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ConFind: a robust tool for conserved sequence identification.

SUMMARY: ConFind (conserved region finder) identifies regions of conservation in multiple sequence alignments that can serve as diagnostic targets. Designed to work with a large number of closely related, highly variable sequences, ConFind provides robust handling of alignments containing partial sequences and ambiguous characters. Conserved regions are defined in terms of minimum region length, maximum informational entropy (variability) per position, number of exceptions allowed to the maximum entropy criterion and the minimum number of sequences that must contain a non-ambiguous character at a position to be considered for inclusion in a conserved region. Comparison of the calculated entropy for an alignment of 95 influenza A hemagglutinin sequences with random deletions results in a 98% reduction in the average error in ConFind relative to the 'Find Conserved Regions' option in BioEdit. REQUIREMENTS: ConFind requires Python 2.3, but Python 2.4 or an upgrade of the optparse module to Optik 1.5 is suggested. The program is known to run under Linux and DOS.

Algorithms↗

Integrating multi-attribute similarity networks for robust representation of the protein space.

MOTIVATION: A global view of the protein space is essential for functional and evolutionary analysis of proteins. In order to achieve this, a similarity network can be built using pairwise relationships among proteins. However, existing similarity networks employ a single similarity measure and therefore their utility depends highly on the quality of the selected measure. A more robust representation of the protein space can be realized if multiple sources of information are used. RESULTS: We propose a novel approach for analyzing multi-attribute similarity networks by combining random walks on graphs with Bayesian theory. A multi-attribute network is created by combining sequence and structure based similarity measures. For each attribute of the similarity network, one can compute a measure of affinity from a given protein to every other protein in the network using random walks. This process makes use of the implicit clustering information of the similarity network, and we show that it is superior to naive, local ranking methods. We then combine the computed affinities using a Bayesian framework. In particular, when we train a Bayesian model for automated classification of a novel protein, we achieve high classification accuracy and outperform single attribute networks. In addition, we demonstrate the effectiveness of our technique by comparison with a competing kernel-based information integration approach.

Algorithms↗

Integrating copy number polymorphisms into array CGH analysis using a robust HMM.

MOTIVATION: Array comparative genomic hybridization (aCGH) is a pervasive technique used to identify chromosomal aberrations in human diseases, including cancer. Aberrations are defined as regions of increased or decreased DNA copy number, relative to a normal sample. Accurately identifying the locations of these aberrations has many important medical applications. Unfortunately, the observed copy number changes are often corrupted by various sources of noise, making the boundaries hard to detect. One popular current technique uses hidden Markov models (HMMs) to divide the signal into regions of constant copy number called segments; a subsequent classification phase labels each segment as a gain, a loss or neutral. Unfortunately, standard HMMs are sensitive to outliers, causing over-segmentation, where segments erroneously span very short regions. RESULTS: We propose a simple modification that makes the HMM robust to such outliers. More importantly, this modification allows us to exploit prior knowledge about the likely location of "outliers", which are often due to copy number polymorphisms (CNPs). By "explaining away" these outliers with prior knowledge about the locations of CNPs, we can focus attention on the more clinically relevant aberrated regions. We show significant improvements over the current state of the art technique (DNAcopy with MergeLevels) on previously published data from mantle cell lymphoma cell lines, and on published benchmark synthetic data augmented with outliers. AVAILABILITY: Source code written in Matlab is available from http://www.cs.ubc.ca/~sshah/acgh.

Artificial Intelligence↗

Robust estimation of the false discovery rate.

MOTIVATION: Presently available methods that use p-values to estimate or control the false discovery rate (FDR) implicitly assume that p-values are continuously distributed and based on two-sided tests. Therefore, it is difficult to reliably estimate the FDR when p-values are discrete or based on one-sided tests. RESULTS: A simple and robust method to estimate the FDR is proposed. The proposed method does not rely on implicit assumptions that tests are two-sided or yield continuously distributed p-values. The proposed method is proven to be conservative and have desirable large-sample properties. In addition, the proposed method was among the best performers across a series of 'real data simulations' comparing the performance of five currently available methods. AVAILABILITY: Libraries of S-plus and R routines to implement the method are freely available from www.stjuderesearch.org/depts/biostats.

