A population‐averaged approach to diagnostic test meta‐analysis

The meta‐analysis of diagnostic accuracy studies is often of interest in screening programs for many diseases. The typical summary statistics for studies chosen for a diagnostic accuracy meta‐analysis are often two dimensional: sensitivities and specificities. The common statistical analysis approach for the meta‐analysis of diagnostic studies is based on the bivariate generalized linear‐mixed model (BGLMM), which has study‐specific interpretations. In this article, we present a population‐averaged (PA) model using generalized estimating equations (GEE) for making inference on mean specificity and sensitivity of a diagnostic test in the population represented by the meta‐analytic studies. We also derive the marginalized counterparts of the regression parameters from the BGLMM. We illustrate the proposed PA approach through two dataset examples and compare performance of estimators of the marginal regression parameters from the PA model with those of the marginalized regression parameters from the BGLMM through Monte Carlo simulation studies. Overall, both marginalized BGLMM and GEE with sandwich standard errors maintained nominal 95% confidence interval coverage levels for mean specificity and mean sensitivity in meta‐analysis of 25 of more studies even under misspecification of the covariance structure of the bivariate positive test counts for diseased and nondiseased subjects.     

Individual‐based and stochastic modeling of cell population dynamics considering substrate dependency

In this article, we propose an individual‐based and stochastic modeling approach that is capable of describing the bacterial cell population dynamics during a batch culture. All stochastic nature inherent in intracellular molecular level reactions and cell division processes were considered in a single model framework by embedding a sub‐model describing individual cell's growth kinetics in a discrete event simulation algorithm. The resultant unique feature of the model is that the effects of the stochasticities on the cell population dynamics can be investigated for different substrate‐dependent cell growth kinetics. When Monod kinetics was used as the sub‐model, the stochasticities only slightly affected the cell mass increase and substrate consumption profiles during the batch culture although they were still important in describing the changes of cell population distributions. When Andrews substrate inhibition kinetics was used, however, it was revealed that the overall cell population dynamics could be seriously influenced by the stochasticities. Under a critical initial substrate level, the cell population could proliferate against the substrate inhibition only when the stochasticities were considered. Biotechnol. Bioeng. 2009;103: 891–899. © 2009 Wiley Periodicals, Inc.     

A chromatin structure‐based model accurately predicts DNA replication timing in human cells

The metazoan genome is replicated in precise cell lineage‐specific temporal order. However, the mechanism controlling this orchestrated process is poorly understood as no molecular mechanisms have been identified that actively regulate the firing sequence of genome replication. Here, we develop a mechanistic model of genome replication capable of predicting, with accuracy rivaling experimental repeats, observed empirical replication timing program in humans. In our model, replication is initiated in an uncoordinated (time‐stochastic) manner at well‐defined sites. The model contains, in addition to the choice of the genomic landmark that localizes initiation, only a single adjustable parameter of direct biological relevance: the number of replication forks. We find that DNase‐hypersensitive sites are optimal and independent determinants of DNA replication initiation. We demonstrate that the DNA replication timing program in human cells is a robust emergent phenomenon that, by its very nature, does not require a regulatory mechanism determining a proper replication initiation firing sequence.     

A generalized knowledge‐based discriminatory function for biomolecular interactions

Several novel and established knowledge‐based discriminatory function formulations and reference state derivations have been evaluated to identify parameter sets capable of distinguishing native and near‐native biomolecular interactions from incorrect ones. We developed the r·m·r function, a novel atomic level radial distribution function with mean reference state that averages over all pairwise atom types from a reduced atom type composition, using experimentally determined intermolecular complexes in the Cambridge Structural Database (CSD) and the Protein Data Bank (PDB) as the information sources. We demonstrate that r·m·r had the best discriminatory accuracy and power for protein‐small molecule and protein‐DNA interactions, regardless of whether the native complex was included or excluded, from the test set. The superior performance of the r·m·r discriminatory function compared with seventeen alternative functions evaluated on publicly available test sets for protein‐small molecule and protein‐DNA interactions indicated that the function was not over optimized through back testing on a single class of biomolecular interactions. The initial success of the reduced composition and superior performance with the CSD as the distribution set over the PDB implies that further improvements and generality of the function are possible by deriving probabilities from subsets of the CSD, using structures that consist of only the atom types to be considered for given biomolecular interactions. The method is available as a web server module at http://protinfo.compbio.washington.edu . Proteins 2009. © 2008 Wiley‐Liss, Inc.     

