ProMAT: protein microarray analysis tool

SUMMARY: ProMAT is a software tool for statistically analyzing data from enzyme-linked immunosorbent assay microarray experiments. The software estimates standard curves, sample protein concentrations and their uncertainties for multiple assays. ProMAT generates a set of comprehensive figures for assessing results and diagnosing process quality. The tool is available for Windows or Mac, and is distributed as open-source Java and R code. AVAILABILITY: ProMAT is available at http://www.pnl.gov/statistics/ProMAT. ProMAT requires Java version 1.5.0 and R version 1.9.1 (or more recent versions). ProMAT requires either Windows XP or Mac OS 10.4 or newer versions.     

CAPS: coevolution analysis using protein sequences

Coevolution Analysis using Protein Sequences (CAPS) is a PERL based software that identifies co-evolution between amino acid sites. Blosum-corrected amino acid distances are used to identify amino acid co-variation. The phylogenetic sequence relationships are used to remove the phylogenetic and stochastic dependencies between sites. The 3D protein structure is used to identify the nature of the dependencies between co-evolving amino acid sites. Friendly interpretable output files are generated. AVAILABILITY: CAPS version 1 is available at http://bioinf.gen.tcd.ie/~faresm/software/caps/. Distribution versions for Linux/Unix, Mac OS X and Windows operating systems are available, including manual and example files.     

msatcommander: detection of microsatellite repeat arrays and automated, locus-specific primer design

msatcommander is a platform-independent program designed to search for microsatellite arrays, design primers, and tag primers using an automated routine. msatcommander accepts as input DNA sequence data in single-sequence or concatenated, fasta-formatted files. Search data and locus-specific primers are written to comma-separated value files for subsequent use in spreadsheet or database programs. Binary versions of the graphical interface for msatcommander are available for Apple OS X and Windows XP. Users of other operating systems may run the graphical interface version using the available source code, provided their environment supports at least Python 2.4, Biopython 1.43, and wxPython 2.8. msatcommander is available from http://code.google.com/p/msatcommander/.     

gmconvert: file conversion for genemapper output files

gmconvert is a platform‐independent program provided in GUI (for Apple OS X and Windows XP) and command‐line versions (for other platforms). gmconvert allows rapid reformatting of microsatellite data from output files produced by Applied Biosystems genemapper software (version 3.x). The program will re‐array data into three formats commonly used in downstream analysis: genepop , cervus , and gerud . gmconvert will greatly increase the speed of data preparation prior to analysis and aid in reducing transpositional errors associated with manual re‐arraying and reformatting steps. gmconvert is available from http://gallus.forestry.uga.edu/software/ .     

jackalope: A swift,versatile phylogenomic and high‐throughput sequencing simulator

High‐throughput sequencing (HTS) is central to the study of population genomics and has an increasingly important role in constructing phylogenies. Choices in research design for sequencing projects can include a wide range of factors, such as sequencing platform, depth of coverage and bioinformatic tools. Simulating HTS data better informs these decisions, as users can validate software by comparing output to the known simulation parameters. However, current standalone HTS simulators cannot generate variant haplotypes under even somewhat complex evolutionary scenarios, such as recombination or demographic change. This greatly reduces their usefulness for fields such as population genomics and phylogenomics. Here I present the R package jackalope that simply and efficiently simulates (i) sets of variant haplotypes from a reference genome and (ii) reads from both Illumina and Pacific Biosciences platforms. Haplotypes can be simulated using phylogenies, gene trees, coalescent‐simulation output, population‐genomic summary statistics, and Variant Call Format (VCF) files. jackalope can simulate single, paired‐end or mate‐pair Illumina reads, as well as reads from Pacific Biosciences. These simulations include sequencing errors, mapping qualities, multiplexing and optical/PCR duplicates. It can read reference genomes from fasta files and can simulate new ones, and all outputs can be written to standard file formats. jackalope is available for Mac, Windows and Linux systems.     

