Genetic association analysis with FAMHAP: a major program update

Summary: FAMHAP is an established software for haplotype associationanalysis of nuclear families. We have released a major updatethat comprises various new features for case-control data. Furthermore,weprovide an additional program runFamhap that allows usersto start the same method repeatedly for varying sets of geneticmarkers. In addition, a platform-independent graphical userinterface (GUI) was developed to simplify the usage of bothFAMHAP and runFamhap. The runFamhap program greatly facilitatesthe application of FAMHAP to genome-wide association studies(GWAS) and supports flexible genome-wide haplotype analysis.As an example, we describe application to HapMap data. Availability: The software is available at http://famhap.meb.uni-bonn.de Contact: herold{at}imbie.meb.uni-bonn.de; becker{at}imbie.meb.uni-bonn.de Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Alex Bateman     

CRONOS: the cross-reference navigation server

Summary: Cross-mapping of gene and protein identifiers betweendifferent databases is a tedious and time-consuming task. Toovercome this, we developed CRONOS, a cross-reference serverthat contains entries from five mammalian organisms presentedby major gene and protein information resources. Sequence similarityanalysis of the mapped entries shows that the cross-referencesare highly accurate. In total, up to 18 different identifiertypes can be used for identification of cross-references. Thequality of the mapping could be improved substantially by exclusionof ambiguous gene and protein names which were manually validated.Organism-specific lists of ambiguous terms, which are valuablefor a variety of bioinformatics applications like text miningare available for download. Availability: CRONOS is freely available to non-commercial usersat http://mips.gsf.de/genre/proj/cronos/index.html, web servicesare available at http://mips.gsf.de/CronosWSService/CronosWS?wsdl. Contact: brigitte.waegele{at}helmholtz-muenchen.de Supplementary information: Supplementary data are availableat Bioinformatics online. The online Supplementary Materialcontains all figures and tables referenced by this article. Associate Editor: Martin Bishop     

Unequal group variances in microarray data analyses

Motivation: In searching for differentially expressed (DE) genesin microarray data, we often observe a fraction of the genesto have unequal variability between groups. This is not an issuein large samples, where a valid test exists that uses individualvariances separately. The problem arises in the small-samplesetting, where the approximately valid Welch test lacks sensitivity,while the more sensitive moderated t-test assumes equal variance. Methods: We introduce a moderated Welch test (MWT) that allowsunequal variance between groups. It is based on (i) weightingof pooled and unpooled standard errors and (ii) improved estimationof the gene-level variance that exploits the information fromacross the genes. Results: When a non-trivial proportion of genes has unequalvariability, false discovery rate (FDR) estimates based on thestandard t and moderated t-tests are often too optimistic, whilethe standard Welch test has low sensitivity. The MWT is shownto (i) perform better than the standard t, the standard Welchand the moderated t-tests when the variances are unequal betweengroups and (ii) perform similarly to the moderated t, and betterthan the standard t and Welch tests when the group variancesare equal. These results mean that MWT is more reliable thanother existing tests over wider range of data conditions. Availability: R package to perform MWT is available at http://www.meb.ki.se/~yudpaw Contact: yudi.pawitan{at}ki.se Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Martin Bishop     

GENOME: a rapid coalescent-based whole genome simulator

Summary: GENOME proposes a rapid coalescent-based approach tosimulate whole genome data. In addition to features of standardcoalescent simulators, the program allows for recombinationrates to vary along the genome and for flexible population histories.Within small regions, we have evaluated samples simulated byGENOME to verify that GENOME provides the expected LD patternsand frequency spectra. The program can be used to study thesampling properties of any statistic for a whole genome study. Availability: The program and C++ source code are availableonline at http://www.sph.umich.edu/csg/liang/genome/ Contact: lianglim{at}umich.edu Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Martin Bishop     

Align human interactome with phenome to identify causative genes and networks underlying disease families

