A simple linear regression method for quantitative trait loci linkage analysis with censored observations

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.     

LOT: a tool for linkage analysis of ordinal traits for pedigree data

SUMMARY: Existing linkage-analysis methods address binary or quantitative traits. However, many complex diseases and human conditions, particularly behavioral disorders, are rated on ordinal scales. Herein, we introduce, LOT, a tool that performs linkage analysis of ordinal traits for pedigree data. It implements a latent-variable proportional-odds logistic model that relates inheritance patterns to the distribution of the ordinal trait. The likelihood-ratio test is used for testing evidence of linkage. AVAILABILITY: The LOT program is available for download at http://c2s2.yale.edu/software/LOT/     

Matapax: an online high-throughput genome-wide association study pipeline

High-throughput sequencing and genotyping methods are dramatically increasing the number of observable genetic intraspecies differences that can be exploited as genetic markers. In addition, automated phenotyping platforms and "omics" profiling technologies further enlarge the set of quantifiable macroscopic and molecular traits at an ever-increasing pace. Combined, both lines of technological advances create unparalleled opportunities to identify candidate gene regions and, ideally, even single genes responsible for observed variations in a particular trait via association studies. However, as of yet, this new potential is not sufficiently matched by enabling software solutions to easily exploit this wealth of genotype/phenotype information. We have developed Matapax, a Web-based platform to address this need. Initially, we built the infrastructure to support association studies in Arabidopsis (Arabidopsis thaliana) based on several genotyping efforts covering up to 1,375 Arabidopsis accessions. Based on the user-supplied trait information, associated single-nucleotide polymorphism markers and single-nucleotide polymorphism-harboring or -neighboring genes are identified using both the GAPIT and EMMA libraries developed for R. Additional interrogation is facilitated by displaying candidate regions and genes in a genome browser and by providing relevant annotation information. In the future, we plan to broaden the scope of organisms to other plant species as more genotype/phenotype information becomes available. Matapax is freely available at http://matapax.mpimp-golm.mpg.de and can be accessed using any internet browser.     

多基因离散性状QTL连锁分析方法

动物中有许多重要的离散性状,与常规的数量性状类似,其遗传基础受多基因控制并受到环境因子的修饰。由于多基因离散性状的表型特殊性,利用常规的QTL连锁分析方法很难获得理想的统计效果,相应地发展了许多基于广义线性模型框架内的非线性方法。本文就目前离散性状的QTL连锁分析方法作简要综述,并对可预期的改进方法进行了展望。     

mrMLM v4.0.2:An R Platform for Multi-locus Genome-wide Association Studies

Previous studies have reported that some important loci are missed in single-locus genome-wide association studies (GWAS), especially because of the large phenotypic error in field experiments. To solve this issue, multi-locus GWAS methods have been recommended. However, only a few software packages for multi-locus GWAS are available. Therefore, we developed an R software named mrMLM v4.0.2. This software integrates mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, and ISIS EM-BLASSO methods developed by our lab. There are four components in mrMLM v4.0.2, including dataset input, parameter setting, software running, and result output. The fread function in data.table is used to quickly read datasets, especially big datasets, and the doParallel package is used to conduct parallel computation using multiple CPUs. In addition, the graphical user interface software mrMLM.GUI v4.0.2, built upon Shiny, is also available. To confirm the correctness of the aforementioned programs, all the methods in mrMLM v4.0.2 and three widely-used methods were used to analyze real and simulated datasets. The results confirm the superior performance of mrMLM v4.0.2 to other methods currently available. False positive rates are effectively controlled, albeit with a less stringent significance threshold. mrMLM v4.0.2 is publicly available at BioCode (https://bigd.big.ac.cn/biocode/tools/BT007077) or R (https://cran.r-project.org/web/packages/mrMLM.GUI/index.html) as an open-source software.     

Qxpak: a versatile mixed model application for genetical genomics and QTL analyses

MOTIVATION: Current methodology and software for quantitative trait loci (QTL) analyses do not use all available information and are inadequate to deal with the huge amount of QTL analyses to be needed in forecoming genetical genomics' studies. RESULTS: We show that a mixed model statistical framework provides a very flexible tool for QTL modeling in a variety of populations, be it a cross between inbred lines, a within population study, or experiments involving a mixture of populations or crosses. The software allows multitrait and multiQTL analyses, inclusion of infinitesimal genetic value and a batch multitrait option suitable for genetical genomics studies. It also allows massive association studies between single nucleotide polymorphisms and the trait(s) of interest. AVAILABILITY: A software (Qxpak), together with a manual and example files, is freely available for research purposes. So far, the compiled program is available for linux systems, the windows version will follow soon. See http://www.icrea.es/pag.asp?id=Miguel.Perez     

Integration of genetic and genomic methods for identification of genes and gene variants encoding QTLs in the nonhuman primate

