MapDraw，在Excel中绘制遗传连锁图的宏

MAPMAKER是现今广泛使用的遗传连锁数据分析软件,然而其广泛使用的DOS版本却不具有连锁图绘制功能,给连锁作图工作带来了相当大的麻烦。为了解决这一问题,我们以大家广泛使用的数据处理软件Microsoft Excel为平台,编写了一个Excel宏——MapDraw来在轻松的操作中实现遗传连锁图的绘制。 Abstract:MAPMAKER is one of the most widely used computer software package for constructing genetic linkage maps.However,the PC version,MAPMAKER 3.0 for PC,could not draw the genetic linkage maps that its Macintosh version,MAPMAKER 3.0 for Macintosh,was able to do.Especially in recent years,Macintosh computer is much less popular than PC.Most of the geneticists use PC to analyze their genetic linkage data.So a new computer software to draw the same genetic linkage maps on PC as the MAPMAKER for Macintosh to do on Macintosh has been crying for.Microsoft Excel,one component of Microsoft Office package,is one of the most popular software in laboratory data processing.Microsoft Visual Basic for Applications (VBA) is one of the most powerful functions of Microsoft Excel.Using this program language,we can take creative control of Excel,including genetic linkage map construction,automatic data processing and more.In this paper,a Microsoft Excel macro called MapDraw is constructed to draw genetic linkage maps on PC computer based on given genetic linkage data.Use this software,you can freely construct beautiful genetic linkage map in Excel and freely edit and copy it to Word or other application.This software is just an Excel format file.You can freely copy it from ftp://211.69.140.177 or ftp://brassica.hzau.edu.cn and the source code can be found in Excel′s Visual Basic Editor.     

Microarray data analysis made easy

DNA microarrays are valuable tools for analyzing global gene expression. Because of the increasing popularity and the large volume of data produced, tools for facile microarray data analysis are essential. FiRe, a recently introduced computer program, has now solved the seemingly insuperable discrepancy between simplicity and evaluation of DNA microarray data. The program is available as a macro for the popular Microsoft Office Excel software and is user-friendly, interactive, versatile and platform-independent, paving the way for a further push in the evaluation of DNA microarrays.     

Spreadsheet-based program for alignment of overlapping DNA sequences.

Molecular biology laboratories frequently face the challenge of aligning small overlapping DNA sequences derived from a long DNA segment. Here, we present a short program that can be used to adapt Excel spreadsheets as a tool for aligning DNA sequences, regardless of their orientation. The program runs on any Windows or Macintosh operating system computer with Excel 97 or Excel 98. The program is available for use as an Excel file, which can be downloaded from the BioTechniques Web site. Upon execution, the program opens a specially designed customized workbook and is capable of identifying overlapping regions between two sequence fragments and displaying the sequence alignment. It also performs a number of specialized functions such as recognition of restriction enzyme cutting sites and CpG island mapping without costly specialized software.     

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.     

Excel在药学数据分析工作中的应用

目的：采用常用的电子表格处理系统Microsoft Excel解决药学实验过程中遇到的数据分析问题。方法：应用工作表函数中内置的统计函数,以线性回归为例说明源数据的输入与结果返回的具体操作过程;对数据分析工具中的＂描述统计＂工具、t检验与方差分析,结合具体实例对药学实践中遇到的药学统计实际问题进行综合探讨。结果：用Excel表中内置的统计函数工具进行线性回归分析,方法简单、结果可靠;Excel表中的数据分析工具适用于日常药学实验数据分析过程中遇到的描述统计分析、t检验与方差分析。Excel与其它数据处理软件相比具有操作快捷、使用方便、计算精确、易于学习与掌握等优点。结论：Excel友好的界面,清晰的统计分析结果,使医药工作者在使用Excel的数据分析软件时会感到非常的方便快捷,灵活实用,值得在药学实践中应用推广。     

Uncertainty in Measurement: A Review of Monte Carlo Simulation Using Microsoft Excel for the Calculation of Uncertainties Through Functional Relationships,Including Uncertainties in Empirically Derived Constants

