BicOverlapper: a tool for bicluster visualization

Summary: BicOverlapper is a tool to visualize biclusters fromgene-expression matrices in a way that helps to compare biclusteringmethods, to unravel trends and to highlight relevant genes andconditions. A visual approach can complement biological andstatistical analysis and reduce the time spent by specialistsinterpreting the results of biclustering algorithms. The techniqueis based on a force-directed graph where biclusters are representedas flexible overlapped groups of genes and conditions. Availability: The BicOverlapper software and supplementary materialare available at http://vis.usal.es/bicoverlapper Contact: rodri{at}usal.es Associate Editor: John Quackenbush The first two authors should be reported as joint first authors.     

GenomeComp: a visualization tool for microbial genome comparison

We have developed a software tool, GenomeComp, for summarizing, parsing and visualizing the genome sequences comparison results derived from voluminous BLAST textual output. With GenomeComp, the variation between genomes can be easily highlighted, such as repeat regions, insertions, deletions and rearrangements of genomic segments. This software provides a new visualizing tool for microbe comparative genomics.     

SNP-VISTA: An interactive SNP visualization tool

Background  

Recent advances in sequencing technologies promise to provide a better understanding of the genetics of human disease as well as the evolution of microbial populations. Single Nucleotide Polymorphisms (SNPs) are established genetic markers that aid in the identification of loci affecting quantitative traits and/or disease in a wide variety of eukaryotic species. With today's technological capabilities, it has become possible to re-sequence a large set of appropriate candidate genes in individuals with a given disease in an attempt to identify causative mutations. In addition, SNPs have been used extensively in efforts to study the evolution of microbial populations, and the recent application of random shotgun sequencing to environmental samples enables more extensive SNP analysis of co-occurring and co-evolving microbial populations. The program is available at [1].     

MarVis: a tool for clustering and visualization of metabolic biomarkers

Background  

A central goal of experimental studies in systems biology is to identify meaningful markers that are hidden within a diffuse background of data originating from large-scale analytical intensity measurements as obtained from metabolomic experiments. Intensity-based clustering is an unsupervised approach to the identification of metabolic markers based on the grouping of similar intensity profiles. A major problem of this basic approach is that in general there is no prior information about an adequate number of biologically relevant clusters.     

MarVis: a tool for clustering and visualization of metabolic biomarkers

Background

Gene set analysis based on Gene Ontology (GO) can be a promising method for the analysis of differential expression patterns. However, current studies that focus on individual GO terms have limited analytical power, because the complex structure of GO introduces strong dependencies among the terms, and some genes that are annotated to a GO term cannot be found by statistically significant enrichment.

Results

We proposed a method for enriching clustered GO terms based on semantic similarity, namely cluster enrichment analysis based on GO (CeaGO), to extend the individual term analysis method. Using an Affymetrix HGU95aV2 chip dataset with simulated gene sets, we illustrated that CeaGO was sensitive enough to detect moderate expression changes. When compared to parent-based individual term analysis methods, the results showed that CeaGO may provide more accurate differentiation of gene expression results. When used with two acute leukemia (ALL and ALL/AML) microarray expression datasets, CeaGO correctly identified specifically enriched GO groups that were overlooked by other individual test methods.

Conclusion

By applying CeaGO to both simulated and real microarray data, we showed that this approach could enhance the interpretation of microarray experiments. CeaGO is currently available at http://chgc.sh.cn/en/software/CeaGO/.     

BLogo: a tool for visualization of bias in biological sequences

Blogo is a web-based tool that detects and displays statistically significant position-specific sequence bias with reduced background noise. The over-represented and under-represented symbols in a particular position are shown above and below the zero line. When the sequences are in open reading frames, the background frequency of nucleotides could be calculated separately for the three positions of a codon, thus greatly reducing the background noise. The chi(2)-test or Fisher's exact test is used to evaluate the statistical significance of every symbol in every position and only those that are significant are highlighted in the resulting logo. The perl source code of the program is freely available and can be run locally. AVAILABILITY: http://acephpx.cropdb.org/blogo/, http://www.bioinformatics.org/blogo/.     

Spore-displayed streptavidin: a live diagnostic tool in biotechnology

Streptavidin, which is one of the most widely used proteins in biotechnological application field and is active only in tetrameric form, was surface expressed on the surface of Bacillus subtilis spore. Spore coat protein of B. subtilis, CotG, was used as an anchoring motif to display streptavidin. FACS using anti-streptavidin antibody was used for the verification of surface localization of expressed CotG-streptavidin fusion protein. FACS and dot-blot were used for the verification of biological activity of displayed streptavidin with FITC-labeled biotin.     

WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data

Background  

Analysis of High Throughput (HTP) Data such as microarray and proteomics data has provided a powerful methodology to study patterns of gene regulation at genome scale. A major unresolved problem in the post-genomic era is to assemble the large amounts of data generated into a meaningful biological context. We have developed a comprehensive software tool, WholePathwayScope (WPS), for deriving biological insights from analysis of HTP data.     

PIPE-CLIP: a comprehensive online tool for CLIP-seq data analysis

CLIP-seq is widely used to study genome-wide interactions between RNA-binding proteins and RNAs. However, there are few tools available to analyze CLIP-seq data, thus creating a bottleneck to the implementation of this methodology. Here, we present PIPE-CLIP, a Galaxy framework-based comprehensive online pipeline for reliable analysis of data generated by three types of CLIP-seq protocol: HITS-CLIP, PAR-CLIP and iCLIP. PIPE-CLIP provides both data processing and statistical analysis to determine candidate cross-linking regions, which are comparable to those regions identified from the original studies or using existing computational tools. PIPE-CLIP is available at http://pipeclip.qbrc.org/.     

SNPTools: a software tool for visualization and analysis of microarray data

SUMMARY: We have created a software tool, SNPTools, for analysis and visualization of microarray data, mainly SNP array data. The software can analyse and find differences in intensity levels between groups of arrays and identify segments of SNPs (genes, clones), where the intensity levels differ significantly between the groups. In addition, SNPTools can show jointly loss-of-heterozygosity (LOH) data (derived from genotypes) and intensity data for paired samples of tumour and normal arrays. The output graphs can be manipulated in various ways to modify and adjust the layout. A wizard allows options and parameters to be changed easily and graphs replotted. All output can be saved in various formats, and also re-opened in SNPTools for further analysis. For explorative use, SNPTools allows various genome information to be loaded onto the graphs. AVAILABILITY: The software, example data sets and tutorials are freely available from http://www.birc.au.dk/snptools     

VisBio: a computational tool for visualization of multidimensional biological image data

New laser scanning microscopy techniques enable biologists to acquire larger, more complex image datasets. Emerging imaging modalities such as multispectral, harmonic, and fluorescence lifetime can generate data with six or more dimensions; however, existing software is not well suited to the visualization or analysis of such data. To address these concerns, we have developed VisBio, an application and toolkit for visualization and analysis of multidimensional, biological image data of any dimensionality.