Protein probabilities in shotgun proteomics: evaluating different estimation methods using a semi-random sampling model

The calculation of protein probabilities is one of the most intractable problems in large-scale proteomic research. Current available estimating methods, for example, ProteinProphet, PROT_PROBE, Poisson model and two-peptide hits, employ different models trying to resolve this problem. Until now, no efficient method is used for comparative evaluation of the above methods in large-scale datasets. In order to evaluate these various methods, we developed a semi-random sampling model to simulate large-scale proteomic data. In this model, the identified peptides were sampled from the designed proteins and their cross-correlation scores were simulated according to the results from reverse database searching. The simulated result of 18 control proteins was consistent with the experimental one, demonstrating the efficiency of our model. According to the simulated results of human liver sample, ProteinProphet returned slightly higher probabilities and lower specificity than real cases. PROT_PROBE was a more efficient method with higher specificity. Predicted results from a Poisson model roughly coincide with real datasets, and the method of two-peptide hits seems solid but imprecise. However, the probabilities of identified proteins are strongly correlated with several experimental factors including spectra number, database size and protein abundance distribution.     

Blood volume measurement in baboons: simultaneous estimation of red cell volume and plasma volume

A method is described for frequent sequential blood volume estimation in baboons using 32P for red cell volume measurements and 125I-albumin for simultaneous plasma volume measurements. Values for red cell, plasma, and total blood volumes are reported. Close correlations of the volumes to bodyweight were demonstrated. Circulatory half-lives of the isotopes, determined from disappearance curves, confirmed their suitability for serial measurements in these baboons.     

不同蚯蚓采样方法对比研究

蚯蚓种类组成和丰度变化是反映农业管理措施对土壤质量影响的重要指标。为研究利用芥末悬液等方法进行蚯蚓样品采集的有效性和准确性,寻求合理有效的蚯蚓种群特征调查方法,在我国东北玉米连作黑土上分别运用手拣法、福尔马林溶液驱赶法、芥末+水悬液及芥末+乙酸悬液驱赶法,以及驱虫剂与手拣法相结合的方法进行蚯蚓样品采集,将上述7种方法测得的蚯蚓丰度、生物量及年龄组成信息进行了系统分析。结果表明,福尔马林溶液驱赶法不结合手拣法使用时测得的蚯蚓丰度及生物量远远低于其他方法,尤其幼年蚯蚓比例偏低,并不能反映真实的蚯蚓种群特征。使用芥末悬液做驱虫剂有效性明显提高,尤其芥末+乙酸悬液,测得的蚯蚓丰度比手拣法高22.3%。福尔马林溶液结合手拣法后有效性大大提高,测得的蚯蚓丰度和生物量分别是其单独使用时的19.1和9.3倍,但相对其他驱虫剂方法仍高估了成年蚯蚓的比例;芥末+水悬液和芥末+乙酸悬液方法结合手拣法后收集到蚯蚓的数量分别提高了67.8%和89.1%,平均个体重量分别是原来的1.8和1.3倍,说明芥末悬液不会杀死小个体的幼年蚯蚓,但少部分大个体蚯蚓及洞穴不与地表相接的蚯蚓可能并不能被其驱赶至地表,结合手拣法后可以弥补这个缺陷。芥末+乙酸悬液结合手拣法收集到的成年及幼年蚯蚓数量和生物量均显著高于其他方法(P<0.05),既能有效地驱赶小个体和幼年蚯蚓,又可以收集到洞穴不与地表相接的土栖型蚯蚓,因此可以作为真实有效地反映蚯蚓种群特征的采样方法之一。     

Activity patterns in Glossina longipennis : a field study using different sampling methods

Abstract .Studies on the daily activity of Glossina longipennis at Galana Ranch using a black odour-baited electrocuting target confirmed its crepuscular activity profile. Activity started at 05.00–05.30 hours and peaked at 06.00–06.30 hours, stopped by 09.00 hours, then started again at 17.00–17.30 hours with a peak at 18.30–19.00 hours, ceasing by 19.30 hours. Females made up 60% of the overall catch, and tended to arrive later than males. Other stationary sampling methods (trap, stationary ox) gave similar results. With the stationary methods, very few flies were caught outside the periods of peak activity (only 1.5% of the total between 09.00 and 17.00 hours); the ox was the only stationary bait to catch any flies between 10.00 and 16.00 hours. More flies were caught throughout the day at mobile baits (8.3% of the male and 2.3% of the female catch was taken between 09.00 and 17.00 hours). Mobile baits caught considerably more males than females (females were 17% of the catch). These males had on average higher fat and haematin reserves. Similar nutritional differences were not observed for females. There were fewer older females (ovarian category 3 or more) in mobile compared to stationary baits, and a lower proportion of the youngest males (wing fray category 1) at natural compared with artificial baits.     

