Alignment of Escherichia coli K12 DNA sequences to a genomic restriction map.

We use the extensive published information describing the genome of Escherichia coli and new restriction map alignment software to align DNA sequence, genetic, and physical maps. Restriction map alignment software is used which considers restriction maps as strings analogous to DNA or protein sequences except that two values, enzyme name and DNA base address, are associated with each position on the string. The resulting alignments reveal a nearly linear relationship between the physical and genetic maps of the E. coli chromosome. Physical map comparisons with the 1976, 1980, and 1983 genetic maps demonstrate a better fit with the more recent maps. The results of these alignments are genomic kilobase coordinates, orientation and rank of the alignment that best fits the genetic data. A statistical measure based on extreme value distribution is applied to the alignments. Additional computer analyses allow us to estimate the accuracy of the published E. coli genomic restriction map, simulate rearrangements of the bacterial chromosome, and search for repetitive DNA. The procedures we used are general enough to be applicable to other genome mapping projects.     

A feasible and automatic free tool for T1 and ECV mapping

PurposeCardiac magnetic resonance (CMR) is a useful non-invasive tool for characterizing tissues and detecting myocardial fibrosis and edema. Estimation of extracellular volume fraction (ECV) using T1 sequences is emerging as an accurate biomarker in cardiac diseases associated with diffuse fibrosis. In this study, automatic software for T1 and ECV map generation consisting of an executable file was developed and validated using phantom and human data.MethodsT1 mapping was performed in phantoms and 30 subjects (22 patients and 8 healthy subjects) on a 1.5T MR scanner using the modified Look-Locker inversion-recovery (MOLLI) sequence prototype before and 15 min after contrast agent administration. T1 maps were generated using a Fast Nonlinear Least Squares algorithm. Myocardial ECV maps were generated using both pre- and post-contrast T1 image registration and automatic extraction of blood relaxation rates.ResultsUsing our software, pre- and post-contrast T1 maps were obtained in phantoms and healthy subjects resulting in a robust and reliable quantification as compared to reference software. Coregistration of pre- and post-contrast images improved the quality of ECV maps. Mean ECV value in healthy subjects was 24.5% ± 2.5%.ConclusionsThis study demonstrated that it is possible to obtain accurate T1 maps and informative ECV maps using our software. Pixel-wise ECV maps obtained with this automatic software made it possible to visualize and evaluate the extent and severity of ECV alterations.     

Automated ordering of fingerprinted clones

MOTIVATION: A considerable amount of human intervention is currently required to produce high-quality fingerprint-based physical maps for genomic studies. RESULTS: An algorithm has been developed and implemented to automatically order fingerprinted clones within contigs. The resulting software, named CORAL (Clone ORdering ALgorithm), has been tested on maps that have previously been manually edited and on maps derived from in silico simulations. The fingerprint map and DNA sequence of the human genome has provided an additional test to CORAL. Measurements suggest that CORAL performs significantly better than the software currently used by most laboratories to order fingerprinted clones at throughputs far exceeding those that can be achieved manually.     

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.     

冷冻电镜密度图可视化软件VAT4M

基于冷冻电镜三维密度图的特征分析,研究开发了冷冻电镜密度图可视化软件VAT4M(Visual Analysis Tools for Macro-Molecule Map and Model),实现了对三维冷冻电镜密度图的可视化分析,其主要功能包括密度图和分子模型的可视化、密度图的分割和晶体结构在密度图中的匹配。在可视化方面,在实现等值面可视化方法的同时还实现了体绘制可视化模式。对于结构分析,VAT4M提供了自动分割工具,和所见即所得的分割浏览器。同时,VAT4M还提供了极值吸收法与梯度法相结合的自动匹配方法,而且,对于具有对称性的密度图,可根据一个亚基的匹配结果,迅速得到其准原子模型。最后给出了若干应用实例。实验表明,本平台对冷冻电镜密度数据具有良好的可视与分析功能。     

PentaPlot: A software tool for the illustration of genome mosaicism

Background  

Dekapentagonal maps depict the phylogenetic relationships of five genomes in a visually appealing diagram and can be viewed as an alternative to a single evolutionary consensus tree. In particular, the generated maps focus attention on those gene families that significantly deviate from the consensus or plurality phylogeny. PentaPlot is a software tool that computes such dekapentagonal maps given an appropriate probability support matrix.     

