Sampling, WLS, and Mixed Models

Mixed models may be defined with or without reference to sampling, and can be used to predict realized random effects, as when estimating the latent values of study subjects measured with response error. When the model is specified without reference to sampling, a simple mixed model includes two random variables, one stemming from an exchangeable distribution of latent values of study subjects and the other, from the study subjects` response error distributions. Positive probabilities are assigned to both potentially realizable responses and artificial responses that are not potentially realizable, resulting in artificial latent values. In contrast, finite population mixed models represent the two-stage process of sampling subjects and measuring their responses, where positive probabilities are only assigned to potentially realizable responses. A comparison of the estimators over the same potentially realizable responses indicates that the optimal linear mixed model estimator (the usual best linear unbiased predictor, BLUP) is often (but not always) more accurate than the comparable finite population mixed model estimator (the FPMM BLUP). We examine a simple example and provide the basis for a broader discussion of the role of conditioning, sampling, and model assumptions in developing inference.

Spatial pattern detection modeling of thrips (Thrips tabaci) on onion fields

Onion (Allium cepa) is one of the most cultivated and consumed vegetables in Brazil and its importance is due to the large laborforce involved. One of the main pests that affect this crop is the Onion Thrips (Thrips tabaci), but the spatial distribution of this insect, although important, has not been considered in crop management recommendations, experimental planning or sampling procedures. Our purpose here is to consider statistical tools to detect and model spatial patterns of the occurrence of the onion thrips. In order to characterize the spatial distribution pattern of the Onion Thrips a survey was carried out to record the number of insects in each development phase on onion plant leaves, on different dates and sample locations, in four rural properties with neighboring farms under different infestation levels and planting methods. The Mantel randomization test proved to be a useful tool to test for spatial correlation which, when detected, was described by a mixed spatial Poisson model with a geostatistical random component and parameters allowing for a characterization of the spatial pattern, as well as the production of prediction maps of susceptibility to levels of infestation throughout the area.

Temporal variation of the phytoplankton community at short sampling intervals in the Mundaú reservoir, Northeastern Brazil

The aim of this study was to determine how abiotic factors drive the phytoplankton community in a water supply reservoir within short sampling intervals. Samples were collected at the subsurface (0.1 m) and bottom of limnetic (8 m) and littoral (2 m) zones in both the dry and rainy seasons. The following abiotic variables were analyzed: water temperature, dissolved oxygen, electrical conductivity, total dissolved solids, turbidity, pH, total nitrogen, nitrite, nitrate, total phosphorus, total dissolved phosphorus and orthophosphate. Phytoplankton biomass was determined from biovolume values. The role abiotic variables play in the dynamics of phytoplankton species was determined by means of Canonical Correspondence Analysis. Algae biomass ranged from 1.17×10(4) to 9.21×10(4) µg.L-1; cyanobacteria had biomass values ranging from 1.07×10(4) to 8.21×10(4) µg.L-1. High availability of phosphorous, nitrogen limitation, alkaline pH and thermal stability all favored cyanobacteria blooms, particularly during the dry season. Temperature, pH, total phosphorous and turbidity were key factors in characterizing the phytoplankton community between sampling times and stations. Of the species studied, Cylindrospermopsis raciborskii populations were dominant in the phytoplankton in both the dry and rainy seasons. We conclude that the phytoplankton was strongly influenced by abiotic variables, particularly in relation to seasonal distribution patterns.

Searching for molecular markers in head and neck squamous cell carcinomas (HNSCC) by statistical and bioinformatic analysis of larynx-derived SAGE libraries