Algorithms↗

Robust inference of positive selection from recombining coding sequences.

MOTIVATION: Accurate detection of positive Darwinian selection can provide important insights to researchers investigating the evolution of pathogens. However, many pathogens (particularly viruses) undergo frequent recombination and the phylogenetic methods commonly applied to detect positive selection have been shown to give misleading results when applied to recombining sequences. We propose a method that makes maximum likelihood inference of positive selection robust to the presence of recombination. This is achieved by allowing tree topologies and branch lengths to change across detected recombination breakpoints. Further improvements are obtained by allowing synonymous substitution rates to vary across sites. RESULTS: Using simulation we show that, even for extreme cases where recombination causes standard methods to reach false positive rates >90%, the proposed method decreases the false positive rate to acceptable levels while retaining high power. We applied the method to two HIV-1 datasets for which we have previously found that inference of positive selection is invalid owing to high rates of recombination. In one of these (env gene) we still detected positive selection using the proposed method, while in the other (gag gene) we found no significant evidence of positive selection. AVAILABILITY: A HyPhy batch language implementation of the proposed methods and the HIV-1 datasets analysed are available at http://www.cbio.uct.ac.za/pub_support/bioinf06. The HyPhy package is available at http://www.hyphy.org, and it is planned that the proposed methods will be included in the next distribution. RDP2 is available at http://darwin.uvigo.es/rdp/rdp.html

Base Sequence↗

Robust method for detecting differential gene expression in twin studies.

MOTIVATION: A steadily increasing number of experiments with microarrays stimulate the further development of the statistical methods of the analysis of gene expression data. One of the central problems in this area is detecting differential gene expression under two or more conditions. Unfortunately, up to now it has not been studied how the correlations between related individuals, such as twins influence the estimates of differential gene expression. RESULTS: In this paper, we discuss this problem and propose a new method that is robust with respect to correlations of gene expression data for twins.

Algorithms↗

Quantitative performance metrics for robustness in circadian rhythms.

MOTIVATION: Sensitivity analysis provides key measures that aid in unraveling the design principles responsible for the robust performance of biological networks. Such metrics allow researchers to investigate comprehensively model performance, to develop more realistic models, and to design informative experiments. However, sensitivity analysis of oscillatory systems focuses on period and amplitude characteristics, while biologically relevant effects on phase are neglected. RESULTS: Here, we introduce a novel set of phase-based sensitivity metrics for performance: period, phase, corrected phase and relative phase. Both state- and phase-based tools are applied to free-running Drosophila melanogaster and Mus musculus circadian models. Each metric produces unique sensitivity values used to rank parameters from least to most sensitive. Similarities among the resulting rank distributions strongly suggest a conservation of sensitivity with respect to parameter function and type. A consistent result, for instance, is that model performance of biological oscillators is more sensitive to global parameters than local (i.e. circadian specific) parameters. Discrepancies among these distributions highlight the individual metrics' definition of performance as specific parametric sensitivity values depend on the defined metric, or output. AVAILABILITY: An implementation of the algorithm in MATLAB (Mathworks, Inc.) is available from the authors. SUPPLEMENTARY INFORMATION: Supplementary Data are available at Bioinformatics online.

Animals↗

Robust prediction of consensus secondary structures using averaged base pairing probability matrices.