SMOOTH: a statistical method for successful removal of genotyping errors from high-density genetic linkage data

High-density genetic linkage maps can be used for purposes such as fine-scale targeted gene cloning and anchoring of physical maps. However, their construction is significantly complicated by even relatively small amounts of scoring errors. Currently available software is not able to solve the ordering ambiguities in marker clusters, which inhibits the application of high-density maps. A statistical method named SMOOTH was developed to remove genotyping errors from genetic linkage data during the mapping process. The program SMOOTH calculates the difference between the observed and predicted values of data points based on data points of neighbouring loci in a given marker order. Highly improbable data points are removed by the program in an iterative process with a mapping algorithm that recalculates the map after cleaning. SMOOTH has been tested with simulated data and experimental mapping data from potato. The simulations prove that this method is able to detect a high amount of scoring errors and demonstrates that the program enables mapping software to successfully construct a very accurate high-density map. In potato the application of the program resulted in a reliable placement of nearly 1,000 markers in one linkage group.     

An algorithm for analyzing linkages affected by heterozygous translocations: QuadMap

Heterozygous chromosome rearrangements such as reciprocal translocations are most accurately displayed as two-dimensional linkage maps. Standard linkage mapping software packages, such as MapMaker, generate only one-dimensional maps and so reciprocal translocations appear as clusters of markers, even though they originate from two nonhomologous chromosomes. To more accurately map these regions, researchers have developed statistical methods that use the variance in map distance to distinguish among the four segments (two translocation, two interstitial) of the translocation. In this study, we describe modifications to one of these protocols, that proposed by Livingstone et al. (2000). We also introduce QuadMap, a new software application for dissecting heterozygous translocation-affected linkage maps.     

PROTMAP2D: visualization, comparison and analysis of 2D maps of protein structure

MOTIVATION: Protein structure comparison is a fundamental problem in structural biology and bioinformatics. Two-dimensional maps of distances between residues in the structure contain sufficient information to restore the 3D representation, while maps of contacts reveal characteristic patterns of interactions between secondary and super-secondary structures and are very attractive for visual analysis. The overlap of 2D maps of two structures can be easily calculated, providing a sensitive measure of protein structure similarity. PROTMAP2D is a software tool for calculation of contact and distance maps based on user-defined criteria, quantitative comparison of pairs or series of contact maps (e.g. alternative models of the same protein, model versus native structure, different trajectories from molecular dynamics simulations, etc.) and visualization of the results. AVAILABILITY: PROTMAP2D for Windows / Linux / MacOSX is freely available for academic users from http://genesilico.pl/protmap2d.htm     

BACCardI--a tool for the validation of genomic assemblies, assisting genome finishing and intergenome comparison

SUMMARY: We provide the graphical tool BACCardI for the construction of virtual clone maps from standard assembler output files or BLAST based sequence comparisons. This new tool has been applied to numerous genome projects to solve various problems including (a) validation of whole genome shotgun assemblies, (b) support for contig ordering in the finishing phase of a genome project, and (c) intergenome comparison between related strains when only one of the strains has been sequenced and a large insert library is available for the other. The BACCardI software can seamlessly interact with various sequence assembly packages. MOTIVATION: Genomic assemblies generated from sequence information need to be validated by independent methods such as physical maps. The time-consuming task of building physical maps can be circumvented by virtual clone maps derived from read pair information of large insert libraries.     