We have developed an integrated approach, using genetic and genomic methods, in conjunction with resources from the Southwest National Primate Research Center (SNPRC) baboon colony, for the identification of genes and their functional variants that encode quantitative trait loci (QTL). In addition, we use comparative genomic methods to overcome the paucity of baboon specific reagents and to augment translation of our findings in a nonhuman primate (NHP) to the human population. We are using the baboon as a model to study the genetics of cardiovascular disease (CVD). A key step for understanding gene–environment interactions in cardiovascular disease is the identification of genes and gene variants that influence CVD phenotypes. We have developed a sequential methodology that takes advantage of the SNPRC pedigreed baboon colony, the annotated human genome, and current genomic and bioinformatic tools. The process of functional polymorphism identification for genes encoding QTLs involves comparison of expression profiles for genes and predicted genes in the genomic region of the QTL for individuals discordant for the phenotypic trait mapping to the QTL. After comparison, genes of interest are prioritized, and functional polymorphisms are identified in candidate genes by genotyping and quantitative trait nucleotide analysis. This approach reduces the time and labor necessary to prioritize and identify genes and their polymorphisms influencing variation in a quantitative trait compared with traditional positional cloning methods.     

Coordinated conditional simulation with SLINK and SUP of many markers linked or associated to a trait in large pedigrees

Simulation of genotypes in pedigrees is an important tool to evaluate the power of a linkage or an association study and to assess the empirical significance of results. SLINK is a widely-used package for pedigree simulations, but its implementation has not previously been described in a published paper. SLINK was initially derived from the LINKAGE programs. Over the 20 years since its release, SLINK has been modified to incorporate faster algorithms, notably from the linkage analysis package FASTLINK, also derived from LINKAGE. While SLINK can simulate genotypes on pedigrees of high complexity, one limitation of SLINK, as with most methods based on peeling algorithms to evaluate pedigree likelihoods, is the small number of linked markers that can be generated. The software package SUP includes an elegant wrapper for SLINK that circumvents the limitation on number of markers by using descent markers generated by SLINK to simulate a much larger number of markers on the same chromosome, linked and possibly associated with a trait locus. We have released new coordinated versions of SLINK (3.0; available from http://watson.hgen.pitt.edu) and SUP (v090804; available from http://mlemire.freeshell.org/software or http://watson.hgen.pitt.edu) that integrate the two software packages. Thereby, we have removed some of the previous limitations on the joint functionality of the programs, such as the number of founders in a pedigree. We review the history of SLINK and describe how SLINK and SUP are now coordinated to permit the simulation of large numbers of markers linked and possibly associated with a trait in large pedigrees.     

shRNAPred (version 1.0): An open source and standalone software for short hairpin RNA (shRNA) prediction

The small hairpin RNAs (shRNA) are useful in many ways like identification of trait specific molecular markers, gene silencing and characterization of a species. In public domain, hardly there exists any standalone software for shRNA prediction. Hence, a software shRNAPred (1.0) is proposed here to offer a user-friendly Command-line User Interface (CUI) to predict 'shRNA-like' regions from a large set of nucleotide sequences. The software is developed using PERL Version 5.12.5 taking into account the parameters such as stem and loop length combinations, specific loop sequence, GC content, melting temperature, position specific nucleotides, low complexity filter, etc. Each of the parameters is assigned with a specific score and based on which the software ranks the predicted shRNAs. The high scored shRNAs obtained from the software are depicted as potential shRNAs and provided to the user in the form of a text file. The proposed software also allows the user to customize certain parameters while predicting specific shRNAs of his interest. The shRNAPred (1.0) is open access software available for academic users. It can be downloaded freely along with user manual, example dataset and output for easy understanding and implementation. AVAILABILITY: The database is available for free at http://bioinformatics.iasri.res.in/EDA/downloads/shRNAPred_v1.0.exe.     

TOPD/FMTS: a new software to compare phylogenetic trees

SUMMARY: TOPD/FMTS has been developed to evaluate similarities and differences between phylogenetic trees. The software implements several new algorithms (including the Disagree method that returns the taxa, that disagree between two trees and the Nodal method that compares two trees using nodal information) and several previously described methods (such as the Partition method, Triplets or Quartets) to compare phylogenetic trees. One of the novelties of this software is that the FMTS (From Multiple to Single) program allows the comparison of trees that contain both orthologs and paralogs. Each option is also complemented with a randomization analysis to test the null hypothesis that the similarity between two trees is not better than chance expectation. AVAILABILITY: The Perl source code of TOPD/FMTS is available at http://genomes.urv.es/topd.     

Procom: a web-based tool to compare multiple eukaryotic proteomes

SUMMARY: Each organism has traits that are shared with some, but not all, organisms. Identification of genes needed for a particular trait can be accomplished by a comparative genomics approach using three or more organisms. Genes that occur in organisms without the trait are removed from the set of genes in common among organisms with the trait. To facilitate these comparisons, a web-based server, Procom, was developed to identify the subset of genes that may be needed for a trait. AVAILABILITY: The Procom program is freely available with documentation and examples at http://ural.wustl.edu/~billy/Procom/ CONTACT: billy@ural.wustl.edu.     

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 .     

Segregation and linkage analysis.

