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ErmineJ: Tool for functional analysis of gene expression data sets

BMC BIOINFORMATICS 2005年第1期6卷 1-8页

作者： Lee, HK Braynen, W Keshav, K Pavlidis, P Columbia Univ Columbia Genome Ctr New York NY 10032 USA Columbia Univ Dept Comp Sci New York NY 10025 USA Univ Arizona Dept Philosophy Tucson AZ 85721 USA

Background: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories. The most common method for such analysis uses the hypergeometric distribution (or a related technique) to look for "over-representation" of groups among genes selected as being differentially expressed or otherwise of interest based on a gene-by-gene analysis. However, this method suffers from some limitations, and biologist-friendly tools that implement alternatives have not been reported. Results: We introduce ErmineJ, a multiplatform user-friendly stand- alone software tool for the analysis of functionally-relevant sets of genes in the context of microarray gene expression data. ErmineJ implements multiple algorithms for gene set analysis, including over-representation and resampling-based methods that focus on gene scores or correlation of gene expression profiles. In addition to a graphical user interface, ErmineJ has a command line interface and an application programming interface that can be used to automate analyses. The graphical user interface includes tools for creating and modifying gene sets, visualizing the Gene Ontology as a table or tree, and visualizing gene expression data. ErmineJ comes with a complete user manual, and is open-source software licensed under the Gnu Public License. Conclusion: The availability of multiple analysis algorithms, together with a rich feature set and simple graphical interface, should make ErmineJ a useful addition to the biologist's informatics toolbox. ErmineJ is available from http://***.

关键词： Gene Ontology Application Programming Interface annotation file Gene Score Command Line Interface

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Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data

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BMC BIOINFORMATICS 2007年第1期8卷 1-15页

作者： Yu, Hui Wang, Feng Tu, Kang Xie, Lu Li, Yuan-Yuan Li, Yi-Xue Agrawal, Sunil Shanghai Ctr Bioinformat Technol Shanghai 200235 Peoples R China Shanghai Jiao Tong Univ Sch Life Sci & Technol Shanghai 200240 Peoples R China Chinese Acad Sci Shanghai Inst Biol Sci Key Lab Syst Biol Shanghai 200031 Peoples R China Chinese Acad Sci Shanghai Inst Biol Sci Bioinformat Ctr Shanghai 200031 Peoples R China

Background: The wide use of Affymetrix microarray in broadened fields of biological research has made the probeset annotation an important issue. Standard Affymetrix probeset annotation is at gene level, i.e. a probeset is precisely linked to a gene, and probeset intensity is interpreted as gene expression. The increased knowledge that one gene may have multiple transcript variants clearly brings up the necessity of updating this gene-level annotation to a refined transcript-level. Results: Through performing rigorous alignments of the Affymetrix probe sequences against a comprehensive pool of currently available transcript sequences, and further linking the probesets to the International Protein Index, we generated transcript-level or protein-level annotation tables for two popular Affymetrix expression arrays, Mouse Genome 430A 2.0 Array and Human Genome U133A Array. Application of our new annotations in re-examining existing expression data sets shows increased expression consistency among synonymous probesets and strengthened expression correlation between interacting proteins. Conclusion: By refining the standard Affymetrix annotation of microarray probesets from the gene level to the transcript level and protein level, one can achieve a more reliable interpretation of their experimental data, which may lead to discovery of more profound regulatory mechanism.

关键词： Transcript Variant annotation file Expression Correlation Affymetrix Array International Protein Index

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GOLEM: an interactive graph-based gene-ontology navigation and analysis tool

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BMC BIOINFORMATICS 2006年第1期7卷 1-9页

作者： Sealfon, Rachel S. G. Hibbs, Matthew A. Huttenhower, Curtis Myers, Chad L. Troyanskaya, Olga G. Princeton Univ Dept Comp Sci Princeton NJ 08544 USA Princeton Univ Carl Icahn Labs Lewis Sigler Inst Integrat Genomics Princeton NJ 08544 USA