MOTIVATION: Recent transcriptomic studies have revealed the existence of a considerable number of non-protein-coding RNA transcripts in higher eukaryotic cells. To investigate the functional roles of these transcripts, it is of great interest to find conserved secondary structures from multiple alignments on a genomic scale. Since multiple alignments are often created using alignment programs that neglect the special conservation patterns of RNA secondary structures for computational efficiency, alignment failures can cause potential risks of overlooking conserved stem structures. RESULTS: We investigated the dependence of the accuracy of secondary structure prediction on the quality of alignments. We compared three algorithms that maximize the expected accuracy of secondary structures as well as other frequently used algorithms. We found that one of our algorithms, called McCaskill-MEA, was more robust against alignment failures than others. The McCaskill-MEA method first computes the base pairing probability matrices for all the sequences in the alignment and then obtains the base pairing probability matrix of the alignment by averaging over these matrices. The consensus secondary structure is predicted from this matrix such that the expected accuracy of the prediction is maximized. We show that the McCaskill-MEA method performs better than other methods, particularly when the alignment quality is low and when the alignment consists of many sequences. Our model has a parameter that controls the sensitivity and specificity of predictions. We discussed the uses of that parameter for multi-step screening procedures to search for conserved secondary structures and for assigning confidence values to the predicted base pairs. AVAILABILITY: The C++ source code that implements the McCaskill-MEA algorithm and the test dataset used in this paper are available at http://www.ncrna.org/papers/McCaskillMEA/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Algorithms↗

Robust modeling in screening studies: estimation of sensitivity and preclinical sojourn time distribution.

In early-detection clinical trials, quantities such as the sensitivity of the screening modality and the preclinical duration of the disease are important to describe the natural history of the disease and its interaction with a screening program. Assume that the schedule of a screening program is periodic and that the sojourn time in the preclinical state has a piecewise density function. Modeling the preclinical sojourn time distribution as a piecewise density function results in robust estimation of the distribution function. Our aim is to estimate the piecewise density function and the examination sensitivity using both generalized least squares and maximum likelihood methods. We carried out extensive simulations to evaluate the performance of the methods of estimation. The different estimation methods provide complimentary tools to obtain the unknown parameters. The methods are applied to three breast cancer early-detection trials.

Adult↗

Robust persistent neural activity in a model integrator with multiple hysteretic dendrites per neuron.

Short-term memory is often correlated with persistent changes in neuronal firing rates in response to transient inputs. We model the persistent maintenance of an analog eye position signal by an oculomotor neural integrator receiving transient eye movement commands. Previous models of this network rely on precisely tuned positive feedback with <1% tolerance to mistuning, or use neurons that exhibit large discontinuities in firing rate with small changes in eye position. We show analytically how using neurons with multiple bistable dendritic compartments can enhance the robustness of eye fixations to mistuning while reproducing the approximately linear and continuous relationship between neuronal firing rates and eye position, and the dependence of neuron pair firing rate relationships on the direction of the previous saccade. The response of the model to continuously varying inputs makes testable predictions for the performance of the vestibuloocular reflex. Our results suggest that dendritic bistability could stabilize the persistent neural activity observed in working memory systems.

Action Potentials↗

Aneuploid colon cancer cells have a robust spindle checkpoint.

Colon cancer cells frequently display minisatellite instability (MIN) or chromosome instability (CIN). While MIN is caused by mismatch repair defects, the lesions responsible for CIN are unknown. The observation that CIN cells fail to undergo mitotic arrest following spindle damage suggested that mutations in spindle checkpoint genes may account for CIN. However, here we show that CIN cells do undergo mitotic arrest in response to spindle damage. Although the maximum mitotic index achieved by CIN lines is diminished relative to MIN lines, CIN cells clearly have a robust spindle checkpoint. Consistently, mutations in spindle checkpoint genes are rare in human tumours. In contrast, the adenomatous polyposis coli (APC) gene is frequently mutated in CIN cells. Significantly, we show here that expression of an APC mutant in MIN cells reduces the mitotic index following spindle damage to a level observed in CIN cells, suggesting that APC dysfunction may contribute to CIN.

