snp.plotter: an R-based SNP/haplotype association and linkage disequilibrium plotting package

snp.plotter is a newly developed R package which produces high-quality plots of results from genetic association studies. The main features of the package include options to display a linkage disequilibrium (LD) plot below the P-value plot using either the r2 or D' LD metric, to set the X-axis to equal spacing or to use the physical map of markers, and to specify plot labels, colors, symbols and LD heatmap color scheme. snp.plotter can plot single SNP and/or haplotype data and simultaneously plot multiple sets of results. R is a free software environment for statistical computing and graphics available for most platforms. The proposed package provides a simple way to convey both association and LD information in a single appealing graphic for genetic association studies. AVAILABILITY: Downloadable R package and example datasets are available at http://cbdb.nimh.nih.gov/~kristin/snp.plotter.html and http://www.r-project.org.     

introgress: a software package for mapping components of isolation in hybrids

A new software package (introgress) provides functions for analysing introgression of genotypes between divergent, hybridizing lineages, including estimating genomic clines from multi-locus genotype data and testing for deviations from neutral expectations. The software works with co-dominant, dominant and haploid marker data, and does not require fixed allelic differences between parental populations for the sampled genetic markers. Permutation and parametric procedures generate neutral expectations for introgression and provide a basis for significance tests of observed genomic clines. The software also implements maximum likelihood estimates of hybrid index from genotypic data and a number of graphical analyses. The package is an extension of the R statistical software, is written in the R language and is freely available through the Comprehensive R Archive Network (CRAN; http://cran.r-project.org/). In this study, we describe introgress and demonstrate its use with a sample data set.     

GEIGER: investigating evolutionary radiations

SUMMARY: GEIGER is a new software package, written in the R language, to describe evolutionary radiations. GEIGER can carry out simulations, parameter estimation and statistical hypothesis testing. Additionally, GEIGER's simulation algorithms can be used to analyze the statistical power of comparative approaches. AVAILABILITY: This open source software is written entirely in the R language and is freely available through the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org/.     

spacodiR: structuring of phylogenetic diversity in ecological communities

MOTIVATION: spacodiR is a cross-platform package, written for the R environment, for studying partitioning of diversity among natural communities in space and time. Complementing and extending existing software, spacodiR allows for hypothesis testing and parameter estimation in studying spatial structuring of species-, phylogenetic- and trait diversities. AVAILABILITY: Integrated with other software in the R environment and with well documented and demonstrated functions, spacodiR is an open-source package and available at http://cran.r-project.org. CONTACT: jonathan.eastman@gmail.com; ohardy@ulb.ac.be.     

HapSim: a simulation tool for generating haplotype data with pre-specified allele frequencies and LD coefficients

We have developed a simulation tool HapSim for the generation of haplotype data. The simulated haplotypes are such that their allele frequencies and linkage disequilibrium coefficients match exactly those estimated in a real sample. AVAILABILITY: The program is available as an R package and can be downloaded from http://cran.r-project.org/.     

P2BAT: a massive parallel implementation of PBAT for genome-wide association studies in R

The software tool P2BAT provides a massive parallel and user friendly implementation of the PBAT-analysis tools for family-based association tests (FBATs) in large-scale studies, including genome-wide association studies with several thousand subjects. Built on the original PBAT-implementation of the Lange-Van Steen algorithm to bypass the multiple testing problem in family-based association studies, P2BAT integrates all PBAT-analysis tools for binary and complex traits into R and makes them accessible through a user-friendly GUI. The genome-wide analysis tools are fully automated and can be ran massively parallel directly through the GUI. P2BAT is fully documented and contains graphical output tools for time-to-onset analysis. P2BAT also features the ability to test for gene and environment/drug interaction. AVAILABILITY: The P2BAT package is available as the R package 'pbatR' which can be downloaded from http://cran.r-project.org/. The PBAT-software is available at http://www.biostat.harvard.edu/~clange/.     

WAVECLOCK: wavelet analysis of circadian oscillation

Oscillations in mRNA and protein of circadian clock components can be continuously monitored in vitro using synchronized cell lines. These rhythms can be highly variable due to culture conditions and are non-stationary due to baseline trends, damping and drift in period length. We present a technique for characterizing the modal frequencies of oscillation using continuous wavelet decomposition to non-parametrically model changes in amplitude and period while removing baseline effects and noise. AVAILABILITY: The method has been implemented as the package waveclock for the free statistical software program R and is available for download from http://cran.r-project.org/     

APE: Analyses of Phylogenetics and Evolution in R language

Analysis of Phylogenetics and Evolution (APE) is a package written in the R language for use in molecular evolution and phylogenetics. APE provides both utility functions for reading and writing data and manipulating phylogenetic trees, as well as several advanced methods for phylogenetic and evolutionary analysis (e.g. comparative and population genetic methods). APE takes advantage of the many R functions for statistics and graphics, and also provides a flexible framework for developing and implementing further statistical methods for the analysis of evolutionary processes. AVAILABILITY: The program is free and available from the official R package archive at http://cran.r-project.org/src/contrib/PACKAGES.html#ape. APE is licensed under the GNU General Public License.     