Motivation: Understanding the complexity in gene–phenotyperelationship is vital for revealing the genetic basis of commondiseases. Recent studies on the basis of human interactome andphenome not only uncovers prevalent phenotypic overlap and geneticoverlap between diseases, but also reveals a modular organizationof the genetic landscape of human diseases, providing new opportunitiesto reduce the complexity in dissecting the gene–phenotypeassociation. Results: We provide systematic and quantitative evidence thatphenotypic overlap implies genetic overlap. With these results,we perform the first heterogeneous alignment of human interactomeand phenome via a network alignment technique and identify 39disease families with corresponding causative gene networks.Finally, we propose AlignPI, an alignment-based framework topredict disease genes, and identify plausible candidates for70 diseases. Our method scales well to the whole genome, asdemonstrated by prioritizing 6154 genes across 37 chromosomeregions for Crohn's disease (CD). Results are consistent witha recent meta-analysis of genome-wide association studies forCD. Availability: Bi-modules and disease gene predictions are freelyavailable at the URL http://bioinfo.au.tsinghua.edu.cn/alignpi/ Contact: ruijiang{at}tsinghua.edu.cn Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Trey Ideker     

Model-based deconvolution of genome-wide DNA binding

Motivation: Chromatin immunoprecipitation followed by hybridizationto a genomic tiling microarray (ChIP-chip) is a routinely usedprotocol for localizing the genomic targets of DNA-binding proteins.The resolution to which binding sites in this assay can be identifiedis commonly considered to be limited by two factors: (1) theresolution at which the genomic targets are tiled in the microarrayand (2) the large and variable lengths of the immunoprecipitatedDNA fragments. Results: We have developed a generative model of binding sitesin ChIP-chip data and an approach, MeDiChI, for efficientlyand robustly learning that model from diverse data sets. Wehave evaluated MeDiChI's performance using simulated data, aswell as on several diverse ChIP-chip data sets collected onwidely different tiling array platforms for two different organisms(Saccharomyces cerevisiae and Halobacterium salinarium NRC-1).We find that MeDiChI accurately predicts binding locations toa resolution greater than that of the probe spacing, even foroverlapping peaks, and can increase the effective resolutionof tiling array data by a factor of 5x or better. Moreover,the method's performance on simulated data provides insightsinto effectively optimizing the experimental design for increasedbinding site localization accuracy and efficacy. Availability: MeDiChI is available as an open-source R package,including all data, from http://baliga.systemsbiology.net/medichi. Contact: dreiss{at}systemsbiology.org Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Martin Bishop     

DeconMSn: a software tool for accurate parent ion monoisotopic mass determination for tandem mass spectra

Summary: DeconMSn accurately determines the monoisotopic massand charge state of parent ions from high-resolution tandemmass spectrometry data, offering significant improvement forLTQ_FT and LTQ_Orbitrap instruments over the commercially deliveredThermo Fisher Scientific's extract_msn tool. Optimal parention mass tolerance values can be determined using accurate massinformation, thus improving peptide identifications for high-massmeasurement accuracy experiments. For low-resolution data fromLCQ and LTQ instruments, DeconMSn incorporates a support-vector-machine-basedcharge detection algorithm that identifies the most likely chargeof a parent species through peak characteristics of its fragmentationpattern. Availability: http://ncrr.pnl.gov/software/ or http://www.proteomicsresource.org/ Contact: rds{at}pnl.gov Supplementary information: PowerPoint presentation/Poster onhttp://ncrr.pnl.gov/software/. Associate Editor: Alfonso Valencia     

The effect of sequence quality on sequence alignment

Motivation: The nucleotide sequencing process produces not onlythe sequence of nucleotides, but also associated quality values.Quality values provide valuable information, but are primarilyused only for trimming sequences and generally ignored in subsequentanalyses. Results: This article describes how the scoring schemes of standardalignment algorithms can be modified to take into account qualityvalues to produce improved alignments and statistically moreaccurate scores. A prototype implementation is also provided,and used to post-process a set of BLAST results. Quality-adjustedalignment is a natural extension of standard alignment methods,and can be implemented with only a small constant factor performancepenalty. The method can also be applied to related methods includingheuristic search algorithms like BLAST and FASTA. Availability: Software is available at http://malde.org/~ketil/qaa. Contact: ketil.malde{at}imr.no Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Limsoon Wong     

