Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis

Background  

Spectral processing and post-experimental data analysis are the major tasks in NMR-based metabonomics studies. While there are commercial and free licensed software tools available to assist these tasks, researchers usually have to use multiple software packages for their studies because software packages generally focus on specific tasks. It would be beneficial to have a highly integrated platform, in which these tasks can be completed within one package. Moreover, with open source architecture, newly proposed algorithms or methods for spectral processing and data analysis can be implemented much more easily and accessed freely by the public.     

Bioclipse: an open source workbench for chemo- and bioinformatics

Background  

There is a need for software applications that provide users with a complete and extensible toolkit for chemo- and bioinformatics accessible from a single workbench. Commercial packages are expensive and closed source, hence they do not allow end users to modify algorithms and add custom functionality. Existing open source projects are more focused on providing a framework for integrating existing, separately installed bioinformatics packages, rather than providing user-friendly interfaces. No open source chemoinformatics workbench has previously been published, and no sucessful attempts have been made to integrate chemo- and bioinformatics into a single framework.     

Automating dChip: toward reproducible sharing of microarray data analysis

Background  

During the past decade, many software packages have been developed for analysis and visualization of various types of microarrays. We have developed and maintained the widely used dChip as a microarray analysis software package accessible to both biologist and data analysts. However, challenges arise when dChip users want to analyze large number of arrays automatically and share data analysis procedures and parameters. Improvement is also needed when the dChip user support team tries to identify the causes of reported analysis errors or bugs from users.     

WebArray: an online platform for microarray data analysis

Background  

Many cutting-edge microarray analysis tools and algorithms, including commonly used limma and affy packages in Bioconductor, need sophisticated knowledge of mathematics, statistics and computer skills for implementation. Commercially available software can provide a user-friendly interface at considerable cost. To facilitate the use of these tools for microarray data analysis on an open platform we developed an online microarray data analysis platform, WebArray, for bench biologists to utilize these tools to explore data from single/dual color microarray experiments.     

The dChip survival analysis module for microarray data

Background  

Genome-wide expression signatures are emerging as potential marker for overall survival and disease recurrence risk as evidenced by recent commercialization of gene expression based biomarkers in breast cancer. Similar predictions have recently been carried out using genome-wide copy number alterations and microRNAs. Existing software packages for microarray data analysis provide functions to define expression-based survival gene signatures. However, there is no software that can perform survival analysis using SNP array data or draw survival curves interactively for expression-based sample clusters.     

phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

Background

The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data.

Results

Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research.

Conclusions

The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.     

A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data

Background  

Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible for serious diseases, with a great scientific impact and a wide application area. Several standalone applications had been developed in order to analyze microarray data. Two of the most known free analysis software packages are the R-based Bioconductor and dChip. The part of dChip software concerning the calculation and the analysis of gene expression has been modified to permit its execution on both cluster environments (supercomputers) and Grid infrastructures (distributed computing).     

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.     

fcGENE: A Versatile Tool for Processing and Transforming SNP Datasets

Background

Modern analysis of high-dimensional SNP data requires a number of biometrical and statistical methods such as pre-processing, analysis of population structure, association analysis and genotype imputation. Software used for these purposes often rely on specific and incompatible input and output data formats. Therefore extensive data management including multiple format conversions is necessary during analyses.

Methods

In order to support fast and efficient management and bio-statistical quality control of high-dimensional SNP data, we developed the publically available software fcGENE using C++ object-oriented programming language. This software simplifies and automates the use of different existing analysis packages, especially during the workflow of genotype imputations and corresponding analyses.

Results

fcGENE transforms SNP data and imputation results into different formats required for a large variety of analysis packages such as PLINK, SNPTEST, HAPLOVIEW, EIGENSOFT, GenABEL and tools used for genotype imputation such as MaCH, IMPUTE, BEAGLE and others. Data Management tasks like merging, splitting, extracting SNP and pedigree information can be performed. fcGENE also supports a number of bio-statistical quality control processes and quality based filtering processes at SNP- and sample-wise level. The tool also generates templates of commands required to run specific software packages, especially those required for genotype imputation. We demonstrate the functionality of fcGENE by example workflows of SNP data analyses and provide a comprehensive manual of commands, options and applications.

Conclusions

We have developed a user-friendly open-source software fcGENE, which comprehensively supports SNP data management, quality control and analysis workflows. Download statistics and corresponding feedbacks indicate that software is highly recognised and extensively applied by the scientific community.     

Flexible mapping of homology onto structure with Homolmapper

Background  

Over the past decade, a number of tools have emerged for the examination of homology relationships among protein sequences in a structural context. Most recent software implementations for such analysis are tied to specific molecular viewing programs, which can be problematic for collaborations involving multiple viewing environments. Incorporation into larger packages also adds complications for users interested in adding their own scoring schemes or in analyzing proteins incorporating unusual amino acid residues such as selenocysteine.     

msBayes: Pipeline for testing comparative phylogeographic histories using hierarchical approximate Bayesian computation

Background  

Although testing for simultaneous divergence (vicariance) across different population-pairs that span the same barrier to gene flow is of central importance to evolutionary biology, researchers often equate the gene tree and population/species tree thereby ignoring stochastic coalescent variance in their conclusions of temporal incongruence. In contrast to other available phylogeographic software packages, msBayes is the only one that analyses data from multiple species/population pairs under a hierarchical model.     

