Correction for bias in visual transect censuses of coral reef fishes

Transect techniques for censusing reef fishes, and the sources of bias inherent in them are considered. A technique, derived from aeraly survey methods, is demonstrated to correct a bias in density estimates due to the width of the transect being censused. This bias is sufficient on a transect 1 m wide to underestimate density by 11.1–26.7% for five species or species groups examined. The bias is still greater on wider transects. Because this bias varies in degree among species, comparisons among species should not be made using uncorrected transect data. Comments are made on other probable sources of bias in transect data, and on ways of minimising bias when making visual transect censuses.     

The significance of redundancy in the genetic code

The genetic code has an inherent bias towards some amino acids because of the variable number of synonymous codons per amino acid. In proteins generally, this bias is expressed in the relative proportions of the twenty amino acids. It is suggested that even though neutral mutation may be responsible for the 'expression of this bias, the latter could be providing a positive advantage by directing mutation to introduce chemically simpler and more immutable amino acids where selective criteria have become relaxed.     

Equilibrating errors: reliable estimation of information transmission rates in biological systems with spectral analysis-based methods

Shannon’s seminal approach to estimating information capacity is widely used to quantify information processing by biological systems. However, the Shannon information theory, which is based on power spectrum estimation, necessarily contains two sources of error: time delay bias error and random error. These errors are particularly important for systems with relatively large time delay values and for responses of limited duration, as is often the case in experimental work. The window function type and size chosen, as well as the values of inherent delays cause changes in both the delay bias and random errors, with possibly strong effect on the estimates of system properties. Here, we investigated the properties of these errors using white-noise simulations and analysis of experimental photoreceptor responses to naturalistic and white-noise light contrasts. Photoreceptors were used from several insect species, each characterized by different visual performance, behavior, and ecology. We show that the effect of random error on the spectral estimates of photoreceptor performance (gain, coherence, signal-to-noise ratio, Shannon information rate) is opposite to that of the time delay bias error: the former overestimates information rate, while the latter underestimates it. We propose a new algorithm for reducing the impact of time delay bias error and random error, based on discovering, and then using that size of window, at which the absolute values of these errors are equal and opposite, thus cancelling each other, allowing minimally biased measurement of neural coding.     

Some Remarks on the Estimation of the Pair-Correlation Function for Point Processes

Doguwa (1990) proposed kernel based pair-correlation function estimators for Point processes. These estimators transport a part of the probability mass into the negative or left, to a hard-core distance. The reflection technique is used to provide an alternative estimator of the pair-correlation function, which drastically reduces the bias inherent in these estimators for the case of random and clustered point patterns. However, the drastic reduction in bias, is at the cost of a much larger variance.     

Maximum likelihood estimation of population growth rates based on the coalescent.

We describe a method for co-estimating 4Nemu (four times the product of effective population size and neutral mutation rate) and population growth rate from sequence samples using Metropolis-Hastings sampling. Population growth (or decline) is assumed to be exponential. The estimates of growth rate are biased upwards, especially when 4Nemu is low; there is also a slight upwards bias in the estimate of 4Nemu itself due to correlation between the parameters. This bias cannot be attributed solely to Metropolis-Hastings sampling but appears to be an inherent property of the estimator and is expected to appear in any approach which estimates growth rate from genealogy structure. Sampling additional unlinked loci is much more effective in reducing the bias than increasing the number or length of sequences from the same locus.     

Estimation of error rates in discriminant analysis with selection of variables

Accurate estimation of misclassification rates in discriminant analysis with selection of variables by, for example, a stepwise algorithm, is complicated by the large optimistic bias inherent in standard estimators such as those obtained by the resubstitution method. Application of a bootstrap adjustment can reduce the bias of the resubstitution method; however, the bootstrap technique requires the variable selection procedure to be repeated many times and is therefore difficult to compute. In this paper we propose a smoothed estimator that requires relatively little computation and which, on the basis of a Monte Carlo sampling study, is found to perform generally at least as well as the bootstrap method.     

Locomotor Adaptation and Leading Limb Asymmetries in Neonatal Chimpanzees (Pan troglodytes)

We assessed laterality for leading limb in crawling and leading limb in stepping in 13 chimpanzees (Pan troglodytes) during the first 3 months of life. Overall, there is a significant populational right-side bias for crawling but not for stepping. There is a significant negative correlation between laterality in stepping and crawling. The females are more right-sided in lateral bias than the males across both measures. These data suggest that asymmetries in postural organization are present early in life and are specific to the inherent locomotor behavior of a given species.     

