R/Bioconductor在Affymetrix表达芯片中的应用

R是用于统计计算和数据作图的编程语言和程序设计环境,能在多种平台下编译和运行。Bioconductor也是免费开源的程序设计环境,它主要基于统计编程语言R,用于基因组数据的分析。我们通过已发表的数据,包含斑马鱼心肌再生的生物芯片数据,分析源码实例,较为详细地介绍和讲解了R/BioConductor的用法,为推广优秀的免费统计软件提供了一个简单的中文使用手册。     

基于Cygwin实现生物信息学软件从Unix/Linux向Windows移植

Cygwin可在Windows环境下提供对Unix/Linux环境的模拟与支持,具有较为完善的Unix/Linux工具包和编程环境。利用Cygwin对常用的生物信息学数据分析软件如Sim4、FASTA、Phred/Phrap/RepeatMasker、EMBOSS、HMMER和ClustalW等进行重新编译,发现通过该方式能够获得可在Windows环境下运行的可执行代码,为利用Windows环境优势的同时进行跨平台生物信息学数据分析平台的开发提供重要参考价值。     

Windows下16S rRNA基因扩增子测序数据分析的简易流程

微生物组数据分析需要掌握Linux系统操作,这对缺乏计算机知识的生物研究人员是一个很大的障碍。为此我们设计了一套在Windows的Linux子系统(WSL)下分析16S rRNA基因扩增子高通量测序数据的简易流程。本流程整合常用的开源软件VSEARCH与QIIME等,能对16S rRNA测序数据进行质量控制、OTU聚类、多样性分析及结果可视化呈现。以唾液微生物组分析为例,详细介绍从原始数据到多样性统计分析过程的参数和命令,及结果解读。教学实践证明,此流程易于学习,并有助于掌握微生物组的基本概念与方法。利用Windows系统最新的WSL功能,本流程方便Windows用户使用大量在Linux上运行的生物信息工具,有助于促进微生物组研究的发展。流程的安装程序与测序数据可从网址(http://www. ligene. cn/win16s/)免费下载使用。     

MorphoJ: an integrated software package for geometric morphometrics

Increasingly, data on shape are analysed in combination with molecular genetic or ecological information, so that tools for geometric morphometric analysis are required. Morphometric studies most often use the arrangements of morphological landmarks as the data source and extract shape information from them by Procrustes superimposition. The MorphoJ software combines this approach with a wide range of methods for shape analysis in different biological contexts. The program offers an integrated and user-friendly environment for standard multivariate analyses such as principal components, discriminant analysis and multivariate regression as well as specialized applications including phylogenetics, quantitative genetics and analyses of modularity in shape data. MorphoJ is written in Java and versions for the Windows, Macintosh and Unix/Linux platforms are freely available from http://www.flywings.org.uk/MorphoJ_page.htm.     

SNPCEQer II: the integrated detection and analysis of SNPs in DNA sequences

SNPCEQer II is a graphical user interface (GUI)-based application that integrates single nucleotide polymorphism (SNP) detection, SNP analysis and SNP editing in the Microsoft Windows (R) environment. SNPCEQer II detects SNPs in DNA sequences generated by the Beckman CEQ TM 2000 XL DNA analysis system. It provides tools to analyse SNPs by inspecting and comparing trace data (chromatograms) around putative SNPs with that of other related DNA sequences, and it can search for those SNPs in the National Center for Biotechnology Information (NCBI) databases. SNPCEQer II can determine the mutation type of a coding SNP and generate data for submission to the dbSNP database. The SNP report can be edited and printed, as can the chromatograms. SNPCEQer II is implemented in Visual C++.     

Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST)

Background  

BLAST is one of the most common and useful tools for Genetic Research. This paper describes a software application we have termed Windows .NET Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST), which enhances the BLAST utility by improving usability, fault recovery, and scalability in a Windows desktop environment. Our goal was to develop an easy to use, fault tolerant, high-throughput BLAST solution that incorporates a comprehensive BLAST result viewer with curation and annotation functionality.     

Validation of a computer software program for statistical analysis of accelerated stability studies on biological standards.

Long-term stability is an essential requirement for biological measurement standards and it has been evaluated by applying the Arrhenius model to the data obtained from accelerated thermostability studies. A computer program DEGTEST suited to a mainframe computer has been used for evaluating the stability of biological standards for more than a decade. This paper describes the validation of a computer program executable in a personal computer Microsoft Windows XP environment for the analysis of accelerated thermostability study data.     