Background: The Gene Ontology has become an extremely useful tool for the analysis of genomic data and structuring of biological knowledge. Several excellent software tools for navigating the gene ontology have been developed. However, no existing system provides an interactively expandable graph-based view of the gene ontology hierarchy. Furthermore, most existing tools are web-based or require an Internet connection, will not load local annotations files, and provide either analysis or visualization functionality, but not both. Results: To address the above limitations, we have developed GOLEM (Gene Ontology Local Exploration Map), a visualization and analysis tool for focused exploration of the gene ontology graph. GOLEM allows the user to dynamically expand and focus the local graph structure of the gene ontology hierarchy in the neighborhood of any chosen term. It also supports rapid analysis of an input list of genes to find enriched gene ontology terms. The GOLEM application permits the user either to utilize local gene ontology and annotations files in the absence of an Internet connection, or to access the most recent ontology and annotation information from the gene ontology webpage. GOLEM supports global and organism-specific searches by gene ontology term name, gene ontology id and gene name. Conclusion: GOLEM is a useful software tool for biologists interested in visualizing the local directed acyclic graph structure of the gene ontology hierarchy and searching for gene ontology terms enriched in genes of interest.

关键词： Gene Ontology Directed Acyclic Graph Annotate Gene Gene Ontology Term annotation file

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Computational approaches for isoform detection and estimation: good and bad news

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BMC BIOINFORMATICS 2014年第1期15卷 1-25页

作者： Angelini, Claudia De Canditiis, Daniela De Feis, Italia CNR Ist Applicaz Calcolo I-80125 Naples Italy CNR Ist Applicaz Calcolo Rome Italy

Background: The main goal of the whole transcriptome analysis is to correctly identify all expressed transcripts within a specific cell/tissue- at a particular stage and condition - to determine their structures and to measure their abundances. RNA-seq data promise to allow identification and quantification of transcriptome at unprecedented level of resolution, accuracy and low cost. Several computational methods have been proposed to achieve such purposes. However, it is still not clear which promises are already met and which challenges are still open and require further methodological developments. Results: We carried out a simulation study to assess the performance of 5 widely used tools, such as: CEM, Cufflinks, iReckon, RSEM, and SLIDE. All of them have been used with default parameters. In particular, we considered the effect of the following three different scenarios: the availability of complete annotation, incomplete annotation, and no annotation at all. Moreover, comparisons were carried out using the methods in three different modes of action. In the first mode, the methods were forced to only deal with those isoforms that are present in the annotation;in the second mode, they were allowed to detect novel isoforms using the annotation as guide;in the third mode, they were operating in fully data driven way (although with the support of the alignment on the reference genome). In the latter modality, precision and recall are quite poor. On the contrary, results are better with the support of the annotation, even though it is not complete. Finally, abundance estimation error often shows a very skewed distribution. The performance strongly depends on the true real abundance of the isoforms. Lowly (and sometimes also moderately) expressed isoforms are poorly detected and estimated. In particular, lowly expressed isoforms are identified mainly if they are provided in the original annotation as potential isoforms. Conclusions: Both detection and quantification

关键词： Sequencing Depth annotation file Flux Simulator Complete annotation Incomplete annotation

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AnnotateGenomicRegions: a web application

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BMC BIOINFORMATICS 2014年第1期15卷 1-7页

作者： Zammataro, Luca DeMolfetta, Rita Bucci, Gabriele Ceol, Arnaud Muller, Heiko IIT Ctr Genom Sci IIT SEMM I-20139 Milan Italy European Sch Mol Med SEMM I-20139 Milan Italy

Background: Modern genomic technologies produce large amounts of data that can be mapped to specific regions in the genome. Among the first steps in interpreting the results is annotation of genomic regions with known features such as genes, promoters, CpG islands etc. Several tools have been published to perform this task. However, using these tools often requires a significant amount of bioinformatics skills and/or downloading and installing dedicated software. Results: Here we present AnnotateGenomicRegions, a web application that accepts genomic regions as input and outputs a selection of overlapping and/or neighboring genome annotations. Supported organisms include human (hg18, hg19), mouse (mm8, mm9, mm10), zebrafish (danRer7), and Saccharomyces cerevisiae (sacCer2, sacCer3). AnnotateGenomicRegions is accessible online on a public server or can be installed locally. Some frequently used annotations and genomes are embedded in the application while custom annotations may be added by the user. Conclusions: The increasing spread of genomic technologies generates the need for a simple-to-use annotation tool for genomic regions that can be used by biologists and bioinformaticians alike. AnnotateGenomicRegions meets this demand. AnnotateGenomicRegions is an open-source web application that can be installed on any personal computer or institute server. AnnotateGenomicRegions is available at: http://***/AnnotateGenomicRegions.