Computer programs are available in the software package SAGE to perform a variety of segregation and linkage analyses used by human geneticists. These methods are designed specifically to uncover major gene segregation in pedigree data coming from non-inbred populations. With the aid of a closely linked polymorphic marker, they can detect a locus that contributes as little as 10% to the variation of a quantitative trait in a pedigree sample of several hundred individuals.     

MLEP: an R package for exploring the maximum likelihood estimates of penetrance parameters

ABSTRACT: BACKGROUND: Linkage analysis is a useful tool for detecting genetic variants that regulate a trait of interest, especially genes associated with a given disease. Although penetrance parameters play an important role in determining gene location, they are assigned arbitrary values according to the researcher's intuition or as estimated by the maximum likelihood principle. Several methods exist by which to evaluate the maximum likelihood estimates of penetrance, although not all of these are supported by software packages and some are biased by marker genotype information, even when disease development is due solely to the genotype of a single allele. FINDINGS: Programs for exploring the maximum likelihood estimates of penetrance parameters were developed using the R statistical programming language supplemented by external C functions. The software returns a vector of polynomial coefficients of penetrance parameters, representing the likelihood of pedigree data. From the likelihood polynomial supplied by the proposed method, the likelihood value and its gradient can be precisely computed. To reduce the effect of the supplied dataset on the likelihood function, feasible parameter constraints can be introduced into maximum likelihood estimates, thus enabling flexible exploration of the penetrance estimates. An auxiliary program generates a perspective plot allowing visual validation of the model's convergence. The functions are collectively available as the MLEP R package. CONCLUSIONS: Linkage analysis using penetrance parameters estimated by the MLEP package enables feasible localization of a disease locus. This is shown through a simulation study and by demonstrating how the package is used to explore maximum likelihood estimates. Although the input dataset tends to bias the likelihood estimates, the method yields accurate results superior to the analysis using intuitive penetrance values for disease with low allele frequencies. MLEP is part of the Comprehensive R Archive Network and is freely available at http://cran.r-project.org/web/packages/MLEP/index.html.     

R/qtl: QTL mapping in experimental crosses

SUMMARY: R/qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental populations derived from inbred lines. It is implemented as an add-on package for the freely-available statistical software, R, and includes functions for estimating genetic maps, identifying genotyping errors, and performing single-QTL and two-dimensional, two-QTL genome scans by multiple methods, with the possible inclusion of covariates. AVAILABILITY: The package is freely available at http://www.biostat.jhsph.edu/~kbroman/qtl.     

Databases and software for the analysis of mutations in the human p53 gene, the human hprt gene and both the lacI and lacZ gene in transgenic rodents.

We have created databases and software applications for the analysis of DNA mutations at the humanp53gene, the humanhprtgene and both the rodent transgeniclacIandlacZlocus. The databases themselves are stand-alone dBASE files and the software for analysis of the databases runs on IBM-compatible computers. Each database has a separate software analysis program. The software created for these databases permit the filtering, ordering, report generation and display of information in the database. In addition, a significant number of routines have been developed for the analysis of single base substitutions. One method of obtaining the databases and software is via the World Wide Web (WWW). Open the following home page with a Web Browser: http://sunsite.unc.edu/dnam/mainpage.ht ml . Alternatively, the databases and programs are available via public FTP from: anonymous@sunsite.unc.edu . There is no password required to enter the system. The databases and software are found beneath the subdirectory: pub/academic/biology/dna-mutations. Two other programs are available at the site-a program for comparison of mutational spectra and a program for entry of mutational data into a relational database.     

ProDy: protein dynamics inferred from theory and experiments

SUMMARY: We developed a Python package, ProDy, for structure-based analysis of protein dynamics. ProDy allows for quantitative characterization of structural variations in heterogeneous datasets of structures experimentally resolved for a given biomolecular system, and for comparison of these variations with the theoretically predicted equilibrium dynamics. Datasets include structural ensembles for a given family or subfamily of proteins, their mutants and sequence homologues, in the presence/absence of their substrates, ligands or inhibitors. Numerous helper functions enable comparative analysis of experimental and theoretical data, and visualization of the principal changes in conformations that are accessible in different functional states. ProDy application programming interface (API) has been designed so that users can easily extend the software and implement new methods. AVAILABILITY: ProDy is open source and freely available under GNU General Public License from http://www.csb.pitt.edu/ProDy/.     

Statistical adjustment of signal censoring in gene expression experiments

MOTIVATION: Numerical output of spotted microarrays displays censoring of pixel intensities at some software dependent threshold. This reduces the quality of gene expression data, because it seriously violates the linearity of expression with respect to signal intensity. Statistical methods based on typically available spot summaries together with some parametric assumptions can suggest ways to correct for this defect. RESULTS: A maximum likelihood approach is suggested together with a sensible approximation to the joint density of the mean, median and variance-which are typically available to the biological end-user. The method 'corrects' the gene expression values for pixel censoring. A by-product of our approach is a comparison between several two-parameter models for pixel intensity values. It suggests that pixels separated by one or two other pixels can be considered independent draws from a Lognormal or a Gamma distribution. AVAILABILITY: The R/S-Plus code is available at http://www.stats.gla.ac.uk/~microarray/software.