Sex ratios observed in 80 species of parrots

A number of potential evolutionary and physiological factors may be involved in avian sex ratio bias so that under certain conditions a sex ratio bias may favour males or females within a population. In addition different factors may be important in manipulating sex ratio bias through the different life stages. In this study sex ratio bias was examined in a total of 16 570 captive parrots, representing 80 species, many of which are endangered in the wild, using database records originating form commercial laboratories that offer genetic sexing. Within the species examined 72% showed a male bias this was significant in three species, when adjusted for multiple comparisons. This preliminary study is limited due to lack of data on the age of the individuals sampled. However, the large dataset do suggest that this phenomenon should be further considered by investigators working at a species level where such data can be collected.     

Improved accuracy of quantitative birefringence imaging by polarization sensitive OCT with simple noise correction and its application to neuroimaging

Polarization-sensitive optical coherence tomography (PS-OCT) enables three-dimensional imaging of biological tissues based on the inherent contrast provided by scattering and polarization properties. In fibrous tissue such as the white matter of the brain, PS-OCT allows quantitative mapping of tissue birefringence. For the popular PS-OCT layout using a single circular input state, birefringence measurements are based on a straight-forward evaluation of phase retardation data. However, the accuracy of these measurements strongly depends on the signal-to-noise ratio (SNR) and is prone to mapping artifacts when the SNR is low. Here we present a simple yet effective approach for improving the accuracy of PS-OCT phase retardation and birefringence measurements. By performing a noise bias correction of the detected OCT signal amplitudes, the impact of the noise floor on retardation measurements can be markedly reduced. We present simulation data to illustrate the influence of the noise bias correction on phase retardation measurements and support our analysis with real-world PS-OCT image data.     

A rapid,efficient, and economical inverse polymerase chain reaction-based method for generating a site saturation mutant library

With the development of deep sequencing methodologies, it has become important to construct site saturation mutant (SSM) libraries in which every nucleotide/codon in a gene is individually randomized. We describe methodologies for the rapid, efficient, and economical construction of such libraries using inverse polymerase chain reaction (PCR). We show that if the degenerate codon is in the middle of the mutagenic primer, there is an inherent PCR bias due to the thermodynamic mismatch penalty, which decreases the proportion of unique mutants. Introducing a nucleotide bias in the primer can alleviate the problem. Alternatively, if the degenerate codon is placed at the 5′ end, there is no PCR bias, which results in a higher proportion of unique mutants. This also facilitates detection of deletion mutants resulting from errors during primer synthesis. This method can be used to rapidly generate SSM libraries for any gene or nucleotide sequence, which can subsequently be screened and analyzed by deep sequencing.     

The sequencing bias relaxed characteristics of Hi-C derived data and implications for chromatin 3D modeling

The 3D chromatin structure modeling by chromatin interactions derived from Hi-C experiments is significantly challenged by the intrinsic sequencing biases in these experiments. Conventional modeling methods only focus on the bias among different chromatin regions within the same experiment but neglect the bias arising from different experimental sequencing depth. We now show that the regional interaction bias is tightly coupled with the sequencing depth, and we further identify a chromatin structure parameter as the inherent characteristics of Hi-C derived data for chromatin regions. Then we present an approach for chromatin structure prediction capable of relaxing both kinds of sequencing biases by using this identified parameter. This method is validated by intra and inter cell-line comparisons among various chromatin regions for four human cell-lines (K562, GM12878, IMR90 and H1hESC), which shows that the openness of chromatin region is well correlated with chromatin function. This method has been executed by an automatic pipeline (AutoChrom3D) and thus can be conveniently used.     

Order‐Restricted Semiparametric Inference for the Power Bias Model

Summary The power bias model, a generalization of length‐biased sampling, is introduced and investigated in detail. In particular, attention is focused on order‐restricted inference. We show that the power bias model is an example of the density ratio model, or in other words, it is a semiparametric model that is specified by assuming that the ratio of several unknown probability density functions has a parametric form. Estimation and testing procedures under constraints are developed in detail. It is shown that the power bias model can be used for testing for, or against, the likelihood ratio ordering among multiple populations without resorting to any parametric assumptions. Examples and real data analysis demonstrate the usefulness of this approach.     