关键词： Genomic Region UCSC Genome Browser annotation file Query Region Reduce Representation Bisulfite Sequencing

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TreeDyn:: towards dynamic graphics and annotations for analyses of trees

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BMC BIOINFORMATICS 2006年第1期7卷 1-9页

作者： Chevenet, Francois Brun, Christine Banuls, Anne-Laure Jacq, Bernard Christen, Richard IRD IRD 2724 CNRS UMRLab Genet & Evolut Malad Infect F-34394 Montpellier 5 France CNRS UMR 6216 Inst Biol Dev Marseille Luminy F-13288 Marseille 9 France Univ Nice Ctr Biochim CNRS UMR 6543Lab Biol Virtuelle F-06108 Nice France

Background: Analyses of biomolecules for biodiversity, phylogeny or structure/function studies often use graphical tree representations. Many powerful tree editors are now available, but existing tree visualization tools make little use of meta-information related to the entities under study such as taxonomic descriptions or gene functions that can hardly be encoded within the tree itself (if using popular tree formats). Consequently, a tedious manual analysis and post-processing of the tree graphics are required if one needs to use external information for displaying or investigating trees. Results: We have developed TreeDyn, a tool using annotations and dynamic graphical methods for editing and analyzing multiple trees. The main features of TreeDyn are 1) the management of multiple windows and multiple trees per window, 2) the export of graphics to several standard file formats with or without HTML encapsulation and a new format called TGF, which enables saving and restoring graphical analysis, 3) the projection of texts or symbols facing leaf labels or linked to nodes, through manual pasting or by using annotation files, 4) the highlight of graphical elements after querying leaf labels (or annotations) or by selection of graphical elements and information extraction, 5) the highlight of targeted trees according to a source tree browsed by the user, 6) powerful scripts for automating repetitive graphical tasks, 7) a command line interpreter enabling the use of TreeDyn through CGI scripts for online building of trees, 8) the inclusion of a library of packages dedicated to specific research fields involving trees. Conclusion: TreeDyn is a tree visualization and annotation tool which includes tools for tree manipulation and annotation and uses meta-information through dynamic graphical operators or scripting to help analyses and annotations of single trees or tree collections.

关键词： annotation file Reflection Operator Tree Manipulation Leaf Label Graphical Management

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InGeno - an integrated genome and ortholog viewer for improved genome to genome comparisons

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BMC BIOINFORMATICS 2006年第1期7卷 1-10页

作者： Liang, Chunguang Dandekar, Thomas Univ Wurzburg Bioctr Dept Bioinformat D-97074 Wurzburg Germany European Mol Biol Lab D-69012 Heidelberg Germany

Background: Systematic genome comparisons are an important tool to reveal gene functions, pathogenic features, metabolic pathways and genome evolution in the era of post-genomics. Furthermore, such comparisons provide important clues for vaccines and drug development. Existing genome comparison software often lacks accurate information on orthologs, the function of similar genes identified and genome-wide reports and lists on specific functions. All these features and further analyses are provided here in the context of a modular software tool "inGeno" written in Java with Biojava subroutines. Results: InGeno provides a user-friendly interactive visualization platform for sequence comparisons (comprehensive reciprocal protein-protein comparisons) between complete genome sequences and all associated annotations and features. The comparison data can be acquired from several different sequence analysis programs in flexible formats. Automatic dot-plot analysis includes output reduction, filtering, ortholog testing and linear regression, followed by smart clustering (local collinear blocks;LCBs) to reveal similar genome regions. Further, the system provides genome alignment and visualization editor, collinear relationships and strain-specific islands. Specific annotations and functions are parsed, recognized, clustered, logically concatenated and visualized and summarized in reports. Conclusion: As shown in this study, inGeno can be applied to study and compare in particular prokaryotic genomes against each other (gram positive and negative as well as close and more distantly related species) and has been proven to be sensitive and accurate. This modular software is user-friendly and easily accommodates new routines to meet specific user-defined requirements.