Adenomatous Polyposis Coli Protein↗

Oxidative stress resistance: a robust correlated response to selection in extended longevity lines of Drosophila melanogaster?

Stress resistance is associated with longevity in Drosophila melanogaster and other model organisms used for genetic research. The present study tests for oxidative stress resistance in one set of lines selected for late-life reproduction and extended longevity. Both females and males from the selected lines were appreciably more resistant to oxidative stress than were flies from the control lines. A relative increase in oxidative stress resistance is a correlated response to selection in this laboratory selection experiment. Increased oxidative stress resistance appears to be a relatively robust correlated response to laboratory selection for late-life reproduction and extended longevity.

Analysis of Variance↗

Robustness into advanced age of atopy-specific mechanisms in atopy-prone families.

We evaluated atopy-associated parameters in 1,099 people (aged 6-84 years) from families with history for atopy. All were tested for serum total immunoglobulin E (IgE) and allergen sensitivity by skin prick test. Specific IgE tests were done in randomly selected families. There was a decline with age in serum total IgE values, and relative atopy "incidence rates" were slightly lower among those older than 60 years. However, there was no change with age in sensitivity or severity of atopy. Among those sensitized to ragweed (Ambrosia artemisilfolia), there was no age-associated change in IgE levels specific to Amb a 1, a major allergen extracted from ragweed, and no change in the binding affinity of IgE for the Amb a 1 allergen. Among families with atopic histories, the underlying atopic mechanisms are particularly robust, and the atopic propensity remains into advanced age. In addition, established atopic responses may be focused in an immune system compartment either independent of or minimally influenced by T-cell activity.

Adolescent↗

Persistent, consistent, widespread, and robust? Another look at recent trends in old-age disability.

OBJECTIVE: The purpose of this study was to provide new evidence on disability trends among elderly persons from 1982 to 1996. METHODS: The sample includes 124,949 participants aged 70 and older in the 1982-1996 National Health Interview Surveys. Logistic analysis was used to estimate the trend in disability prevalence after controlling for various sociodemographic factors. RESULTS: We found that: (a) the prevalence of disability has declined, but the gains did not persist throughout the entire period or accelerate over time; (b) only routine care disability has declined, whereas more severe personal care disability shows no improvements; (c) estimates are robust to the exclusion of the nursing home population but may be sensitive to growth in the assisted living population; (d) estimates of decline in disability prevalence are fairly consistent across five national surveys; (e) gains have been concentrated among the most educated elderly persons; and (f) gains in education appear to be an important confounder of the improvements. DISCUSSION: Evidence from several surveys using various measures indicates that disability has declined among elderly persons. Determining the causes of the improvements should be a high priority in future research efforts.

Age Distribution↗

clusIBD: Robust Detection of Identity-by-descent Segments Using Unphased Genetic Data from Poor-quality Samples.

The detection of identity-by-descent (IBD) segments is widely used to infer relatedness in many fields, including forensics and ancient DNA analysis. However, existing methods are often ineffective for poor-quality DNA samples. Here, we propose a method, clusIBD, which can robustly detect IBD segments using unphased genetic data with a high rate of genotyping error. We evaluated and compared the performance of clusIBD with that of IBIS, TRUFFLE, and IBDseq using simulated data, artificial poor-quality materials, and ancient DNA samples. The results show that clusIBD outperforms these existing tools and could be used for kinship inference in fields such as ancient DNA analysis and criminal investigation. clusIBD is publicly available at GitHub (https://github.com/Ryan620/clusIBD/) and BioCode (https://ngdc.cncb.ac.cn/biocode/tool/BT007882).

Humans↗

Robustness of Ancestral Sequence Reconstruction to Among-site and Among-lineage Evolutionary Heterogeneity.