Analysis for free: comparing programs for sequence analysis

Programs to import, manage and align sequences and to analyse the properties of DNA, RNA and proteins are essential for every biological laboratory. This review describes two different freeware (BioEdit and pDRAW for MS Windows) and a commercial program (Sequencher for MS Windows and Apple MacOS). Bioedit and Sequencher offer functions such as sequence alignment and editing plus reading of sequence trace files. pDRAW is a very comfortable visualisation tool with a variety of analysis functions. While Sequencher impresses with a very user-friendly interface and easy-to-use tools, BioEdit offers the largest and most customisable variety of tools. The strength of pDRAW is drawing and analysis of single sequences for priming and restriction sites and virtual cloning. It has a database function for user-specific oligonucleotides and restriction enzymes.     

Chronomics analysis toolkit (CATkit)

Chronomics, and the study of biological rhythms, is a rapidly growing area of study. As biological researchers transition to awareness of the impact biological oscillators have on experimental outcomes, and the need to design experiments around genetic, molecular, physiological, and behavioral rhythms, there is increasing need to identify and characterize rhythmicity. There is a corresponding increase in demand for accessible software tools to analyze data for rhythms, both macroscopically and quantitatively. The chronomics analysis toolkit (CATkit), an R package for analysis of periodicities in time series, is a free and open source suite of rhythm analysis tools that runs on UNIX, Windows, and Macintosh platforms. It is particularly well suited to the often scarce, frequently noisy, biological data, and is also applicable to long and/or denser records. CATkit includes a variety of tools, providing visualization and inspection tools to aid in determining whether data meet key assumptions for analysis; as well as quantitative assessment, by cosinor, of mean, amplitude and phase at an assumed period (or periods), with a measure of uncertainty for each parameter.     

Diving in uncharted waters: An updated genetics toolkit highlights the challenges of polyploidy in landscape genomics analyses

As molecular ecologists, we have by necessity become adept at working across computational platforms. A diverse community of scientists has developed a broad array of analytical resources spanning command line to graphical user interface across Linux, Mac, and Windows environments and a dizzying array of program‐specific input formats. In light of this, we often explore our data like free divers – filling our lungs with air and descending for a short period of time into one part of our data set before resurfacing, reformatting, and preparing for our next analysis. In this issue of Molecular Ecology Resources, Meirmans (2020) presents an updated version of GenoDive, a program with a toolkit that provides users with the opportunity to stay a while and delve deeper into the diverse portfolio of information provided by a genomic data set. The comprehensive nature of GenoDive coupled with its unique capability to handle both diploid and polyploid data also provides an opportunity to reflect on the unevenness of resources available for the analysis of polyploid versus diploid data. Since new updates include the addition of plug‐ins for genotype‐environment association analyses, we limit the observations presented here to the common tools used for landscape genomics analyses.     

SLControl: PC-based data acquisition and analysis for muscle mechanics

SLControl is a computerized data acquisition and analysis system that was developed in our laboratory to help perform mechanical experiments using striated muscle preparations. It consists of a computer program (Windows 2000 or later) and a commercially available data acquisition board (16-bit resolution, DAP5216a, Microstar Laboratories, Bellevue, WA). Signals from the user's existing equipment representing force, fiber length (FL), and (if desired) sarcomere length (SL) are connected to the system through standard Bayonet Neill Concelman cables and saved to data files for later analysis. Output signals from the board control FL and trigger additional equipment, e.g., flash lamps. Windows dialogs drive several different experimental protocols, including slack tests and rate of tension recovery measurements. Precise measurements of muscle stiffness and force velocity/power characteristics can also be accomplished using SL and tension control, respectively. In these situations, the FL command signal is updated in real time (at rates > or =2.5 kHz) in response to changes in the measured SL or force signals. Data files can be exported as raw text or analyzed within SLControl with the use of built-in tools for cursor analysis, digital filtering, curve fitting, etc. The software is available for free download at http://www.slcontrol.com.     