Distribution and evolution of sequence characteristics in the E. coli genome

The mean (G + C) composition (51.0%) and standard deviation (+/- 3.8%) of published DNA sequences accounting for 10% of the E. coli genome is in excellent agreement with the principal overall distribution determined by high resolution melting. While differences in base and neighbor characteristics are small and uniform throughout all regions of the genome, it is found that the (G + C) content of sequences varies in segmented fashion within boundaries corresponding to coding (53% G + C) and noncoding (46% G + C) regions; with variances in the latter being six-fold greater than in coding regions. The variance in different regions shows a strong negative dependence on (G + C) content of the region, reflecting the condition that A-T and G-C base pairs are preferred neighbors of A-T and C-G pairs, respectively; with the bias increasing with decreasing (G + C) content. Neighbor analysis indicates the most extreme positive biases occur in AA, TT, GC and CG throughout all regions, but particularly in noncoding regions. Extraordinary numbers of oligomeric strings of (A)n, etc., are the further consequence of this bias. These and other characteristics point to the existence of inherent biases in neighbor frequencies levied during replication or repair, and which reflect, in turn, neighbor influences during mutation. The bias in codon usage noted by Grantham and others is seen here as due, in part, to the adaptation of coding sequences to this microenvironment through selection among synonymous codons so as to preserve inherent neighbor biases.     

Large-scale insertional mutagenesis of a coleopteran stored grain pest, the red flour beetle Tribolium castaneum, identifies embryonic lethal mutations and enhancer traps

Background  

Given its sequenced genome and efficient systemic RNA interference response, the red flour beetle Tribolium castaneum is a model organism well suited for reverse genetics. Even so, there is a pressing need for forward genetic analysis to escape the bias inherent in candidate gene approaches.     

Estimating nucleotide diversity from random amplified polymorphic DNA and amplified fragment length polymorphism data

A way to estimate the index of nucleotide diversity (pi) from band match frequencies in random amplified polymorphic DNA and amplified fragment length polymorphism data is described. pi is shown to be a simple function of the proportion of mismatched bands between two individuals drawn at random from a population (phi) and the number of discriminating sites in the amplification system. The method is computationally and conceptually simple and avoids some of the assumptions inherent in other approaches: the relationship is independent of the base composition of the target DNA and avoids the bias inherent in estimations of allelic frequencies in dominant systems. Only two individuals from a population are needed to estimate pi. This economy of material suggests utility of this approach in conservation genetics or other fields where obtaining large samples is impractical or undesirable.     

Parental care and adaptive brood sex ratio manipulation in birds

Under many circumstances, it might be adaptive for parents to bias the investment in offspring in relation to sex. Recently developed molecular techniques that allow sex determination of newly hatched offspring have caused a surge in studies of avian sex allocation. Whether females bias the primary brood sex ratio in relation to factors such as environmental and parental quality is debated. Progress is hampered because the mechanisms for primary sex ratio manipulation are unknown. Moreover, publication bias against non-significant results may distort our view of adaptive sex ratio manipulation. Despite this, there is recent experimental evidence for adaptive brood sex ratio manipulation in birds. Parental care is a particularly likely candidate to affect the brood sex ratio because it can have strong direct effects on the fitness of both parents and their offspring. We investigate and make predictions of factors that can be important for adaptive brood sex ratio manipulation under different patterns of parental care. We encourage correlational studies based on sufficiently large datasets to ensure high statistical power, studies identifying and experimentally altering factors with sex-differential fitness effects that may cause brood sex ratio skew, and studies that experimentally manipulate brood sex ratio and investigate fitness effects.     

Weighted compromise trees: a method to summarize competing phylogenetic hypotheses

A new consensus method for summarizing competing phylogenetic hypotheses, weighted compromise, is described. The method corrects for a bias inherent in majority‐rule consensus/compromise trees when the source trees exhibit non‐independence due to ambiguity in terminal clades. Suggestions are given for its employment in parsimony analyses and tree resampling strategies such as bootstrapping and jackknifing. An R function is described that can be used with the programming language R to produce the consensus.     

Adjusting for selection bias in retrospective, case-control studies

Retrospective case–control studies are more susceptibleto selection bias than other epidemiologic studies as by designthey require that both cases and controls are representativeof the same population. However, as cases and control recruitmentprocesses are often different, it is not always obvious thatthe necessary exchangeability conditions hold. Selection biastypically arises when the selection criteria are associatedwith the risk factor under investigation. We develop a methodwhich produces bias-adjusted estimates for the odds ratio. Ourmethod hinges on 2 conditions. The first is that a variablethat separates the risk factor from the selection criteria canbe identified. This is termed the "bias breaking" variable.The second condition is that data can be found such that a bias-correctedestimate of the distribution of the bias breaking variable canbe obtained. We show by means of a set of examples that suchbias breaking variables are not uncommon in epidemiologic settings.We demonstrate using simulations that the estimates of the oddsratios produced by our method are consistently closer to thetrue odds ratio than standard odds ratio estimates using logisticregression. Further, by applying it to a case–controlstudy, we show that our method can help to determine whetherselection bias is present and thus confirm the validity of studyconclusions when no evidence of selection bias can be found.