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.     

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     

SNPdetector: a software tool for sensitive and accurate SNP detection

Identification of single nucleotide polymorphisms (SNPs) and mutations is important for the discovery of genetic predisposition to complex diseases. PCR resequencing is the method of choice for de novo SNP discovery. However, manual curation of putative SNPs has been a major bottleneck in the application of this method to high-throughput screening. Therefore it is critical to develop a more sensitive and accurate computational method for automated SNP detection. We developed a software tool, SNPdetector, for automated identification of SNPs and mutations in fluorescence-based resequencing reads. SNPdetector was designed to model the process of human visual inspection and has a very low false positive and false negative rate. We demonstrate the superior performance of SNPdetector in SNP and mutation analysis by comparing its results with those derived by human inspection, PolyPhred (a popular SNP detection tool), and independent genotype assays in three large-scale investigations. The first study identified and validated inter- and intra-subspecies variations in 4,650 traces of 25 inbred mouse strains that belong to either the Mus musculus species or the M. spretus species. Unexpected heterozygosity in CAST/Ei strain was observed in two out of 1,167 mouse SNPs. The second study identified 11,241 candidate SNPs in five ENCODE regions of the human genome covering 2.5 Mb of genomic sequence. Approximately 50% of the candidate SNPs were selected for experimental genotyping; the validation rate exceeded 95%. The third study detected ENU-induced mutations (at 0.04% allele frequency) in 64,896 traces of 1,236 zebra fish. Our analysis of three large and diverse test datasets demonstrated that SNPdetector is an effective tool for genome-scale research and for large-sample clinical studies. SNPdetector runs on Unix/Linux platform and is available publicly (http://lpg.nci.nih.gov).     

G-IMEx: A comprehensive software tool for detection of microsatellites from genome sequences

Microsatellites are ubiquitous short tandem repeats found in all known genomes and are known to play a very important role in various studies and fields including DNA fingerprinting, paternity studies, evolutionary studies, virulence and adaptation of certain bacteria and viruses etc. Due to the sequencing of several genomes and the availability of enormous amounts of sequence data during the past few years, computational studies of microsatellites are of interest for many researchers. In this context, we developed a software tool called Imperfect Microsatellite Extractor (IMEx), to extract perfect, imperfect and compound microsatellites from genome sequences along with their complete statistics. Recently we developed a user-friendly graphical-interface using JAVA for IMEx to be used as a stand-alone software named G-IMEx. G-IMEx takes a nucleotide sequence as an input and the results are produced in both html and text formats. The Linux version of G-IMEx can be downloaded for free from http://www.cdfd.org.in/imex.     

BCETM: a tool for software integration

The integration of software into special-purpose systems (e.g.for gene sequence analysis) can be a difficult task. We describea general-purpose software integration tool, the BCETM program,that facilitates assembly of VAX-based software into applicationsystems and provides an easy-to-use, intuitive user interface.We describe the use of BCE to integrate a heterogeneous collectionof sequence analysis tools. Many BCE design features are generallyapplicable and can be implemented in other language or hardwareenvironments. Received on May 13, 1987; accepted on October 2, 1987     

JColorGrid: software for the visualization of biological measurements

Background  

Two-dimensional data colourings are an effective medium by which to represent three-dimensional data in two dimensions. Such "color-grid" representations have found increasing use in the biological sciences (e.g. microarray 'heat maps' and bioactivity data) as they are particularly suited to complex data sets and offer an alternative to the graphical representations included in traditional statistical software packages. The effectiveness of color-grids lies in their graphical design, which introduces a standard for customizable data representation. Currently, software applications capable of generating limited color-grid representations can be found only in advanced statistical packages or custom programs (e.g. micro-array analysis tools), often associated with steep learning curves and requiring expert knowledge.     

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.     

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/.     

SeqExpress: desktop analysis and visualization tool for gene expression experiments

SUMMARY: SeqExpress is a stand-alone desktop application for the identification of relevant genes within collections of microarray or SAGE experiments. A number of analysis, filtering and visualization tools are provided to aid in the selection of groups of genes. If R is installed then the application can use this to provide further analysis. AVAILABILITY: SeqExpress is available at: http://www.seqexpress.com     

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.     