关键词： Hemolytic Uremic Syndrome annotation file Strain MG1655 Genome Viewer Java Runtime Environment

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A web-based multi-genome synteny viewer for customized data

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BMC BIOINFORMATICS 2012年第1期13卷 1-7页

作者： Revanna, Kashi V. Munro, Daniel Gao, Alvin Chiu, Chi-Chen Pathak, Anil Dong, Qunfeng Univ N Texas Dept Biol Sci Denton TX 76203 USA Univ N Texas Texas Acad Math & Sci Denton TX 76203 USA Univ N Texas Dept Comp Sci & Engn Denton TX 76203 USA

Background: Web-based synteny visualization tools are important for sharing data and revealing patterns of complicated genome conservation and rearrangements. Such tools should allow biologists to upload genomic data for their own analysis. This requirement is critical because individual biologists are generating large amounts of genomic sequences that quickly overwhelm any centralized web resources to collect and display all those data. Recently, we published a web-based synteny viewer, GSV, which was designed to satisfy the above requirement. However, GSV can only compare two genomes at a given time. Extending the functionality of GSV to visualize multiple genomes is important to meet the increasing demand of the research community. Results: We have developed a multi-Genome Synteny Viewer (mGSV). Similar to GSV, mGSV is a web-based tool that allows users to upload their own genomic data files for visualization. Multiple genomes can be presented in a single integrated view with an enhanced user interface. Users can navigate through all the selected genomes in either pairwise or multiple viewing mode to examine conserved genomic regions as well as the accompanying genome annotations. Besides serving users who manually interact with the web server, mGSV also provides Web Services for machine-to-machine communication to accept data sent by other remote resources. The entire mGSV package can also be downloaded for easy local installation. Conclusions: mGSV significantly enhances the original functionalities of GSV. A web server hosting mGSV is provided at http://***/mgsv.

关键词： annotation file Multiple Genome CoGe Blast Output annotation Track

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Inconsistencies over time in 5% of NetAffx probe-to-gene annotations

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BMC BIOINFORMATICS 2005年第1期6卷 1-3页

作者： Perez-Iratxeta, C Andrade, MA Ottawa Hlth Res Inst Ontario Genom Innovat Ctr Ottawa ON K1H 8L6 Canada

Background: DNA microarray probes are designed to match particular mRNA transcripts, often based on expressed sequences like ESTs, or cDNAs, many times incomplete. As a result, the relations between probes and genes can change as the sequence data are updated. However, it is frequent that the reported results of microarray analyses are given just as lists of genes without any reference to the underlying probes. Results: We show for a particular commercial microarray design that the number of probes associated to some genes change with time. These changes concern approximately 5% of the probe sets across the history of annotation releases over a two year span. Conclusion: We recommend to report probe set identifiers when publishing microarray results, and to submit those analyses to microarray public databases to ensure that the interpretation of the data is updated with the latest set of annotations.

关键词： annotation file Microarray Gene Expression Data UniGene Cluster Microarray Analysis Result Variable Gene Structure

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GSV: a web-based genome synteny viewer for customized data

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BMC BIOINFORMATICS 2011年第1期12卷 1-4页

作者： Revanna, Kashi V. Chiu, Chi-Chen Bierschank, Ezekiel Dong, Qunfeng Univ N Texas Dept Biol Sci Denton TX 76203 USA Univ N Texas Dept Comp Sci & Engn Denton TX 76203 USA

Background: The analysis of genome synteny is a common practice in comparative genomics. With the advent of DNA sequencing technologies, individual biologists can rapidly produce their genomic sequences of interest. Although web-based synteny visualization tools are convenient for biologists to use, none of the existing ones allow biologists to upload their own data for analysis. Results: We have developed the web-based Genome Synteny Viewer (GSV) that allows users to upload two data files for synteny visualization, the mandatory synteny file for specifying genomic positions of conserved regions and the optional genome annotation file. GSV presents two selected genomes in a single integrated view while still retaining the browsing flexibility necessary for exploring individual genomes. Users can browse and filter for genomic regions of interest, change the color or shape of each annotation track as well as re-order, hide or show the tracks dynamically. Additional features include downloadable images, immediate email notification and tracking of usage history. The entire GSV package is also light-weighted which enables easy local installation. Conclusions: GSV provides a unique option for biologists to analyze genome synteny by uploading their own data set to a web-based comparative genome browser. A web server hosting GSV is provided at http://***/gsv, and the software is also freely available for local installations.

关键词： Genomic Feature Alignment Score annotation file Individual Genome Local Installation

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