Ancestral sequence reconstruction is typically performed using homogeneous evolutionary models, which assume that the same substitution propensities affect all sites and lineages. These assumptions are routinely violated: heterogeneous structural and functional constraints favor different amino acids at different sites, and these constraints often change among lineages as epistatic substitutions accrue at other sites. To evaluate how violations of the homogeneity assumption affect ancestral sequence reconstruction under realistic conditions, we developed site-specific substitution models and parameterized them using data from deep mutational scanning experiments on three protein families; we then used these models to perform ancestral sequence reconstruction on the empirical alignments and on alignments simulated under heterogeneous conditions derived from the experiments. Extensive among-site and -lineage heterogeneity is present in these datasets, but the sequences reconstructed from empirical alignments are almost identical when heterogeneous or homogeneous models are used for ancestral sequence reconstruction. Using models fit to deep mutational scanning data from distantly related proteins in which mutational effects are very different also has a minimal impact on ancestral sequence reconstruction. The rare differences occur primarily where phylogenetic signal is weak-at fast-evolving sites and nodes connected by long branches. When ancestral sequence reconstruction is performed on simulated data, errors in the reconstructed sequences become more likely as branch lengths increase, but incorporating heterogeneity into the model does not improve accuracy. These data establish that ancestral sequence reconstruction is robust to unincorporated realistic forms of evolutionary heterogeneity, because the primary determinant of ancestral sequence reconstruction is phylogenetic signal, not the substitution model. The best way to improve accuracy is therefore not to develop more elaborate models but to apply ancestral sequence reconstruction to densely sampled alignments that maximize phylogenetic signal at the nodes of interest.

Phylogeny↗

Local ancestry inference identifies robust evidence of selection in Neolithic Europe.

During the European Neolithic, migrating Anatolian farmers admixed with local hunter-gatherers, coinciding with major shifts in diet, environment, and lifestyle that imposed strong selective pressures. Local ancestry inference is widely used to detect selection following admixture, but most methods were developed and validated on present-day populations. Their performance in ancient DNA - where reference panels are smaller, data are sparser, and admixture is more ancient - remains unresolved. We benchmark eight local ancestry inference methods on 176 imputed Neolithic genomes. While individual-level ancestry estimates are highly correlated across methods, inferred tract lengths and admixture time estimates vary by an order of magnitude. Overall, we recommend Gnomix or RFMix for general use. We also investigated our ability to detect natural selection using LAI. Integrating results across methods and replicating across methods and in two independent datasets (n=378 and 1,121) we identify a robust ancestry deviation at FADS1/2, consistent with adaptation on metabolism. We also identify IRAK4 (innate immunity) as a candidate locus, but with less consistent signal across methods. Finally, we replicate previous reports of excess hunter-gatherer ancestry at the HLA, but these results are inconsistent across methods and suggest that they may be affected by bias in local ancestry inference. Our findings demonstrate that while local ancestry inference recovers biologically meaningful signals in ancient genomes, results can be sensitive to the methods used for inference, particularly in complex regions like the HLA. Method choice critically influences inferred ancestry patterns and selection signals, underscoring the importance of multi-method validation.

Journal Article↗

A robust measure of HIV-1 population turnover within chronically infected individuals.

A simple nonparameteric test for population structure was applied to temporally spaced samples of HIV-1 sequences from the gag-pol region within two chronically infected individuals. The results show that temporal structure can be detected for samples separated by about 22 months or more. The performance of the method, which was originally proposed to detect geographic structure, was tested for temporally spaced samples using neutral coalescent simulations. Simulations showed that the method is robust to variation in samples sizes and mutation rates, to the presence/absence of recombination, and that the power to detect temporal structure is high. By comparing levels of temporal structure in simulations to the levels observed in real data, we estimate the effective intra-individual population size of HIV-1 to be between 10(3) and 10(4) viruses, which is in agreement with some previous estimates. Using this estimate and a simple measure of sequence diversity, we estimate an effective neutral mutation rate of about 5 x 10(-6) per site per generation in the gag-pol region. The definition and interpretation of estimates of such "effective" population parameters are discussed.

Evolution, Molecular↗