GelMap-a novel software tool for building and presenting proteome reference maps

Protein separation by two-dimensional gel electrophoresis is of central importance for proteomics. Upon combination with systematic protein identifications by mass spectrometry, large data sets are routinely generated in several proteome laboratories which can be used as "reference maps" for future analyses of analogous biochemical fractions. Here we present GelMap, a novel software tool for the building presentation and evaluation of proteomic reference maps. Variable frames are introduced in order to group proteins into functional categories on three levels or into categories according to differential abundance during comparative proteome analyses. The software is easy to handle as it only requires uploading two digital files to a web site. An additional file including detailed information on all proteins can be combined with the primary map. Two different gel-based projects are presented to illustrate the capacity of GelMap for proteome annotation and evaluation.     

ODS2: a multiplatform software application for creating integrated physical and genetic maps

A contig map is a physical map that shows the native order of a library of overlapping genomic clones. One common method for creating such maps involves using hybridization to detect clone overlaps. False- positive and false-negative hybridization errors, the presence of chimeric clones, and gaps in library coverage lead to ambiguity and error in the clone order. Genomes with good genetic maps, such as Neurospora crassa, provide a means for reducing ambiguities and errors when constructing contig maps if clones can be anchored with genetic markers to the genetic map. A software application called ODS2 for creating contig maps based on clone-clone hybridization data is presented. This application is also designed to exploit partial ordering information provided by anchorage of clones to a genetic map. This information, along with clone-clone hybridization data, is used by a clone ordering algorithm and is represented graphically, allowing users to interactively align physical and genetic maps. ODS2 has a graphical user interface and is implemented entirely in Java, so it runs on multiple platforms. Other features include the flexibility of storing data in a local file or relational database and the ability to create full or minimum tiling contig maps.     

GFSWeb: a web tool for genome-based identification of proteins from mass spectrometric samples

The interpretation of mass spectrometry data for protein identification has become a vital component of proteomics research. However, since most existing software tools rely on protein databases, their success is limited, especially as the pace of annotation efforts fails to keep pace with sequencing. We present a publicly available, web-based version of a software tool that maps peptide mass fingerprint data directly to their genomic origin, allowing for genome-based, annotation-independent protein identification.     

Mapping sequenced E.coli genes by computer: software, strategies and examples.

Methods are presented for organizing and integrating DNA sequence data, restriction maps, and genetic maps for the same organism but from a variety of sources (databases, publications, personal communications). Proper software tools are essential for successful organization of such diverse data into an ordered, cohesive body of information, and a suite of novel software to support this endeavor is described. Though these tools automate much of the task, a variety of strategies is needed to cope with recalcitrant cases. We describe such strategies and illustrate their application with numerous examples. These strategies have allowed us to order, analyze, and display over one megabase of E. coli DNA sequence information. The integration task often exposes inconsistencies in the available data, perhaps caused by strain polymorphisms or human oversight, necessitating the application of sound biological judgment. The examples illustrate both the level of expertise required of the database curator and the knowledge gained as apparent inconsistencies are resolved. The software and mapping methods are applicable to the study of any genome for which a high resolution restriction map is available. They were developed to support a weakly coordinated sequencing effort involving many laboratories, but would also be useful for highly orchestrated sequencing projects.     

Integrated Mapping Package—A Physical Mapping Software Tool Kit

We have developed an integrated physical mapping computer software package (IMP), originally designed to support the physical mapping of human chromosome 13 and expanded to support several gene-identification projects based on the positional candidate approach. IMP displays map data in a form that provides useful guidelines to the end users. An integrated map with high resolution and confidence is constructed from different types of mapping data, including hybridization experiments, STS-based PCR assays, genetic linkage mapping, cDNA localization, and FISH data. The map is also designed to provide suggestions for specific experiments that are required to obtain maps with even higher resolution and confidence. To this end, the optimization employs multiple constraints that take into account already established STS “scaffold” maps. This software thus serves as an important general tool kit for physical mapping, sequencing, and gene-hunting projects.     