The Guide to the Expression of Uncertainty in Measurement (usually referred to as the GUM) provides the basic framework for evaluating uncertainty in measurement. The GUM however does not always provide clearly identifiable procedures suitable for medical laboratory applications, particularly when internal quality control (IQC) is used to derive most of the uncertainty estimates. The GUM modelling approach requires advanced mathematical skills for many of its procedures, but Monte Carlo simulation (MCS) can be used as an alternative for many medical laboratory applications. In particular, calculations for determining how uncertainties in the input quantities to a functional relationship propagate through to the output can be accomplished using a readily available spreadsheet such as Microsoft Excel.The MCS procedure uses algorithmically generated pseudo-random numbers which are then forced to follow a prescribed probability distribution. When IQC data provide the uncertainty estimates the normal (Gaussian) distribution is generally considered appropriate, but MCS is by no means restricted to this particular case. With input variations simulated by random numbers, the functional relationship then provides the corresponding variations in the output in a manner which also provides its probability distribution. The MCS procedure thus provides output uncertainty estimates without the need for the differential equations associated with GUM modelling.The aim of this article is to demonstrate the ease with which Microsoft Excel (or a similar spreadsheet) can be used to provide an uncertainty estimate for measurands derived through a functional relationship. In addition, we also consider the relatively common situation where an empirically derived formula includes one or more ‘constants’, each of which has an empirically derived numerical value. Such empirically derived ‘constants’ must also have associated uncertainties which propagate through the functional relationship and contribute to the combined standard uncertainty of the measurand.     

Assessing the Reliability of Amplified RNA Used in Microarrays

A certain minimal amount of RNA from biological samples is necessary to perform a microarray experiment with suitable replication. In some cases, the amount of RNA available is insufficient, necessitating RNA amplification prior to target synthesis. However, there is some uncertainty about the reliability of targets that have been generated from amplified RNA, because of nonlinearity and preferential amplification. This current work develops a straightforward strategy to assess the reliability of microarray data obtained from amplified RNA. The tabular method we developed, which utilises a Down-Up-Missing-Below (DUMB) classification scheme, shows that microarrays generated with amplified RNA targets are reliable within constraints. There was an increase in false negatives because of the need for increased filtering. Furthermore, this analysis method is generic and can be broadly applied to evaluate all microarray data. A copy of the Microsoft Excel spreadsheet is available upon request from Edward Bearden.     

江苏省南通市农村生物质能资源潜力估算及地区分布

摸清农村生物质能资源潜力对南通市农村能源建设具有重大意义。以南通市为实证区域,利用草谷比、收集系数、折标系数、副产物系数并根据南通市可能源化利用的实际情况,从县域层面较为全面地估算了包括秸秆、农业加工副产品、人畜粪便等可能源化利用的生物质能资源总量。估算结果表明:(1)南通市每年提供的可能源化利用秸秆资源量约为105万t标煤,以稻秸、麦秸和油菜秸为主;农业加工副产品资源量约为20万t标煤,以稻壳、玉米芯、棉籽等为主;人禽粪便资源量为108万t标煤,以猪粪和禽粪为主,约占到资源总量的1/2。(2)南通市拥有较为丰富的生物质能资源,其中可能源化利用的生物质资源总量为年均233万t标煤,并且其资源总量呈增长趋势;预计在短期内其资源总量将增加到240万t标煤。(3)南通市生物质资源的地区分布极不均匀,从生物质能资源总量、单位国土面积生物质能资源量、人均生物质能资源量看,海安县、如东县和如皋市等经济比较薄弱的县市均具有明显优势,其中海安县在南通各县市中凭借其规模渐增的养殖业、种植业产生的生物质资源而遥遥领先;此外如东县的秸秆资源也具有重要地位。(4)南通市生物质资源的季节分布也不均匀,这种季节分布不均主要是由秸秆资源引起的,因为秸秆资源主要集中在秋季和春季,约占到60%—75%;而夏季和冬季则很少。这就给农村能源的持续开发利用带来一定难度。建议:需要针对各县市的生物质能开发利用的实际情况因地制宜合理开发生物质资源,科学布局避免恶性竞争,并及时做好秸秆资源的收集、转运与储存工作以避免资源的浪费和严重的环境污染,从而促进南通农村能源建设的健康发展。     