Pedigree-drawing with R and graphviz

Two functions for pedigree-drawing available in R (http://www.r-project.org): plot.pedigree in kinship and pedtodot in gap are described. The latter requires graphviz (http://www.graphviz.org). They can produce many pedigree diagrams quickly into a single file, serving as alternatives to programs that only offer interactive use. Availability: Packages kinship and gap are available from http://cran.r-project.org.     

BaSAR-A tool in R for frequency detection

Many biological processes are periodic, for example cell cycle expression, circadian rhythms and calcium oscillations. However, measured time series from these processes are commonly short and noisy, and finding frequencies in such data can be challenging. Here we present BaSAR, Bayesian Spectrum Analysis in R, a package for extracting frequency information from time series data. The software uses advanced techniques of Bayesian inference that are well suited for handling typical biological data. The core functions are designed for detecting a single key frequency, without the need for data pre-processing such as detrending. The package is freely available at CRAN - The Comprehensive R Archive Network: http://cran.r-project.org/web/packages/BaSAR.     

Alternative forms for genomic clines

Understanding factors regulating hybrid fitness and gene exchange is a major research challenge for evolutionary biology. Genomic cline analysis has been used to evaluate alternative patterns of introgression, but only two models have been used widely and the approach has generally lacked a hypothesis testing framework for distinguishing effects of selection and drift. I propose two alternative cline models, implement multivariate outlier detection to identify markers associated with hybrid fitness, and simulate hybrid zone dynamics to evaluate the signatures of different modes of selection. Analysis of simulated data shows that previous approaches are prone to false positives (multinomial regression) or relatively insensitive to outlier loci affected by selection (Barton's concordance). The new, theory‐based logit‐logistic cline model is generally best at detecting loci affecting hybrid fitness. Although some generalizations can be made about different modes of selection, there is no one‐to‐one correspondence between pattern and process. These new methods will enhance our ability to extract important information about the genetics of reproductive isolation and hybrid fitness. However, much remains to be done to relate statistical patterns to particular evolutionary processes. The methods described here are implemented in a freely available package “HIest” for the R statistical software (CRAN; http://cran.r-project.org/ ).     

Spider: an R package for the analysis of species identity and evolution, with particular reference to DNA barcoding

Spider: SPecies IDentity and Evolution in R is a new R package implementing a number of useful analyses for DNA barcoding studies and associated research into species delimitation and speciation. Included are functions essential for generating important summary statistics from DNA barcode data, assessing specimen identification efficacy, and for testing and optimizing divergence threshold limits. In terms of investigating evolutionary and taxonomic questions, techniques for assessing diagnostic nucleotides and probability of reciprocal monophyly are also provided. Additionally, a sliding window function offers opportunities to analyse information across a gene, essential for marker design in degraded DNA studies. Spider capitalizes on R's extensible ethos and offers an integrated platform ideal for the analysis of both nucleotide and morphological data. The program can be obtained from the comprehensive R archive network (CRAN, http://cran.r-project.org) and from the R-Forge package development site (http://spider.r-forge.r-project.org/).     

I3:A Self-organising Learning Workflow for Intuitive Integrative Interpretation of Complex Genetic Data

We propose a computational workflow(I3) for intuitive integrative interpretation of complex genetic data mainly building on the self-organising principle.We illustrate the use in interpreting genetics of gene expression and understanding genetic regulators of protein phenotypes,particularly in conjunction with information from human population genetics and/or evolutionary history of human genes.We reveal that loss-of-function intolerant genes tend to be depleted of tissue-sharing genetics of gene expression in brains,and if highly expressed,have broad effects on the protein phenotypes studied.We suggest that this workflow presents a general solution to the challenge of complex genetic data interpretation.I3 is available at http://suprahex.r-forge.r-project.org/I3.html.     

SurvJamda: an R package to predict patients' survival and risk assessment using joint analysis of microarray gene expression data

SurvJamda (Survival prediction by joint analysis of microarray data) is an R package that utilizes joint analysis of microarray gene expression data to predict patients' survival and risk assessment. Joint analysis can be performed by merging datasets or meta-analysis to increase the sample size and to improve survival prognosis. The prognosis performance derived from the combined datasets can be assessed to determine which feature selection approach, joint analysis method and bias estimation provide the most robust prognosis for a given set of datasets. AVAILABILITY: The survJamda package is available at the Comprehensive R Archive Network, http://cran.r-project.org. CONTACT: hyasrebi@yahoo.com.     

hzar: hybrid zone analysis using an R software package

We present a new software package (hzar ) that provides functions for fitting molecular genetic and morphological data from hybrid zones to classic equilibrium cline models using the Metropolis–Hastings Markov chain Monte Carlo (MCMC) algorithm. The software applies likelihood functions appropriate for different types of data, including diploid and haploid genetic markers and quantitative morphological traits. The modular design allows flexibility in fitting cline models of varying complexity. To facilitate hypothesis testing, an autofit function is included that allows automated model selection from a set of nested cline models. Cline parameter values, such as cline centre and cline width, are estimated and may be compared statistically across clines. The package is written in the R language and is available through the Comprehensive R Archive Network (CRAN; http://cran.r-project.org/ ). Here, we describe hzar and demonstrate its use with a sample data set from a well‐studied hybrid zone in western Panama between white‐collared (Manacus candei) and golden‐collared manakins (M. vitellinus). Comparisons of our results with previously published results for this hybrid zone validate the hzar software. We extend analysis of this hybrid zone by fitting additional models to molecular data where appropriate.     