Analysis of training-induced changes in ethyl acetate odor maps using a new computational tool to map the glomerular layer of the olfactory bulb

Odor quality is thought to be encoded by the activation of partially overlapping subsets of glomeruli in the olfactory bulb (odor maps). Mouse genetic studies have demonstrated that olfactory sensory neurons (OSNs) expressing a particular olfactory receptor target their axons to a few individual glomeruli in the bulb. While the specific targeting of OSN axons provides a molecular underpinning for the odor maps, much remains to be understood about the relationship between the functional and molecular maps. In this article, we ask the question whether intensive training of mice in a go/no-go operant conditioning odor discrimination task affects odor maps measured by determining c-fos up-regulation in periglomerular cells. Data analysis is performed using a newly developed suite of computational tools designed to systematically map functional and molecular features of glomeruli in the adult mouse olfactory bulb. This suite provides the necessary tools to process high-resolution digital images, map labeled glomeruli, visualize odor maps, and facilitate statistical analysis of patterns of identified glomeruli in the olfactory bulb. The software generates odor maps (density plots) based on glomerular activity, density, or area. We find that training up-regulates the number of glomeruli that become c-fos positive after stimulation with ethyl acetate.     

Multipoint identity-by-descent computations for single-point polymorphism and microsatellite maps

We used the LOKI software to generate multipoint identity-by-descent matrices for a microsatellite map (with 31 markers) and two single-nucleotide polymorphism (SNP) maps to examine information content across chromosome 7 in the Collaborative Study on the Genetics of Alcoholism dataset. Despite the lower information provided by a single SNP, SNP maps overall had higher and more uniform information content across the chromosome. The Affymetrix map (578 SNPs) and the Illumina map (271 SNPs) provided almost identical information. However, increased information has a computational cost: SNP maps require 100 times as many iterations as microsatellites to produce stable estimates.     

Genetic mapping in the presence of genotyping errors

Genetic maps are built using the genotypes of many related individuals. Genotyping errors in these data sets can distort genetic maps, especially by inflating the distances. We have extended the traditional likelihood model used for genetic mapping to include the possibility of genotyping errors. Each individual marker is assigned an error rate, which is inferred from the data, just as the genetic distances are. We have developed a software package, called TMAP, which uses this model to find maximum-likelihood maps for phase-known pedigrees. We have tested our methods using a data set in Vitis and on simulated data and confirmed that our method dramatically reduces the inflationary effect caused by increasing the number of markers and leads to more accurate orders.     

rh_tsp_map 3.0: end-to-end radiation hybrid mapping with improved speed and quality control

rh_tsp_map is a software package for computing radiation hybrid (RH) maps and for integrating physical and genetic maps. It solves the central mapping instances by reducing them to the traveling salesman problem (TSP) and using a modification of the CONCORDE package to solve the TSP instances. We present some of the features added between the initial rh_tsp_map version 1.0 and the current version 3.0, emphasizing the automation of many steps and addition of various checks designed to find problems with the input data. Iterations of improved input data followed by fast re-computation of the maps improves the quality of the final maps. AVAILABILITY: rh_tsp_map source code and documentation including a tutorial is available at ftp://ftp.ncbi.nih.gov/pub/agarwala/rhmapping/rh_tsp_map.tar.gz. CONCORDE modified for RH mapping is available in the directory http://www.isye.gatech.edu/~wcook/rh/. The QSopt library needed for CONCORDE is available at http://www2.isye.gatech.edu/~wcook/qsopt/downloads/downloads.htm     

Design, implementation and maintenance of a model organism database for Arabidopsis thaliana

The Arabidopsis Information Resource (TAIR) is a web-based community database for the model plant Arabidopsis thaliana. It provides an integrated view of genes, sequences, proteins, germplasms, clones, metabolic pathways, gene expression, ecotypes, polymorphisms, publications, maps and community information. TAIR is developed and maintained by collaboration between software developers and biologists. Biologists provide specification and use cases for the system, acquire, analyse and curate data, interact with users and test the software. Software developers design, implement and test the database and software. In this review, we briefly describe how TAIR was built and is being maintained.