红壤微生物量在土壤—黑麦草系统中的肥力意义

研究了红壤微生物量与土壤养分循环及植物生长的内在联系．结果表明,红壤微生物量不仅与土壤有机碳、全氮、有效氮等显著相关,而且与植物干物质产量及吸Ｎ 量也存在着良好的相关性,可作为指示红壤肥力水平和作物产量的重要指标．试验测得的红壤微生物量Ｎ 周转期较短,每年通过微生物周转的Ｎ 素达到微生物量氮含量的１ ．５ 倍到数倍．     

Kgtests: a simple Excel Macro program to detect signatures of population expansion using microsatellites

A simple Microsoft Excel Macro application (kgtests) that performs the k and g tests for detecting population expansion is described. The application, being an Excel Macro, facilitates the ease of preparation of the input file and makes it possible to use the application in any machine that can run Excel.     

MAD: a suite of tools for microarray data management and processing

SUMMARY: Microarray data management and processing (MAD) is a set of Windows integrated software for microarray analysis. It consists of a relational database for data storage with many user-interfaces for data manipulation, several text file parsers and Microsoft Excel macros for automation of data processing, and a generator to produce text files that are ready for cluster analysis. AVAILABILITY: Executable is available free of charge on http://pompous.swmed.edu. The source code is also available upon request.     

Predicting savanna vegetation structure on the basis of plant available moisture (PAM) and plant available nutrients (PAN): a case study from Australia

The use of the plant available moisture (PAM)/plant available nutrients (PAN) concept to compare savanna structure was examined using data from twenty Australian sites. Above-ground biomass was regressed on various combinations of seventeen different estimates of PAM (plant available moisture) and two estimates of PAN (plant available nutrients). The ratios of actual transpirational loss from the subsoil to potential evapotranspiration (PET), and total annual rainfall to PET, were most highly correlated with total biomass. Grass biomass is poorly predicted by PAM on its own, and requires inclusion of woody leaf biomass in the regression. PAN had little effect on total biomass, although it is likely to be important for other, functional aspects of vegetation. The woody : grass ratio is best predicted by an index involving the ratio of subsoil : topsoil moisture. For biomass comparisons the use of a detailed water-balance model to estimate PAM is not warranted.     

Equilibrium expert: an add-in to Microsoft Excel for multiple binding equilibrium simulations and parameter estimations

An add-in to Microsoft Excel was developed to simulate multiple binding equilibriums. A partition function, readily written even when the equilibrium is complex, describes the experimental system. It involves the concentrations of the different free molecular species and of the different complexes present in the experiment. As a result, the software is not restricted to a series of predefined experimental setups but can handle a large variety of problems involving up to nine independent molecular species. Binding parameters are estimated by nonlinear least-square fitting of experimental measurements as supplied by the user. The fitting process allows user-defined weighting of the experimental data. The flexibility of the software and the way it may be used to describe common experimental situations and to deal with usual problems such as tracer reactivity or nonspecific binding is demonstrated by a few examples. The software is available free of charge upon request.     

MetaQuant: a tool for the automatic quantification of GC/MS-based metabolome data

MetaQuant is a Java-based program for the automatic and accurate quantification of GC/MS-based metabolome data. In contrast to other programs MetaQuant is able to quantify hundreds of substances simultaneously with minimal manual intervention. The integration of a self-acting calibration function allows the parallel and fast calibration for several metabolites simultaneously. Finally, MetaQuant is able to import GC/MS data in the common NetCDF format and to export the results of the quantification into Systems Biology Markup Language (SBML), Comma Separated Values (CSV) or Microsoft Excel (XLS) format. AVAILABILITY: MetaQuant is written in Java and is available under an open source license. Precompiled packages for the installation on Windows or Linux operating systems are freely available for download. The source code as well as the installation packages are available at http://bioinformatics.org/metaquant     

NormalizeMets: assessing,selecting and implementing statistical methods for normalizing metabolomics data

Introduction

In metabolomics studies, unwanted variation inevitably arises from various sources. Normalization, that is the removal of unwanted variation, is an essential step in the statistical analysis of metabolomics data. However, metabolomics normalization is often considered an imprecise science due to the diverse sources of variation and the availability of a number of alternative strategies that may be implemented.