Background: Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies in humans. The average 5-year survival rate is one of the lowest among aggressive cancers, showing no significant improvement in recent years. When detected early, HNSCC has a good prognosis, but most patients present metastatic disease at the time of diagnosis, which significantly reduces survival rate. Despite extensive research, no molecular markers are currently available for diagnostic or prognostic purposes. Methods: Aiming to identify differentially-expressed genes involved in laryngeal squamous cell carcinoma (LSCC) development and progression, we generated individual Serial Analysis of Gene Expression (SAGE) libraries from a metastatic and non-metastatic larynx carcinoma, as well as from a normal larynx mucosa sample. Approximately 54,000 unique tags were sequenced in three libraries. Results: Statistical data analysis identified a subset of 1,216 differentially expressed tags between tumor and normal libraries, and 894 differentially expressed tags between metastatic and non-metastatic carcinomas. Three genes displaying differential regulation, one down-regulated (KRT31) and two up-regulated (BST2, MFAP2), as well as one with a non-significant differential expression pattern (GNA15) in our SAGE data were selected for real-time polymerase chain reaction (PCR) in a set of HNSCC samples. Consistent with our statistical analysis, quantitative PCR confirmed the upregulation of BST2 and MFAP2 and the downregulation of KRT31 when samples of HNSCC were compared to tumor-free surgical margins. As expected, GNA15 presented a non-significant differential expression pattern when tumor samples were compared to normal tissues. Conclusion: To the best of our knowledge, this is the first study reporting SAGE data in head and neck squamous cell tumors. Statistical analysis was effective in identifying differentially expressed genes reportedly involved in cancer development. The differential expression of a subset of genes was confirmed in additional larynx carcinoma samples and in carcinomas from a distinct head and neck subsite. This result suggests the existence of potential common biomarkers for prognosis and targeted-therapy development in this heterogeneous type of tumor.

Precision of distances and ordering of microsatellite markers in consensus linkage maps of chromosomes 1, 3 and 4 from two reciprocal chicken populations using bootstrap sampling

Some factors complicate comparisons between linkage maps from different studies. This problem can be resolved if measures of precision, such as confidence intervals and frequency distributions, are associated with markers. We examined the precision of distances and ordering of microsatellite markers in the consensus linkage maps of chromosomes 1, 3 and 4 from two F 2 reciprocal Brazilian chicken populations, using bootstrap sampling. Single and consensus maps were constructed. The consensus map was compared with the International Consensus Linkage Map and with the whole genome sequence. Some loci showed segregation distortion and missing data, but this did not affect the analyses negatively. Several inversions and position shifts were detected, based on 95% confidence intervals and frequency distributions of loci. Some discrepancies in distances between loci and in ordering were due to chance, whereas others could be attributed to other effects, including reciprocal crosses, sampling error of the founder animals from the two populations, F(2) population structure, number of and distance between microsatellite markers, number of informative meioses, loci segregation patterns, and sex. In the Brazilian consensus GGA1, locus LEI1038 was in a position closer to the true genome sequence than in the International Consensus Map, whereas for GGA3 and GGA4, no such differences were found. Extending these analyses to the remaining chromosomes should facilitate comparisons and the integration of several available genetic maps, allowing meta-analyses for map construction and quantitative trait loci (QTL) mapping. The precision of the estimates of QTL positions and their effects would be increased with such information.

Phylogenetic relationships within the speciose family Characidae (Teleostei: Ostariophysi: Characiformes) based on multilocus analysis and extensive ingroup sampling

Background: With nearly 1,100 species, the fish family Characidae represents more than half of the species of Characiformes, and is a key component of Neotropical freshwater ecosystems. The composition, phylogeny, and classification of Characidae is currently uncertain, despite significant efforts based on analysis of morphological and molecular data. No consensus about the monophyly of this group or its position within the order Characiformes has been reached, challenged by the fact that many key studies to date have non-overlapping taxonomic representation and focus only on subsets of this diversity. Results: In the present study we propose a new definition of the family Characidae and a hypothesis of relationships for the Characiformes based on phylogenetic analysis of DNA sequences of two mitochondrial and three nuclear genes (4,680 base pairs). The sequences were obtained from 211 samples representing 166 genera distributed among all 18 recognized families in the order Characiformes, all 14 recognized subfamilies in the Characidae, plus 56 of the genera so far considered incertae sedis in the Characidae. The phylogeny obtained is robust, with most lineages significantly supported by posterior probabilities in Bayesian analysis, and high bootstrap values from maximum likelihood and parsimony analyses. Conclusion: A monophyletic assemblage strongly supported in all our phylogenetic analysis is herein defined as the Characidae and includes the characiform species lacking a supraorbital bone and with a derived position of the emergence of the hyoid artery from the anterior ceratohyal. To recognize this and several other monophyletic groups within characiforms we propose changes in the limits of several families to facilitate future studies in the Characiformes and particularly the Characidae. This work presents a new phylogenetic framework for a speciose and morphologically diverse group of freshwater fishes of significant ecological and evolutionary importance across the Neotropics and portions of Africa.

