Turning publicly available gene expression data into discoveries using gene set context analysis

Gene Set Context Analysis (GSCA) is an open source software package to help researchers use massive amounts of publicly available gene expression data (PED) to make discoveries. Users can interactively visualize and explore gene and gene set activities in 25,000+ consistently normalized human and mouse gene expression samples representing diverse biological contexts (e.g. different cells, tissues and disease types, etc.). By providing one or multiple genes or gene sets as input and specifying a gene set activity pattern of interest, users can query the expression compendium to systematically identify biological contexts associated with the specified gene set activity pattern. In this way, researchers with new gene sets from their own experiments may discover previously unknown contexts of gene set functions and hence increase the value of their experiments. GSCA has a graphical user interface (GUI). The GUI makes the analysis convenient and customizable. Analysis results can be conveniently exported as publication quality figures and tables. GSCA is available at https://github.com/zji90/GSCA. This software significantly lowers the bar for biomedical investigators to use PED in their daily research for generating and screening hypotheses, which was previously difficult because of the complexity, heterogeneity and size of the data.     

Phydbac Gene Function Predictor : a gene annotation tool based on genomic context analysis

Background  

The large amount of completely sequenced genomes allows genomic context analysis to predict reliable functional associations between prokaryotic proteins. Major methods rely on the fact that genes encoding physically interacting partners or members of shared metabolic pathways tend to be proximate on the genome, to evolve in a correlated manner and to be fused as a single sequence in another organism.     

Visualising gene expression in its metabolic context

Relative changes in mRNA as well as protein levels induced by sublethal doses of antibiotics on bacteria are measured and results visualised in the context of metabolic pathway diagrams. The mRNA levels present at a given time point after the addition of the antibiotic are measured using microarrays from Affymetrix. Additionally, the relative amount of each protein synthesised during 3 minute intervals sampled at the given times is measured using radio-labelling followed by two-dimensional polyacrylamide gel electrophoresis and the subsequent analysis of the images produced by exposure to a phosphorimager. Metabolic pathway diagrams are both constructed in-house and imported from KEGG (Kyoto Encyclopedia of Genes and Genomes). Both protein and mRNA expression data can be displayed in the pathway diagrams such that the colour of the vectors or enzyme identifiers indicate the relative change in expression level and reproducibility.     

Putting DNA methylation in context: from genomes to gene expression in plants

Plant DNA methylation is its own language, interpreted by the cell to maintain silencing of transposons, facilitate chromatin structure, and to ensure proper expression of some genes. Just as in any language, context is important. Rather than being a simple “on-off switch”, DNA methylation has a range of “meanings” dependent upon the underlying sequence and its location in the genome. Differences in the sequence context of individual sites are established, maintained, and interpreted by differing molecular pathways. Varying patterns of methylation within genes and surrounding sequences are associated with a continuous range of expression differences, from silencing to constitutive expression. These often-subtle differences have been pieced together from years of effort, but have taken off with the advent of methods for assessing methylation across entire genomes. Recognizing these patterns and identifying underlying causes is essential for understanding the function of DNA methylation and its systems-wide contribution to a range of processes in plant genomes. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.     

Putting microarrays in a context: integrated analysis of diverse biological data

In recent years, multiple types of high-throughput functional genomic data that facilitate rapid functional annotation of sequenced genomes have become available. Gene expression microarrays are the most commonly available source of such data. However, genomic data often sacrifice specificity for scale, yielding very large quantities of relatively lower-quality data than traditional experimental methods. Thus sophisticated analysis methods are necessary to make accurate functional interpretation of these large-scale data sets. This review presents an overview of recently developed methods that integrate the analysis of microarray data with sequence, interaction, localisation and literature data, and further outlines current challenges in the field. The focus of this review is on the use of such methods for gene function prediction, understanding of protein regulation and modelling of biological networks.     

Parallel tion in the context of character analysis

For the establishment of polarity of character transformation prior to phylogenetic analysis, various logical and biological criteria are discussed; some are rejected on grounds of liability to systematic error, circularity or unwarranted assumptions aboutParallel tion is used as a non-polar term, with forward and reverse to indicate polarity. A computer program for the detection of parallel tion is described which takes taxa in groups of four. The characters, with two derived: two primitive states or three derived: one primitive state, are listed according to the distribution of states over the four taxa. To each of the 15 phylogenies there corresponds a compatible pair of character patterns. Discordant 2: 2 patterns are unconditionally incompatible (Le Quesne test failure), discordant 3: 1 patterns are incompatible conditional upon correct scoring of polarity. For any putative phylogeny the concordant and discordant characters are identified. In cases of competing alternatives these character sets have to be weighed against one another. Character weighting is discussed; it is argued that it is the individual character transformation which should be weighted, in each direction separately.     