NMπ—improved re‐implementation of NM+, a software for estimating gene dispersal and mating patterns

This study introduces the NMπ computer program designed for estimation of plant mating system and seed and pollen dispersal kernels. NMπ is a re‐implementation of the NM+ program and provides new features such as support for multicore processors, explicit treatment of dioecy, the possibility of incorporating uniparentally cytoplasmic markers, the possibility of assessing assortative mating due to phenotypic similarity and inference about offspring genealogies. The probability model of parentage (the neighbourhood model) accounts for missing data and genotyping errors, which can be estimated along with regular parameters of the mating system. The program has virtually no restrictions with respect to a number of individuals, markers or phenotypic characters. A console version of NMπ can be run under a wide variety of operating systems, including Windows, Linux or Mac OS. For Windows users, a graphical user interface is provided to facilitate operating the software. The program, user manual and example data are available on http://www.ukw.edu.pl/pracownicy/plik/igor_chybicki/3694/ .     

HapStar: automated haplotype network layout and visualization

Haplotype networks are commonly used for representing associations between sequences, yet there is currently no straightforward way to create optimal layouts. Automated optimal layouts are particularly useful not only because of the time-saving element but also because they avoid both human error and human-induced biases in the presentation of figures. HapStar directly uses the network connection output data generated from Arlequin (or a simple user-generated input file) and uses a force-directed algorithm to automatically lay out the network for easy visualization. In addition, this program is able to use the alternative connections generated by Arlequin to create a minimum spanning tree. HapStar provides a straightforward user-friendly interface, and publication-ready figures can be exported simply. HapStar is freely available (under a GPLv3 licence) for download for MacOSX, UNIX and Windows, at http://fo.am/hapstar.     

PEAS V1.0: a package for elementary analysis of SNP data

We have developed a software package named PEAS to facilitate analyses of large data sets of single nucleotide polymorphisms (SNPs) for population genetics and molecular phylogenetics studies. PEAS reads SNP data in various formats as input and is versatile in data formatting; using PEAS, it is easy to create input files for many popular packages, such as STRUCTURE, frappe, Arlequin, Haploview, LDhat, PLINK, EIGENSOFT, PHASE, fastPHASE, MEGA and PHYLIP. In addition, PEAS fills up several analysis gaps in currently available computer programs in population genetics and molecular phylogenetics. Notably, (i) It calculates genetic distance matrices with bootstrapping for both individuals and populations from genome-wide high-density SNP data, and the output can be streamlined to MEGA and PHYLIP programs for further processing; (ii) It calculates genetic distances from STRUCTURE output and generates MEGA file to reconstruct component trees; (iii) It provides tools to conduct haplotype sharing analysis for phylogenetic studies based on high-density SNP data. To our knowledge, these analyses are not available in any other computer program. PEAS for Windows is freely available for academic users from http://www.picb.ac.cn/~xushua/index.files/Download_PEAS.htm.     

NeEstimator v2: re‐implementation of software for the estimation of contemporary effective population size (Ne) from genetic data

NeEstimator v2 is a completely revised and updated implementation of software that produces estimates of contemporary effective population size, using several different methods and a single input file. NeEstimator v2 includes three single‐sample estimators (updated versions of the linkage disequilibrium and heterozygote‐excess methods, and a new method based on molecular coancestry), as well as the two‐sample (moment‐based temporal) method. New features include the following: (i) an improved method for accounting for missing data; (ii) options for screening out rare alleles; (iii) confidence intervals for all methods; (iv) the ability to analyse data sets with large numbers of genetic markers (10 000 or more); (v) options for batch processing large numbers of different data sets, which will facilitate cross‐method comparisons using simulated data; and (vi) correction for temporal estimates when individuals sampled are not removed from the population (Plan I sampling). The user is given considerable control over input data and composition, and format of output files. The freely available software has a new JAVA interface and runs under MacOS, Linux and Windows.     

Making more sense of the order: A review of Canoco for Windows 4.5, PC‐ORD version 4 and SYN‐TAX 2000

Abstract. Personal computers of ever‐increasing speed have motivated programmers of multivariate software to adapt their programs to be run in Microsoft Windows and Macintosh platforms. Updated versions of these multivariate programs appear more and more frequently and are marketed intensively. In this review we provide a comparative analysis of the most recent versions of three analytical software packages –Canoco for Windows 4.5, PC‐ORD version 4 and SYN‐TAX 2000. The three packages share two characteristics. First, the most recent versions are now compatible with the most recent Windows platforms and should therefore be accessible for use by virtually all vegetation scientists. Second, they have capabilities for numerous multivariate techniques, although each package has some unique techniques. Thus, any one of the packages will have much to offer the user.