An empirical evaluation of imputation accuracy for association statistics reveals increased type-I error rates in genome-wide associations

Background: Genome wide association studies (GWAS) are becoming the approach of choice to identify genetic determinants of complex phenotypes and common diseases. The astonishing amount of generated data and the use of distinct genotyping platforms with variable genomic coverage are still analytical challenges. Imputation algorithms combine directly genotyped markers information with haplotypic structure for the population of interest for the inference of a badly genotyped or missing marker and are considered a near zero cost approach to allow the comparison and combination of data generated in different studies. Several reports stated that imputed markers have an overall acceptable accuracy but no published report has performed a pair wise comparison of imputed and empiric association statistics of a complete set of GWAS markers. Results: In this report we identified a total of 73 imputed markers that yielded a nominally statistically significant association at P < 10(-5) for type 2 Diabetes Mellitus and compared them with results obtained based on empirical allelic frequencies. Interestingly, despite their overall high correlation, association statistics based on imputed frequencies were discordant in 35 of the 73 (47%) associated markers, considerably inflating the type I error rate of imputed markers. We comprehensively tested several quality thresholds, the haplotypic structure underlying imputed markers and the use of flanking markers as predictors of inaccurate association statistics derived from imputed markers. Conclusions: Our results suggest that association statistics from imputed markers showing specific MAF (Minor Allele Frequencies) range, located in weak linkage disequilibrium blocks or strongly deviating from local patterns of association are prone to have inflated false positive association signals. The present study highlights the potential of imputation procedures and proposes simple procedures for selecting the best imputed markers for follow-up genotyping studies.

Comparative analysis of two sampling techniques for pollen gathered by Nannotrigona testaceicornis Lepeletier (Apidae, Meliponini)

Pollen counts from samples taken from storage pots throughout one year (from October to September) were adjusted by Tasei's volumetric correction coefficient for the determination of pollen sources exploited by two colonies of Nannotrigona testaceicornis in Sao Paulo, Brazil. The results obtained by this sampling technique for seven months (December to June) were compared with those from corbicula load samples taken within the same period. This species visited a large variety of plant species, but few of them were frequently used. As a rule, pollen sources that appeared at frequencies greater than 1% were found with both sampling methods and significant positive correlations (Spearman correlation coefficient) were found between their values. The pollen load sample data showed that N. testaceicornis gathered pollen throughout the external activity period.

Statistics of opinion domains of the majority-vote model on a square lattice

The existence of juxtaposed regions of distinct cultures in spite of the fact that people's beliefs have a tendency to become more similar to each other's as the individuals interact repeatedly is a puzzling phenomenon in the social sciences. Here we study an extreme version of the frequency-dependent bias model of social influence in which an individual adopts the opinion shared by the majority of the members of its extended neighborhood, which includes the individual itself. This is a variant of the majority-vote model in which the individual retains its opinion in case there is a tie among the neighbors' opinions. We assume that the individuals are fixed in the sites of a square lattice of linear size L and that they interact with their nearest neighbors only. Within a mean-field framework, we derive the equations of motion for the density of individuals adopting a particular opinion in the single-site and pair approximations. Although the single-site approximation predicts a single opinion domain that takes over the entire lattice, the pair approximation yields a qualitatively correct picture with the coexistence of different opinion domains and a strong dependence on the initial conditions. Extensive Monte Carlo simulations indicate the existence of a rich distribution of opinion domains or clusters, the number of which grows with L(2) whereas the size of the largest cluster grows with ln L(2). The analysis of the sizes of the opinion domains shows that they obey a power-law distribution for not too large sizes but that they are exponentially distributed in the limit of very large clusters. In addition, similarly to other well-known social influence model-Axelrod's model-we found that these opinion domains are unstable to the effect of a thermal-like noise.