GPFrontend and GPGraphics: graphical analysis tools for genetic association studies

Background  

Most software packages for whole genome association studies are non-graphical, purely text based programs originally designed to run with UNIX-like operating systems. Graphical output is often not intended or supposed to be performed with other command line tools, e.g. gnuplot.     

2DDB – a bioinformatics solution for analysis of quantitative proteomics data

Background  

We present 2DDB, a bioinformatics solution for storage, integration and analysis of quantitative proteomics data. As the data complexity and the rate with which it is produced increases in the proteomics field, the need for flexible analysis software increases.     

Criteria for the evaluation of life cycle assessment software packages and life cycle inventory data with application to concrete

Purpose

Life cycle assessment (LCA) software packages have proliferated and evolved as LCA has developed and grown. There are now a multitude of LCA software packages that must be critically evaluated by users. Prior to conducting a comparative LCA study on different concrete materials, it is necessary to examine a variety of software packages for this specific purpose. The paper evaluates five LCA tools in the context of the LCA of seven concrete mix designs (conventional concrete, concrete with fly ash, slag, silica fume or limestone as cement replacement, recycled aggregate concrete, and photocatalytic concrete).

Methods

Three key evaluation criteria required to assess the quality of analysis are adequate flexibility, sophistication and complexity of analysis, and usefulness of outputs. The quality of life cycle inventory (LCI) data included in each software package is also assessed for its reliability, completeness, and correlation to the scope of LCA of concrete products in Canada. A questionnaire is developed for evaluating LCA software packages and is applied to five LCA tools.

Results and discussion

The result is the selection of a software package for the specific context of LCA of concrete materials in Canada, which will be used to complete a full LCA study. The software package with the highest score is software package C (SP-C), with 44 out of a possible 48 points. Its main advantage is that it allows for the user to have a high level of control over the system being modeled and the calculation methods used.

Conclusions

This comparative study highlights the importance of selecting a software package that is appropriate for a specific research project. The ability to accurately model the chosen functional unit and system boundary is an important selection criterion. This study demonstrates a method to enable a critical and rigorous comparison without excessive and redundant duplication of efforts.

     

Pegasys: software for executing and integrating analyses of biological sequences

Background  

We present Pegasys – a flexible, modular and customizable software system that facilitates the execution and data integration from heterogeneous biological sequence analysis tools.     

An interactional network of genes involved in chitin synthesis in Saccharomyces cerevisiae

Background

The identification of disease-associated genes using single nucleotide polymorphisms (SNPs) has been increasingly reported. In particular, the Affymetrix Mapping 10 K SNP microarray platform uses one PCR primer to amplify the DNA samples and determine the genotype of more than 10,000 SNPs in the human genome. This provides the opportunity for large scale, rapid and cost-effective genotyping assays for linkage analysis. However, the analysis of such datasets is nontrivial because of the large number of markers, and visualizing the linkage scores in the context of genome maps remains less automated using the current linkage analysis software packages. For example, the haplotyping results are commonly represented in the text format.

Results

Here we report the development of a novel software tool called CompareLinkage for automated formatting of the Affymetrix Mapping 10 K genotype data into the "Linkage" format and the subsequent analysis with multi-point linkage software programs such as Merlin and Allegro. The new software has the ability to visualize the results for all these programs in dChip in the context of genome annotations and cytoband information. In addition we implemented a variant of the Lander-Green algorithm in the dChipLinkage module of dChip software (V1.3) to perform parametric linkage analysis and haplotyping of SNP array data. These functions are integrated with the existing modules of dChip to visualize SNP genotype data together with LOD score curves. We have analyzed three families with recessive and dominant diseases using the new software programs and the comparison results are presented and discussed.

Conclusions

The CompareLinkage and dChipLinkage software packages are freely available. They provide the visualization tools for high-density oligonucleotide SNP array data, as well as the automated functions for formatting SNP array data for the linkage analysis programs Merlin and Allegro and calling these programs for linkage analysis. The results can be visualized in dChip in the context of genes and cytobands. In addition, a variant of the Lander-Green algorithm is provided that allows parametric linkage analysis and haplotyping.     

Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations

Background  

During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have appeared in the scientific literature. Most of these methods utilize molecular markers for the inferences, while some are also capable of handling DNA sequence data. In a number of earlier works, we have introduced an array of statistical methods for population genetic inference that are implemented in the software BAPS. However, the complexity of biological problems related to genetic structure analysis keeps increasing such that in many cases the current methods may provide either inappropriate or insufficient solutions.     

MatGAT: An application that generates similarity/identity matrices using protein or DNA sequences

Background  

The rapid increase in the amount of protein and DNA sequence information available has become almost overwhelming to researchers. So much information is now accessible that high-quality, functional gene analysis and categorization has become a major goal for many laboratories. To aid in this categorization, there is a need for non-commercial software that is able to both align sequences and also calculate pairwise levels of similarity/identity.