Objectives

We highlight the need for comparative evaluation of different normalization methods and present software strategies to help ease this task for both data-oriented and biological researchers.

Methods

We present NormalizeMets—a joint graphical user interface within the familiar Microsoft Excel and freely-available R software for comparative evaluation of different normalization methods. The NormalizeMets R package along with the vignette describing the workflow can be downloaded from https://cran.r-project.org/web/packages/NormalizeMets/. The Excel Interface and the Excel user guide are available on https://metabolomicstats.github.io/ExNormalizeMets.

Results

NormalizeMets allows for comparative evaluation of normalization methods using criteria that depend on the given dataset and the ultimate research question. Hence it guides researchers to assess, select and implement a suitable normalization method using either the familiar Microsoft Excel and/or freely-available R software. In addition, the package can be used for visualisation of metabolomics data using interactive graphical displays and to obtain end statistical results for clustering, classification, biomarker identification adjusting for confounding variables, and correlation analysis.

Conclusion

NormalizeMets is designed for comparative evaluation of normalization methods, and can also be used to obtain end statistical results. The use of freely-available R software offers an attractive proposition for programming-oriented researchers, and the Excel interface offers a familiar alternative to most biological researchers. The package handles the data locally in the user’s own computer allowing for reproducible code to be stored locally.

     

SNUFER: A software for localization and presentation of single nucleotide polymorphisms using a Clustal multiple sequence alignment output file

SNUFER is a software for the automatic localization and generation of tables used for the presentation of single nucleotide polymorphisms (SNPs). After input of a fasta file containing the sequences to be analyzed, a multiple sequence alignment is generated using ClustalW ran inside SNUFER. The ClustalW output file is then used to generate a table which displays the SNPs detected in the aligned sequences and their degree of similarity. This table can be exported to Microsoft Word, Microsoft Excel or as a single text file, permitting further editing for publication. The software was written using Delphi 7 for programming and FireBird 2.0 for sequence database management. It is freely available for noncommercial use and can be downloaded from http://www.heranza.com.br/bioinformatica2.htm.     

A modern tool for classical plant growth analysis

We present an all-inclusive software tool for dealing with the essential core of mathematical and statistical calculations in plant growth analysis. The tool calculates up to six of the most fundamental growth parameters according to a purely 'classical' approach across one harvest-interval. All of the estimates carry standard errors and 95 % confidence limits. The tool is written in Microsoft Excel 2000 and is available free of charge for use in teaching and research from www.aob.oupjournals.org article supplementary data.     

江苏省能源农业发展的资源现状与发展潜力

在讨论江苏省农村生物质类型和资源总量的基础上,利用已有统计资料和数据,对江苏省能源农业发展的资源基础现状进行定量的估算,并通过对发展能源农业的种质和可利用土地、江苏省农业和畜牧业发展态势的分析研究,对江苏省能源农业的发展潜力进行了预测.研究表明,2006年江苏省农村生物质能总蕴藏量和可利用量折合标准煤分别达到14238.06万t和2311.54万t.到2010年和2015年,江苏省农村生物质能资源量折合标准煤将分别达到5390万t和6109万t.     

生物质调理剂对川西北高寒草地沙化土壤养分和微生物群落特征的影响

将农牧废弃物进行资源化处置制成生物质调理剂,用于沙化土壤改良是目前川西北沙化草地生态治理的有效途径之一.为了阐明不同原料调理剂在川西北高寒沙化草地上的实际应用效果,本研究以不施用调理剂为对照(CK),设置施用量均为12 t·hm-2的菌渣(JZ)、秸秆(JG)和生物炭(SWT)3种调理剂,分析了调理剂施用对土壤养分和微...