TOPPAS: a graphical workflow editor for the analysis of high-throughput proteomics data

Mass spectrometry coupled to high-performance liquid chromatography (HPLC-MS) is evolving more quickly than ever. A wide range of different instrument types and experimental setups are commonly used. Modern instruments acquire huge amounts of data, thus requiring tools for an efficient and automated data analysis. Most existing software for analyzing HPLC-MS data is monolithic and tailored toward a specific application. A more flexible alternative consists of pipeline-based tool kits allowing the construction of custom analysis workflows from small building blocks, e.g., the Trans Proteomics Pipeline (TPP) or The OpenMS Proteomics Pipeline (TOPP). One drawback, however, is the hurdle of setting up complex workflows using command line tools. We present TOPPAS, The OpenMS Proteomics Pipeline ASsistant, a graphical user interface (GUI) for rapid composition of HPLC-MS analysis workflows. Workflow construction reduces to simple drag-and-drop of analysis tools and adding connections in between. Integration of external tools into these workflows is possible as well. Once workflows have been developed, they can be deployed in other workflow management systems or batch processing systems in a fully automated fashion. The implementation is portable and has been tested under Windows, Mac OS X, and Linux. TOPPAS is open-source software and available free of charge at http://www.OpenMS.de/TOPPAS .     

SpotWhatR: a user-friendly microarray data analysis system

SpotWhatR is a user-friendly microarray data analysis tool that runs under a widely and freely available R statistical language (http://www.r-project.org) for Windows and Linux operational systems. The aim of SpotWhatR is to help the researcher to analyze microarray data by providing basic tools for data visualization, normalization, determination of differentially expressed genes, summarization by Gene Ontology terms, and clustering analysis. SpotWhatR allows researchers who are not familiar with computational programming to choose the most suitable analysis for their microarray dataset. Along with well-known procedures used in microarray data analysis, we have introduced a stand-alone implementation of the HTself method, especially designed to find differentially expressed genes in low-replication contexts. This approach is more compatible with our local reality than the usual statistical methods. We provide several examples derived from the Blastocladiella emersonii and Xylella fastidiosa Microarray Projects. SpotWhatR is freely available at http://blasto.iq.usp.br/~tkoide/SpotWhatR, in English and Portuguese versions. In addition, the user can choose between "single experiment" and "batch processing" versions.     

Anvaya: a workflows environment for automated genome analysis

Anvaya is a workflow environment for automated genome analysis that provides an interface for several bioinformatics tools and databases, loosely coupled together in a coordinated system, enabling the execution of a set of analyses tools in series or in parallel. It is a client-server workflow environment that has an advantage over existing software as it enables extensive pre & post processing of biological data in an efficient manner. "Anvaya" offers the user, novel functionalities to carry out exhaustive comparative analysis via "custom tools," which are tools with new functionality not available in standard tools, and "built-in PERL parsers," which automate data-flow between tools that hitherto, required manual intervention. It also provides a set of 11 pre-defined workflows for frequently used pipelines in genome annotation and comparative genomics ranging from EST assembly and annotation to phylogenetic reconstruction and microarray analysis. It provides a platform that serves as a single-stop solution for biologists to carry out hassle-free and comprehensive analysis, without being bothered about the nuances involved in tool installation, command line parameters, format conversions required to connect tools and manage/process multiple data sets at a single instance.     

Retriever and CompareTable, two informatics tools for data analysis of high-density oligonucleotide arrays.

High-density oligonucleotide arrays are widely employed for detecting global changes in gene expression profiles of cells or tissues exposed to specific stimuli. Presented with large amounts of data, investigators can spend significant amounts of time analyzing and interpreting this array data. In our application of GeneChip arrays to analyze changes in gene expression in viral-infected epithelium, we have needed to develop additional computational tools that may be of utility to other investigators using this methodology. Here, I describe two executable programs to facilitate data extraction and multiple data point analysis. These programs run in a virtual DOS environment on Microsoft Windows 95/98/2K operating systems on a desktop PC. Both programs can be freely downloaded from the BioTechniques Software Library (www.BioTechniques.com). The first program, Retriever, extracts primary data from an array experiment contained in an Affymetrix textfile using user-inputted individual identification strings (e.g., the probe set identification numbers). With specific data retrieved for individual genes, hybridization profiles can be examined and data normalized. The second program, CompareTable, is used to facilitate comparison analysis of two experimental replicates. CompareTable compares two lists of genes, identifies common entries, extracts their data, and writes an output text file containing only those genes present in both of the experiments. The output files generated by these two programs can be opened and manipulated by any software application recognizing tab-delimited text files (e.g., Microsoft NotePad or Excel).     