Method for cadmium and lead longitudinal profiles determination in hair by solid sampling graphite furnace atomic absorption spectrometry

This paper describes methods for the direct determination of Cd and Pb in hair segments (c.a. 5 mm similar to 80 mu g) by solid sampling graphite furnace atomic absorption spectrometry, becoming possible longitudinal profiles in a single strand of hair. To distinguish endogenous and exogenous content. strands of hair were washed by using two different procedures: IAEA protocol (acetone + water + acetone) and the combination of IAEA protocol with HCl washing (acetone + water + acetone + 0.1 mol l(-1) HCl). The concentration of Cd and Pb increased from the root Until the tip of hair washed according to IAEA protocol. However, when the strand of hair was washed using the combination of IAEA protocol and 0.1 mol l(-1) HCl, Cd concentrations decreased in all segments, and Pb concentrations decreased drastically near to the root (5 to 12 mm) and was systematically higher ill the end. The proposed method showed to be useful to assess the temporal variation to Cd and Pb exposure and call be Used for toxicological and environmental investigations. The limits of detection were 2.8 ng g(-1) for Cd and 40 ng g(-1) for Pb. The characteristic masses based oil integrated absorbance were 2.4 pg for Cd and 22 pg for Pb.

Simultaneous determination of Cr, Fe, Ni and V in crude oil by emulsion sampling graphite furnace atomic absorption spectrometry

In this work a simple and reliable method for the simultaneous determination of Cr, Fe, Ni and V in crude oil, using emulsion sampling graphite furnace atomic absorption spectrometry is proposed. Under the best conditions, sample masses around 50 mg were weighed in polypropylene tubes and emulsified in a mixture of 0.5% (v v(-1)) hexane + 6% (m v(-1)) Triton X-100 (R). Considering the compromised conditions, the pyrolysis an atomization temperatures for the simultaneous determination of Cr, Fe, Ni and V were 1400 degrees C and 2500 degrees C, respectively. Aliquots of 20 mu L of reference solution and sample emulsion were co-injected into the graphite tube with 10 mu L of 1.0 g L(-1) Mg(NO(3))(2) as chemical modifier. The detection limits (n = 10, 3 sigma) and characteristic masses were, respectively: 0.07 mu g g(-1) and 19 pg for Cr; 2.15 mu g g(-1) and 31 pg for Fe; 1.25 mu g g(-1) and 44 pg for Ni; and 1.15 mu g g(-1) and 149 pg for V. The reliability of the proposed method was checked by fuel oil Standard Reference Material (SRMTriton X-100 (R) 1634c - NIST) analysis. The concentrations found presented no statistical differences compared to the certified values at 95% confidence level.

A sampling device to quantify offspring release of sessile marine invertebrates

Quantifying the rate of propagule release is of most importance to estimate reproductive output of natural populations, but simple methods to obtain such data are seldom reported. We designed and tested an inexpensive apparatus capable of reliably measure the release of gametes, eggs or larvae of sessile marine invertebrates in vertical walls. A population of the acom barnacle Chthamalus bisinuatus was sampled with this trap over 68d to obtain a time series of naupliar release. An apparent semilunar trend is shown, indicating the effectiveness of this sampling method.

Sampling study in milk storage tanks by INAA

This study investigated the representativeness of samples for assessing chemical elements in milk bulk tanks. Milk samples were collected from a closed tank in a dairy plant and from an open top tank in a dairy farm. Samples were analyzed for chemical elements by instrumental neutron activation analysis (INAA). For both experiments, Br, Ca, Cs, K, Na, Rb and Zn did not present significant differences between samples thereby indicating the appropriateness of the sampling procedure adopted to evaluate the analytes of interest.

Feasibility of using solid sampling graphite furnace atomic absorption spectrometry for preparation of spiked filter papers with Cu and Zn as standards for direct solid analysis

An approach was developed for the preparation of cryogenic ground spiked filter papers with Cu and Zn for use as synthetic calibrating standards for direct solid microanalysis. Solid sampling graphite furnace atomic absorption spectrometry was used to evaluate the microhomogeneity and to check the applicability of the synthetic calibrating standards for the direct determination of Cu and Zn in vegetable certified reference materials. The found concentrations presented no statistical differences at the 95% confidence level. The homogeneity factors ranged from 2.7 to 4.2 for Cu and from 6.4 to 11.5 for Zn.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.