Assessing Statistical Significance in Microarray Experiments Using the Distance Between Microarrays

We propose permutation tests based on the pairwise distances between microarrays to compare location, variability, or equivalence of gene expression between two populations. For these tests the entire microarray or some pre-specified subset of genes is the unit of analysis. The pairwise distances only have to be computed once so the procedure is not computationally intensive despite the high dimensionality of the data. An R software package, permtest, implementing the method is freely available from the Comprehensive R Archive Network at http://cran.r-project.org.     

POLYSAT: an R package for polyploid microsatellite analysis

We present an R package to help remedy the lack of software for manipulating and analysing autopolyploid and allopolyploid microsatellite data. POLYSAT can handle genotype data of any ploidy, including populations of mixed ploidy, and assumes that allele copy number is always ambiguous in partial heterozygotes. It can import and export genotype data in eight different formats, calculate pairwise distances between individuals using a stepwise mutation and infinite alleles model, estimate ploidy based on allele counts and estimate allele frequencies and pairwise F(ST) values. This software is freely available through the Comprehensive R Archive Network (http://cran.r-project.org/) and includes a thorough tutorial.     

mvmapper: Interactive spatial mapping of genetic structures

Characterizing genetic structure across geographic space is a fundamental challenge in population genetics. Multivariate statistical analyses are powerful tools for summarizing genetic variability, but geographic information and accompanying metadata are not always easily integrated into these methods in a user‐friendly fashion. Here, we present a deployable Python‐based web‐tool, mvmapper , for visualizing and exploring results of multivariate analyses in geographic space. This tool can be used to map results of virtually any multivariate analysis of georeferenced data, and routines for exporting results from a number of standard methods have been integrated in the R package adegenet , including principal components analysis (PCA), spatial PCA, discriminant analysis of principal components, principal coordinates analysis, nonmetric dimensional scaling and correspondence analysis. mvmapper 's greatest strength is facilitating dynamic and interactive exploration of the statistical and geographic frameworks side by side, a task that is difficult and time‐consuming with currently available tools. Source code and deployment instructions, as well as a link to a hosted instance of mvmapper , can be found at https://popphylotools.github.io/mvMapper/ .     

'SEEDY' (Simulation of Evolutionary and Epidemiological Dynamics): An R Package to Follow Accumulation of Within-Host Mutation in Pathogens

Genome sequencing is an increasingly common component of infectious disease outbreak investigations. However, the relationship between pathogen transmission and observed genetic data is complex, and dependent on several uncertain factors. As such, simulation of pathogen dynamics is an important tool for interpreting observed genomic data in an infectious disease outbreak setting, in order to test hypotheses and to explore the range of outcomes consistent with a given set of parameters. We introduce ‘seedy’, an R package for the simulation of evolutionary and epidemiological dynamics (http://cran.r-project.org/web/packages/seedy/). Our software implements stochastic models for the accumulation of mutations within hosts, as well as individual-level disease transmission. By allowing variables such as the transmission bottleneck size, within-host effective population size and population mixing rates to be specified by the user, our package offers a flexible framework to investigate evolutionary dynamics during disease outbreaks. Furthermore, our software provides theoretical pairwise genetic distance distributions to provide a likelihood of person-to-person transmission based on genomic observations, and using this framework, implements transmission route assessment for genomic data collected during an outbreak. Our open source software provides an accessible platform for users to explore pathogen evolution and outbreak dynamics via simulation, and offers tools to assess observed genomic data in this context.     

Multivariate correlation estimator for inferring functional relationships from replicated genome-wide data

Estimating pairwise correlation from replicated genome-scale (a.k.a. OMICS) data is fundamental to cluster functionally relevant biomolecules to a cellular pathway. The popular Pearson correlation coefficient estimates bivariate correlation by averaging over replicates. It is not completely satisfactory since it introduces strong bias while reducing variance. We propose a new multivariate correlation estimator that models all replicates as independent and identically distributed (i.i.d.) samples from the multivariate normal distribution. We derive the estimator by maximizing the likelihood function. For small sample data, we provide a resampling-based statistical inference procedure, and for moderate to large sample data, we provide an asymptotic statistical inference procedure based on the Likelihood Ratio Test (LRT). We demonstrate advantages of the new multivariate correlation estimator over Pearson bivariate correlation estimator using simulations and real-world data analysis examples. AVAILABILITY: The estimator and statistical inference procedures have been implemented in an R package 'CORREP' that is available from CRAN [http://cran.r-project.org] and Bioconductor [http://www.bioconductor.org/]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.