DNABind: A hybrid algorithm for structure‐based prediction of DNA‐binding residues by combining machine learning‐ and template‐based approaches

Accurate prediction of DNA‐binding residues has become a problem of increasing importance in structural bioinformatics. Here, we presented DNABind, a novel hybrid algorithm for identifying these crucial residues by exploiting the complementarity between machine learning‐ and template‐based methods. Our machine learning‐based method was based on the probabilistic combination of a structure‐based and a sequence‐based predictor, both of which were implemented using support vector machines algorithms. The former included our well‐designed structural features, such as solvent accessibility, local geometry, topological features, and relative positions, which can effectively quantify the difference between DNA‐binding and nonbinding residues. The latter combined evolutionary conservation features with three other sequence attributes. Our template‐based method depended on structural alignment and utilized the template structure from known protein–DNA complexes to infer DNA‐binding residues. We showed that the template method had excellent performance when reliable templates were found for the query proteins but tended to be strongly influenced by the template quality as well as the conformational changes upon DNA binding. In contrast, the machine learning approach yielded better performance when high‐quality templates were not available (about 1/3 cases in our dataset) or the query protein was subject to intensive transformation changes upon DNA binding. Our extensive experiments indicated that the hybrid approach can distinctly improve the performance of the individual methods for both bound and unbound structures. DNABind also significantly outperformed the state‐of‐art algorithms by around 10% in terms of Matthews's correlation coefficient. The proposed methodology could also have wide application in various protein functional site annotations. DNABind is freely available at http://mleg.cse.sc.edu/DNABind/ . Proteins 2013; 81:1885–1899. © 2013 Wiley Periodicals, Inc.     

Maternal factors in the origin of isolated oesophageal atresia: A population‐based case–control study

Background: In most patients affected by isolated oesophageal atresia (IOA) the etiology is largely unknown. Thus, the aim of this study was to analyze potential risk factors in mothers. Methods: The study samples included 221 cases with IOA, 356 matched and 38,151 population controls without any defect in the population‐based dataset of the Hungarian Case–Control Surveillance of Congenital Abnormalities, 1980 to 1996. Only those exposures were evaluated that were medically recorded in prenatal maternity logbooks during the critical period of IOA. Results: The findings of this case–control study suggested that the mothers of cases with IOA had a higher proportion of first delivery and lower socioeconomic status. Acute respiratory diseases (odds ratio [OR] 95% confidence interval [CI], 3.8, 1.8–8.1) and essential hypertension treated with nifedipine (OR 95% CI, 3.8, 1.7–8.7) in the mothers of cases associated with a higher risk for IOA in their children. Conclusion: First delivery, lower socioeconomic status, acute respiratory diseases and essential hypertension treated with nifedipine in the mothers may associate with a higher risk for IOA in their children. Birth Defects Research (Part A) 103:804–813, 2015. © 2015 Wiley Periodicals, Inc.     

Model‐Based Quality Assessment and Base‐Calling for Second‐Generation Sequencing Data

Summary Second‐generation sequencing (sec‐gen) technology can sequence millions of short fragments of DNA in parallel, making it capable of assembling complex genomes for a small fraction of the price and time of previous technologies. In fact, a recently formed international consortium, the 1000 Genomes Project, plans to fully sequence the genomes of approximately 1200 people. The prospect of comparative analysis at the sequence level of a large number of samples across multiple populations may be achieved within the next five years. These data present unprecedented challenges in statistical analysis. For instance, analysis operates on millions of short nucleotide sequences, or reads—strings of A,C,G, or T's, between 30 and 100 characters long—which are the result of complex processing of noisy continuous fluorescence intensity measurements known as base‐calling. The complexity of the base‐calling discretization process results in reads of widely varying quality within and across sequence samples. This variation in processing quality results in infrequent but systematic errors that we have found to mislead downstream analysis of the discretized sequence read data. For instance, a central goal of the 1000 Genomes Project is to quantify across‐sample variation at the single nucleotide level. At this resolution, small error rates in sequencing prove significant, especially for rare variants. Sec‐gen sequencing is a relatively new technology for which potential biases and sources of obscuring variation are not yet fully understood. Therefore, modeling and quantifying the uncertainty inherent in the generation of sequence reads is of utmost importance. In this article, we present a simple model to capture uncertainty arising in the base‐calling procedure of the Illumina/Solexa GA platform. Model parameters have a straightforward interpretation in terms of the chemistry of base‐calling allowing for informative and easily interpretable metrics that capture the variability in sequencing quality. Our model provides these informative estimates readily usable in quality assessment tools while significantly improving base‐calling performance.     