Flapjack--graphical genotype visualization

SUMMARY: New software tools for graphical genotyping are required that can routinely handle the large data volumes generated by the high-throughput single-nucleotide polymorphism (SNP) platforms, genotyping-by-sequencing and other comparable genotyping technologies. Flapjack has been developed to facilitate analysis of these data, providing real time rendering with rapid navigation and comparisons between lines, markers and chromosomes, with visualization, sorting and querying based on associated data, such as phenotypes, quantitative trait loci or other mappable features. AVAILABILITY: Flapjack is freely available for Microsoft Windows, Mac OS X, Linux and Solaris, and can be downloaded from http://bioinf.scri.ac.uk/flapjack .     

The collaboratory for MS3D: a new cyberinfrastructure for the structural elucidation of biological macromolecules and their assemblies using mass spectrometry-based approaches

Modern biomedical research is evolving with the rapid growth of diverse data types, biophysical characterization methods, computational tools and extensive collaboration among researchers spanning various communities and having complementary backgrounds and expertise. Collaborating researchers are increasingly dependent on shared data and tools made available by other investigators with common interests, thus forming communities that transcend the traditional boundaries of the single research laboratory or institution. Barriers, however, remain to the formation of these virtual communities, usually due to the steep learning curve associated with becoming familiar with new tools, or with the difficulties associated with transferring data between tools. Recognizing the need for shared reference data and analysis tools, we are developing an integrated knowledge environment that supports productive interactions among researchers. Here we report on our current collaborative environment, which focuses on bringing together structural biologists working in the area of mass spectrometric based methods for the analysis of tertiary and quaternary macromolecular structures (MS3D) called the Collaboratory for MS3D (C-MS3D). C-MS3D is a Web-portal designed to provide collaborators with a shared work environment that integrates data storage and management with data analysis tools. Files are stored and archived along with pertinent meta data in such a way as to allow file handling to be tracked (data provenance) and data files to be searched using keywords and modification dates. While at this time the portal is designed around a specific application, the shared work environment is a general approach to building collaborative work groups. The goal of this is to not only provide a common data sharing and archiving system, but also to assist in the building of new collaborations and to spur the development of new tools and technologies.     

The Gaggle: An open-source software system for integrating bioinformatics software and data sources

Background  

Systems biologists work with many kinds of data, from many different sources, using a variety of software tools. Each of these tools typically excels at one type of analysis, such as of microarrays, of metabolic networks and of predicted protein structure. A crucial challenge is to combine the capabilities of these (and other forthcoming) data resources and tools to create a data exploration and analysis environment that does justice to the variety and complexity of systems biology data sets. A solution to this problem should recognize that data types, formats and software in this high throughput age of biology are constantly changing.     

MIPortal: a high capacity server for molecular imaging research

The introduction of novel molecular tools in research and clinical medicine has created a need for more refined information management systems. This article describes the design and implementation of such a new information platform: the Molecular Imaging Portal (MIPortal). The platform was created to organize, archive, and rapidly retrieve large datasets using Web-based browsers as access points. The system has been implemented in a heterogeneous, academic research environment serving Macintosh, Unix, and Microsoft Windows clients and has been shown to be extraordinarily robust and versatile. In addition, it has served as a useful tool for clinical trials and collaborative multi-institutional small-animal imaging research.     

DNA array analysis in a Microsoft Windows environment.

Microsoft Windows-based computers have evolved to the point that they provide sufficient computational and visualization power for robust analysis of DNA array data. In fact, smaller laboratories might prefer to carry out some or all of their analyses and visualization in a Windows environment, rather than alternative platforms such as UNIX. We have developed a series of manually executed macros written in Visual Basic for Microsoft Excel spreadsheets, that allows for rapid and comprehensive gene expression data analysis. The first macro assigns gene names to spots on the DNA array and normalizes individual hybridizations by expressing the signal intensity for each gene as a percentage of the sum of all gene intensities. The second macro streamlines statistical consideration of the confidence in individual gene measurements for sets of experimental replicates by calculating probability values with the Student's t test. The third macro introduces a threshold value, calculates expression ratios between experimental conditions, and calculates the standard deviation of the mean of the log ratio values. Selected columns of data are copied by a fourth macro to create a processed data set suitable for entry into a Microsoft Access database. An Access database structure is described that allows simple queries across multiple experiments and export of data into third-party data visualization software packages. These analysis tools can be used in their present form by others working with commercial E. coli membrane arrays, or they may be adapted for use with other systems. The Excel spreadsheets with embedded Visual Basic macros and detailed instructions for their use are available at http://www.ou.edu/microarray.