Disease association tests by inferring ancestral haplotypes using a hidden markov model

Motivation: Most genome-wide association studies rely on singlenucleotide polymorphism (SNP) analyses to identify causal loci.The increased stringency required for genome-wide analyses (withper-SNP significance threshold typically 10^–7) meansthat many real signals will be missed. Thus it is still highlyrelevant to develop methods with improved power at low typeI error. Haplotype-based methods provide a promising approach;however, they suffer from statistical problems such as abundanceof rare haplotypes and ambiguity in defining haplotype blockboundaries. Results: We have developed an ancestral haplotype clustering(AncesHC) association method which addresses many of these problems.It can be applied to biallelic or multiallelic markers typedin haploid, diploid or multiploid organisms, and also handlesmissing genotypes. Our model is free from the assumption ofa rigid block structure but recognizes a block-like structureif it exists in the data. We employ a Hidden Markov Model (HMM)to cluster the haplotypes into groups of predicted common ancestralorigin. We then test each cluster for association with diseaseby comparing the numbers of cases and controls with 0, 1 and2 chromosomes in the cluster. We demonstrate the power of thisapproach by simulation of case-control status under a rangeof disease models for 1500 outcrossed mice originating fromeight inbred lines. Our results suggest that AncesHC has substantiallymore power than single-SNP analyses to detect disease association,and is also more powerful than the cladistic haplotype clusteringmethod CLADHC. Availability: The software can be downloaded from http://www.imperial.ac.uk/medicine/people/l.coin Contact: I.coin{at}imperial.ac.uk Supplementary Information: Supplementary data are availableat Bioinformatics online. Associate Editor: Martin Bishop     

Combining multiple positive training sets to generate confidence scores for protein-protein interactions

Motivation: High-throughput experimental and computational methodsare generating a wealth of protein–protein interactiondata for a variety of organisms. However, data produced by currentstate-of-the-art methods include many false positives, whichcan hinder the analyses needed to derive biological insights.One way to address this problem is to assign confidence scoresthat reflect the reliability and biological significance ofeach interaction. Most previously described scoring methodsuse a set of likely true positives to train a model to scoreall interactions in a dataset. A single positive training set,however, may be biased and not representative of true interactionspace. Results: We demonstrate a method to score protein interactionsby utilizing multiple independent sets of training positivesto reduce the potential bias inherent in using a single trainingset. We used a set of benchmark yeast protein interactions toshow that our approach outperforms other scoring methods. Ourapproach can also score interactions across data types, whichmakes it more widely applicable than many previously proposedmethods. We applied the method to protein interaction data fromboth Drosophila melanogaster and Homo sapiens. Independent evaluationsshow that the resulting confidence scores accurately reflectthe biological significance of the interactions. Contact: rfinley{at}wayne.edu Supplementary information: Supplementary data are availableat Bioinformatics Online. Associate Editor: Burkhard Rost     

A new algorithm for cluster analysis of genomic methylation: the Helicobacter pylori case

Motivation: The genomic methylation analysis is useful to typebacteria that have a high number of expressed type II methyltransferases.Methyltransferases are usually committed to Restriction andModification (R-M) systems, in which the restriction endonucleaseimposes high pressure on the expression of the cognate methyltransferasethat hinder R-M system loss. Conventional cluster methods donot reflect this tendency. An algorithm was developed for dendrogramconstruction reflecting the propensity for conservation of R-MType II systems. Results: The new algorithm was applied to 52 Helicobacter pyloristrains from different geographical regions and compared withconventional clustering methods. The algorithm works by firstgrouping strains that share a common minimum set of R-M systemsand gradually adds strains according to the number of the R-Msystems acquired. Dendrograms revealed a cluster of Africanstrains, which suggest that R-M systems are present in H.pylorigenome since its human host migrates from Africa. Availability: The software files are available at http://www.ff.ul.pt/paginas/jvitor/Bioinformatics/MCRM_algorithm.zip Contact: filipavale{at}fe.ucp.pt Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Martin Bishop     