VIP Barcoding: composition vector‐based software for rapid species identification based on DNA barcoding

Species identification based on short sequences of DNA markers, that is, DNA barcoding, has emerged as an integral part of modern taxonomy. However, software for the analysis of large and multilocus barcoding data sets is scarce. The Basic Local Alignment Search Tool (BLAST) is currently the fastest tool capable of handling large databases (e.g. >5000 sequences), but its accuracy is a concern and has been criticized for its local optimization. However, current more accurate software requires sequence alignment or complex calculations, which are time‐consuming when dealing with large data sets during data preprocessing or during the search stage. Therefore, it is imperative to develop a practical program for both accurate and scalable species identification for DNA barcoding. In this context, we present VIP Barcoding: a user‐friendly software in graphical user interface for rapid DNA barcoding. It adopts a hybrid, two‐stage algorithm. First, an alignment‐free composition vector (CV) method is utilized to reduce searching space by screening a reference database. The alignment‐based K2P distance nearest‐neighbour method is then employed to analyse the smaller data set generated in the first stage. In comparison with other software, we demonstrate that VIP Barcoding has (i) higher accuracy than Blastn and several alignment‐free methods and (ii) higher scalability than alignment‐based distance methods and character‐based methods. These results suggest that this platform is able to deal with both large‐scale and multilocus barcoding data with accuracy and can contribute to DNA barcoding for modern taxonomy. VIP Barcoding is free and available at http://msl.sls.cuhk.edu.hk/vipbarcoding/ .     

Development and testing of a genetic marker‐based pedigree reconstruction system ‘PR‐genie’ incorporating size‐class data

For wildlife populations, it is often difficult to determine biological parameters that indicate breeding patterns and population mixing, but knowledge of these parameters is essential for effective management. A pedigree encodes the relationship between individuals and can provide insight into the dynamics of a population over its recent history. Here, we present a method for the reconstruction of pedigrees for wild populations of animals that live long enough to breed multiple times over their lifetime and that have complex or unknown generational structures. Reconstruction was based on microsatellite genotype data along with ancillary biological information: sex and observed body size class as an indicator of relative age of individuals within the population. Using body size‐class data to infer relative age has not been considered previously in wildlife genealogy and provides a marked improvement in accuracy of pedigree reconstruction. Body size‐class data are particularly useful for wild populations because it is much easier to collect noninvasively than absolute age data. This new pedigree reconstruction system, PR‐genie, performs reconstruction using maximum likelihood with optimization driven by the cross‐entropy method. We demonstrated pedigree reconstruction performance on simulated populations (comparing reconstructed pedigrees to known true pedigrees) over a wide range of population parameters and under assortative and intergenerational mating schema. Reconstruction accuracy increased with the presence of size‐class data and as the amount and quality of genetic data increased. We provide recommendations as to the amount and quality of data necessary to provide insight into detailed familial relationships in a wildlife population using this pedigree reconstruction technique.     

Epigenetic population differentiation in field‐ and common garden‐grown Scabiosa columbaria plants

Populations often differ in phenotype and these differences can be caused by adaptation by natural selection, random neutral processes, and environmental responses. The most straightforward way to divide mechanisms that influence phenotypic variation is heritable variation and environmental‐induced variation (e.g., plasticity). While genetic variation is responsible for most heritable phenotypic variation, part of this is also caused by nongenetic inheritance. Epigenetic processes may be one of the underlying mechanisms of plasticity and nongenetic inheritance and can therefore possibly contribute to heritable differences through drift and selection. Epigenetic variation may be influenced directly by the environment, and part of this variation can be transmitted to next generations. Field screenings combined with common garden experiments will add valuable insights into epigenetic differentiation, epigenetic memory and can help to reveal part of the relative importance of epigenetics in explaining trait variation. We explored both genetic and epigenetic diversity, structure and differentiation in the field and a common garden for five British and five French Scabiosa columbaria populations. Genetic and epigenetic variation was subsequently correlated with trait variation. Populations showed significant epigenetic differentiation between populations and countries in the field, but also when grown in a common garden. By comparing the epigenetic variation between field and common garden‐grown plants, we showed that a considerable part of the epigenetic memory differed from the field‐grown plants and was presumably environmentally induced. The memory component can consist of heritable variation in methylation that is not sensitive to environments and possibly genetically based, or environmentally induced variation that is heritable, or a combination of both. Additionally, random epimutations might be responsible for some differences as well. By comparing epigenetic variation in both the field and common environment, our study provides useful insight into the environmental and genetic components of epigenetic variation.     

Stacks 2: Analytical methods for paired‐end sequencing improve RADseq‐based population genomics

For half a century population genetics studies have put type II restriction endonucleases to work. Now, coupled with massively‐parallel, short‐read sequencing, the family of RAD protocols that wields these enzymes has generated vast genetic knowledge from the natural world. Here, we describe the first software natively capable of using paired‐end sequencing to derive short contigs from de novo RAD data. Stacks version 2 employs a de Bruijn graph assembler to build and connect contigs from forward and reverse reads for each de novo RAD locus, which it then uses as a reference for read alignments. The new architecture allows all the individuals in a metapopulation to be considered at the same time as each RAD locus is processed. This enables a Bayesian genotype caller to provide precise SNPs, and a robust algorithm to phase those SNPs into long haplotypes, generating RAD loci that are 400–800 bp in length. To prove its recall and precision, we tested the software with simulated data and compared reference‐aligned and de novo analyses of three empirical data sets. Our study shows that the latest version of Stacks is highly accurate and outperforms other software in assembling and genotyping paired‐end de novo data sets.     