Comprehensive mutational analysis of a herpesvirus gene in the viral genome context reveals a region essential for virus replication

Essential viral proteins perform vital functions during morphogenesis via a complex interaction with other viral and cellular gene products. Here, we present a novel approach to comprehensive mutagenesis of essential cytomegalovirus genes and biological analysis in the 230-kbp-genome context. A random Tn7-based mutagenesis procedure at the single-gene level was combined with site-specific recombination via the FLP/FLP recognition target site system for viral genome reconstitution. We show the function of more than 100 mutants from a larger library of M50/p35, a protein involved in capsid egress from the nucleus. This protein recruits other viral proteins and cellular enzymes to the inner nuclear membrane. Our approach enabled us to rapidly discriminate between essential and nonessential regions within the coding sequence. Based on the prediction of the screen, we were able to map a site essential for viral protein-protein interaction at the amino acid level.     

Talk about talk: Metacommentary and context in the analysis of psychotic discourse

This paper presents an analysis of an interview with a manic patient at a time when her discourse seemed incoherent. It addresses itself to the interface between discourse and context, and argues that adequate contextualization of discourse can render incoherent speech more understandable. Appraisal of context and analysis of metacommentary — speakers' references to the ongoing talk — makes apparently incoherent discourse intelligible, and gives access to the patient's experience of her illness.The implications of discourse analysis for psychiatric research are explored. General goals for discourse analysis in psychiatric settings are suggested, and strengths and weaknesses of the approach discussed.     

BAGET: a web server for the effortless retrieval of prokaryotic gene context and sequence

BAGET (Bacterial and Archaeal Gene Exploration Tool) is a web service designed to facilitate extraction, by molecular geneticists and phylogeneticists, of specific gene and protein sequences from completely determined prokaryotic genomes. Upon selection of a particular prokaryotic organism and gene, two levels of visual gene context information are provided on a single dynamic page: (i) a graphical representation of a user defined portion of the chromosome centered on the gene of interest and (ii) the DNA sequence of the query gene, of the immediate neighboring genes and the intergenic regions each identified by a consistent color code. The aminoacid sequence is provided for protein-coding query genes. Query results can be exported as a rich text format (RTF) word processor file for printing, archival or further analysis. AVAILABILITY: http://archaea.u-psud.fr/bin/baget.dll.     

GEOGLE: context mining tool for the correlation between gene expression and the phenotypic distinction

Background  

In the post-genomic era, the development of high-throughput gene expression detection technology provides huge amounts of experimental data, which challenges the traditional pipelines for data processing and analyzing in scientific researches.     

PAGE: phase-shifted analysis of gene expression

Grouping of gene expression patterns across biological experiments, treatments and time-series data is performed in q-intervals of measurements using phase-shifted analysis of gene expression (PAGE); a Java-based tool to find clusters of genes that share trends of expression profiles within the dataset. The patterns and genes within q-Clusters are visualized in trend plots and compared to determine biological relevance from the gene annotations.     

AGRA: analysis of gene ranking algorithms

Often, the most informative genes have to be selected from different gene sets and several computer gene ranking algorithms have been developed to cope with the problem. To help researchers decide which algorithm to use, we developed the analysis of gene ranking algorithms (AGRA) system that offers a novel technique for comparing ranked lists of genes. The most important feature of AGRA is that no previous knowledge of gene ranking algorithms is needed for their comparison. Using the text mining system finding-associated concepts with text analysis. AGRA defines what we call biomedical concept space (BCS) for each gene list and offers a comparison of the gene lists in six different BCS categories. The uploaded gene lists can be compared using two different methods. In the first method, the overlap between each pair of two gene lists of BCSs is calculated. The second method offers a text field where a specific biomedical concept can be entered. AGRA searches for this concept in each gene lists' BCS, highlights the rank of the concept and offers a visual representation of concepts ranked above and below it. AVAILABILITY AND IMPLEMENTATION: Available at http://agra.fzv.uni-mb.si/, implemented in Java and running on the Glassfish server. CONTACT: simon.kocbek@uni-mb.si.