Phenostat: visualization and statistical tool for analysis of phenotyping data

The effective extraction of information from multidimensional data sets derived from phenotyping experiments is a growing challenge in biology. Data visualization tools are important resources that can aid in exploratory data analysis of complex data sets. Phenotyping experiments of model organisms produce data sets in which a large number of phenotypic measures are collected for each individual in a group. A critical initial step in the analysis of such multidimensional data sets is the exploratory analysis of data distribution and correlation. To facilitate the rapid visualization and exploratory analysis of multidimensional complex trait data, we have developed a user-friendly, web-based software tool called Phenostat. Phenostat is composed of a dynamic graphical environment that allows the user to inspect the distribution of multiple variables in a data set simultaneously. Individuals can be selected by directly clicking on the graphs and thus displaying their identity, highlighting corresponding values in all graphs, allowing their inclusion or exclusion from the analysis. Statistical analysis is provided by R package functions. Phenostat is particularly suited for rapid distribution and correlation analysis of subsets of data. An analysis of behavioral and physiologic data stemming from a large mouse phenotyping experiment using Phenostat reveals previously unsuspected correlations. Phenostat is freely available to academic institutions and nonprofit organizations and can be used from our website at .     

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].     

GGT 2.0: versatile software for visualization and analysis of genetic data

Ever since its first release in 1999, the free software package for visualization of molecular marker data, graphical genotype (GGT), has been constantly adapted and improved. The GGT package was developed in a plant-breeding context and thus focuses on plant genetic data but was not intended to be limited to plants only. The current version has many options for genetic analysis of populations including diversity analyses and simple association studies. A second release of the GGT package, GGT 2.0 (available through http://www.plantbreeding.wur.nl), is therefore presented in this paper. An overview of existing and new features that are available within GGT 2.0, and a case study in which GGT 2.0 is applied to analyze an existing set of plant genetic data, are presented and discussed.     

methGraph: A genome visualization tool for PCR-based methylation assays

Abnormalities in DNA methylation of CpG islands that play a role in gene regulation affect gene expression and hence play a role in disease, including cancer. Bisulfite-based DNA methylation analysis methods such as methylation-specific PCR (MSP) and bisulfite sequencing (BiSeq) are most commonly used to study gene-specific DNA methylation. Assessing specificity and visualizing the position of PCR primers in their genomic context is a laborious and tedious task, primarily due to the sequence changes induced during the bisulfite conversion. For this purpose, we developed methGraph, a web application for easy, fast and flexible visualization and accurate in silico quality evaluation of PCR-based methylation assays. The visualization process starts by submitting PCR primer sequences for specificity assessment and mapping on the genome using the BiSearch ePCR primer-search algorithm. The next step comprises the selection of relevant UCSC genome annotation tracks for display in the final graph. A custom track showing all individual CpG dinucleotides, representing their distribution in the CpG island is also provided. Finally, methGraph creates a BED file that is automatically uploaded to the UCSC genome browser, after which the resulting image files are extracted and made available for visualization and download. The generated high-quality figures can easily be customized and exported for use in publications or presentations. methGraph is available at http://mellfire.ugent.be/methgraph/.     

Interactive visualization software for exploring phylogenetic trees and clades

Summary: The Summary Tree Explorer (STE) is a Java applicationfor interactively exploring sets of phylogenetic trees usingtwo coupled representations: a node-and-link diagram and a textuallist of common clades. Selection, pruning, filtering or re-rootingin one representation is immediately reflected in the other.While summary trees are more effective at showing the relationshipamong clades, they can only show a consistent subset of thosethat appear in the textual list. Working with both representationsmitigates the disadvantages of having to choose just one. Availability: STE, along with several sample datasets, is availableat http://cityscape.inf.cs.cmu.edu/phylogeny/ Contact: mad{at}cs.cmu.edu Associate Editor: Martin Bishop