Fluorescence‐based logic gate for sensing of Ca2+ and F− ions using PVP crowned chrysene nanoparticles in aqueous medium

Polyvinyl pyrrolidone (PVP) crowned chrysene nanoparticles (CHYNPs) were prepared by using a reprecipitation method. Dynamic light scattering (DLS) and scanning electron microscope (SEM) studies indicate that the monodispersed spherical nanoparticles bear a negative charge on their surfaces. The bathochromic spectral shift in the UV–visible and fluorescence spectrum of CHYNPs from chrysene (CHY) in acetone solution supports the J‐ type aggregation of nanoparticles. The aggregation‐induced enhanced emission of CHYNPs at 486 and 522 nm decreases by increasing the concentration of the Ca²⁺ ion solution. It can display an ON–OFF type fluorescence response with high selectivity towards Ca²⁺ ions aqueous medium. Furthermore, the in situ generated PVP–CHYNPs–Ca²⁺ ensemble could recover the quenched fluorescence upon the addition of fluoride anions resulting in an OFF–ON type sensor. The present method has a correlation coefficient R² = 0.988 with a detection limit of 1.22 μg/mL for Ca²⁺ in the aqueous medium. The fluorescence changes of PVP crowned CHYNPs upon the addition of Ca²⁺ and F^? can be utilized as an INHIBIT logic gate at the molecular level, using Ca²⁺ and F^? chemical inputs and the fluorescence intensity signal as output.     

A MinION™‐based pipeline for fast and cost‐effective DNA barcoding

DNA barcodes are useful for species discovery and species identification, but obtaining barcodes currently requires a well‐equipped molecular laboratory and is time‐consuming, and/or expensive. We here address these issues by developing a barcoding pipeline for Oxford Nanopore MinION? and demonstrating that one flow cell can generate barcodes for ~500 specimens despite the high basecall error rates of MinION? reads. The pipeline overcomes these errors by first summarizing all reads for the same tagged amplicon as a consensus barcode. Consensus barcodes are overall mismatch‐free but retain indel errors that are concentrated in homopolymeric regions. They are addressed with an optional error correction pipeline that is based on conserved amino acid motifs from publicly available barcodes. The effectiveness of this pipeline is documented by analysing reads from three MinION? runs that represent three different stages of MinION? development. They generated data for (i) 511 specimens of a mixed Diptera sample, (ii) 575 specimens of ants and (iii) 50 specimens of Chironomidae. The run based on the latest chemistry yielded MinION? barcodes for 490 of the 511 specimens which were assessed against reference Sanger barcodes (N = 471). Overall, the MinION? barcodes have an accuracy of 99.3%–100% with the number of ambiguous bases after correction ranging from <0.01% to 1.5% depending on which correction pipeline is used. We demonstrate that it requires ~2 hr of sequencing to gather all information needed for obtaining reliable barcodes for most specimens (>90%). We estimate that up to 1,000 barcodes can be generated in one flow cell and that the cost per barcode can be 相似文献   

Association of AKAP6 and MIR2113 with cognitive performance in a population‐based sample of older adults

Genetic factors make a substantial contribution to inter‐individual variability in cognitive function. A recent meta‐analysis of genome‐wide association studies identified two loci, AKAP6 and MIR2113, that are associated with general cognitive function. Here, we extend this previous research by investigating the association of MIR2113 and AKAP6 with baseline and longitudinal non‐linear change across a broad spectrum of cognitive domains in a community‐based cohort of older adults without dementia. Two single nucleotide polymorphisms (SNPs), MIR211‐rs10457441 and AKAP6‐rs17522122 were genotyped in 1570 non‐demented older Australians of European ancestry, who were examined up to 4 times over 12 years. Linear mixed effects models were used to examine the association between AKAP6 and MIR2113 with cognitive performance in episodic memory, working memory, vocabulary, perceptual speed and reaction time at baseline and with linear and quadratic rates of change. AKAP6‐rs17522122*T was associated with worse baseline performance in episodic memory, working memory, vocabulary and perceptual speed, but it was not associated with cognitive change in any domain. MIR2113‐rs10457441*T was associated with accelerated decline in episodic memory. No other associations with baseline cognitive performance or with linear or quadratic rate or cognitive changes were observed for this SNP. These results confirm the previous finding that AKAP6 is associated with performance across multiple cognitive domains at baseline but not with cognitive decline, while MIR2113 primarily affects the rate at which memory declines over time.