Observation of multiple folding pathways of beta-hairpin trpzip2 from independent continuous folding trajectories

Motivation: After 10-year investigations, the folding mechanismsof β-hairpins are still under debate. Experiments stronglysupport zip-out pathway, while most simulations prefer the hydrophobiccollapse model (including middle-out and zip-in pathways). Inthis article, we show that all pathways can occur during thefolding of β-hairpins but with different probabilities.The zip-out pathway is the most probable one. This is in agreementwith the experimental results. We came to our conclusions by38 100-ns room-temperature all-atom molecular dynamics simulationsof the β-hairpin trpzip2. Our results may help to clarifythe inconsistencies in the current pictures of β-hairpinfolding mechanisms. Contact: yxiao{at}mail.hust.edu.cn Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Anna Tramontano     

3D-Garden: a system for modelling protein-protein complexes based on conformational refinement of ensembles generated with the marching cubes algorithm

Motivation: Reliable structural modelling of protein–proteincomplexes has widespread application, from drug design to advancingour knowledge of protein interactions and function. This workaddresses three important issues in protein–protein docking:implementing backbone flexibility, incorporating prior indicationsfrom experiment and bioinformatics, and providing public accessvia a server. 3D-Garden (Global And Restrained Docking ExplorationNexus), our benchmarked and server-ready flexible docking system,allows sophisticated programming of surface patches by the uservia a facet representation of the interactors’ molecularsurfaces (generated with the marching cubes algorithm). Flexibilityis implemented as a weighted exhaustive conformer search foreach clashing pair of molecular branches in a set of 5000 modelsfiltered from around 340 000 initially. Results: In a non-global assessment, carried out strictly accordingto the protocols for number of models considered and model qualityof the Critical Assessment of Protein Interactions (CAPRI) experiment,over the widely-used Benchmark 2.0 of 84 complexes, 3D-Gardenidentifies a set of ten models containing an acceptable or bettermodel in 29/45 test cases, including one with large conformationalchange. In 19/45 cases an acceptable or better model is rankedfirst or second out of 340 000 candidates. Availability: http://www.sbg.bio.ic.ac.uk/3dgarden (server) Contact: v.lesk{at}ic.ac.uk Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Burkhard Rost     

Bayesian models based on test statistics for multiple hypothesis testing problems

Motivation: We propose a Bayesian method for the problem ofmultiple hypothesis testing that is routinely encountered inbioinformatics research, such as the differential gene expressionanalysis. Our algorithm is based on modeling the distributionsof test statistics under both null and alternative hypotheses.We substantially reduce the complexity of the process of definingposterior model probabilities by modeling the test statisticsdirectly instead of modeling the full data. Computationally,we apply a Bayesian FDR approach to control the number of rejectionsof null hypotheses. To check if our model assumptions for thetest statistics are valid for various bioinformatics experiments,we also propose a simple graphical model-assessment tool. Results: Using extensive simulations, we demonstrate the performanceof our models and the utility of the model-assessment tool.In the end, we apply the proposed methodology to an siRNA screeningand a gene expression experiment. Contact: yuanji{at}mdanderson.org Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Chris Stoeckert     

e-LiSe--an online tool for finding needles in the '(Medline) haystack'

Summary: Using literature databases one can find not only knownand true relations between processes but also less studied,non-obvious associations. The main problem with discoveringsuch type of relevant biological information is ‘selection’.The ability to distinguish between a true correlation (e.g.between different types of biological processes) and randomchance that this correlation is statistically significant iscrucial for any bio-medical research, literature mining beingno exception. This problem is especially visible when searchingfor information which has not been studied and described inmany publications. Therefore, a novel bio-linguistic statisticalmethod is required, capable of ‘selecting’ truecorrelations, even when they are low-frequency associations.In this article, we present such statistical approach basedon Z-score and implemented in a web-based application ‘e-LiSe’. Availability: The software is available at http://miron.ibb.waw.pl/elise/ Contact: piotr{at}ibb.waw.pl Supplementary information: Supplementary materials are availableat http://miron.ibb.waw.pl/elise/supplementary/ Associate Editor: Alfonso Valencia