis tool for small molecules based on the ChEBI Ontology. BiNChE displays an interactive graph that can be exported as a high-resolution image or in network formats. The tool provides plain, weighted and fragment analysis based on either the ChEBI Role Ontology or the ChEBI Structural Ontology.Conclusions
BiNChE aids in the exploration of large sets of small molecules produced within Metabolomics or other Systems Biology research contexts. The open-source tool provides easy and highly interactive web access to enrichment analysis with the ChEBI ontology tool and is additionally available as a standalone library.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-015-0486-3) contains supplementary material, which is available to authorized users. 相似文献20.