Retrospective dose estimation in remote period after exposure using different biological methods

Investigation of application of chromosome aberrations of lymphocytes in peripheral blood for biological dosimetry purposes in remote (up to 40 years) period after acute exposure to doses of 1 Gy and more was carried out. The comparative analysis of frequency of unstable and stable (using FISH and G-banding methods) aberrations was performed for 24 subjects accidentally exposed to radiation on nuclear submarines during 1961-1985. Statistically significant increasing of frequency of dicentrics and centric rings was determined in the exposed subjects in remote period after exposure to compare with controls. Their sum frequency in the exposed group varied depending on ARS heaviness from 0.1 to 1.0 aberrations per 100 cells. In control group it was from 0 to 0.2 correspondingly. Translocation frequency (complete + incomplete) fixed by FISH method (2, 4, and 12 chromosomes) varied within the limits of 0.2-16.0 for exposed subjects and 0.3-1.26 translocations per genome per 100 cells for controls. Some examined persons (5 subjects) exposed to accident in 1985 had results of analysis of unstable chromosome aberration in acute period after exposure that allow to estimate obtained doses by dicentrics frequency which having good correlation with ARS heaviness. Individual dosed using traslocation frequency were defined retrospectively in 11 from 21 exposed persons. They correlate with calculated physics doses and doses estimated by haematolotical parameters in acute period and also doses obtained by ESR spectroscopy of tooth enamel in remote period.     

Influence of RNA-Seq library construction,sampling methods,and tissue harvesting time on gene expression estimation

RNA sequencing (RNA-Seq) is popular for measuring gene expression in non-model organisms, including wild populations. While RNA-Seq can detect gene expression variation among wild-caught individuals and yield important insights into biological function, sampling methods can also affect gene expression estimates. We examined the influence of multiple technical variables on estimated gene expression in a non-model fish, the westslope cutthroat trout (Oncorhynchus clarkii lewisi), using two RNA-Seq library types: 3′ RNA-Seq (QuantSeq) and whole mRNA-Seq (NEB). We evaluated effects of dip netting versus electrofishing, and of harvesting tissue immediately versus 5 min after euthanasia on estimated gene expression in blood, gill, and muscle. We found no significant differences in gene expression between sampling methods or tissue collection times with either library type. When library types were compared using the same blood samples, 58% of genes detected by both NEB and QuantSeq showed significantly different expression between library types, and NEB detected 31% more genes than QuantSeq. Although the two library types recovered different numbers of genes and expression levels, results with NEB and QuantSeq were consistent in that neither library type showed differences in gene expression between sampling methods and tissue harvesting times. Our study suggests that researchers can safely rely on different fish sampling strategies in the field. In addition, while QuantSeq is more cost effective, NEB detects more expressed genes. Therefore, when it is crucial to detect as many genes as possible (especially low expressed genes), when alternative splicing is of interest, or when working with an organism lacking good genomic resources, whole mRNA-Seq is more powerful.     

Cell volume measurement as an estimation of mammalian cell biomass

Measurements of volume distributions and dry weight are made on hybridoma cells in culture. The volume of viable hybridoma cells is significantly larger than that of nonviable cells. During exponential growth, the volume of the viable hybridoma cells is found to be significantly larger than that during other stages of batch culture. Proportionality is found between the volume of the cells and their dry weight, indicating that the volume data can be used in conjunction with cell concentration data as a practical technique for indirect measurement of the biomass concentration present in a culture. Comparison of dry weight concentrations in continuous culture to predictions from the volume data shows very good agreement.     

Risk estimation and risk prediction using machine-learning methods

After an association between genetic variants and a phenotype has been established, further study goals comprise the classification of patients according to disease risk or the estimation of disease probability. To accomplish this, different statistical methods are required, and specifically machine-learning approaches may offer advantages over classical techniques. In this paper, we describe methods for the construction and evaluation of classification and probability estimation rules. We review the use of machine-learning approaches in this context and explain some of the machine-learning algorithms in detail. Finally, we illustrate the methodology through application to a genome-wide association analysis on rheumatoid arthritis.     

Effects of sampling teams and estimation methods on the assessment of plant cover

Abstract. We evaluated variability in cover estimation data obtained by (1) two sampling teams who double sampled plots and (2) one team that used two methods (line intercepts and visual estimation of cover classes) to characterize vegetation of herbaceous wetlands. Species richness and cover estimates were similar among teams and among methods, but one sampling team scored cover higher than the other. The line intercept technique yielded higher cover estimates but lower species richness estimates than the cover class method. Cluster analyses of plots revealed that 36% and 11% of plots sampled consecutively by two teams or using two methods, respectively, were similar enough in species composition and abundance to be paired together in the resulting clustering tree. Simplifying cover estimate data to presence/absence increased the similarity among both teams and methods at the plot scale. Teams were very similar in their overall characterization of sites when cover estimation data were used, as assessed by cluster analysis, but methods agreed best on their overall characterization of sites when only presence/absence data were considered. Differences in abundance estimates as well as pseudoturnover contribute to variability. For double sampled plots, pseudoturnover was 19.1%, but 57.7% of pseudo‐turnover cases involved taxa with ≤ 0.5% cover while only 3.4% involved taxa with > 8% cover. We suggest that vegetation scientists incorporate quality control, calibrate observers and publish their results.     

Near-native protein loop sampling using nonparametric density estimation accommodating sparcity

Unlike the core structural elements of a protein like regular secondary structure, template based modeling (TBM) has difficulty with loop regions due to their variability in sequence and structure as well as the sparse sampling from a limited number of homologous templates. We present a novel, knowledge-based method for loop sampling that leverages homologous torsion angle information to estimate a continuous joint backbone dihedral angle density at each loop position. The φ,ψ distributions are estimated via a Dirichlet process mixture of hidden Markov models (DPM-HMM). Models are quickly generated based on samples from these distributions and were enriched using an end-to-end distance filter. The performance of the DPM-HMM method was evaluated against a diverse test set in a leave-one-out approach. Candidates as low as 0.45 Å RMSD and with a worst case of 3.66 Å were produced. For the canonical loops like the immunoglobulin complementarity-determining regions (mean RMSD <2.0 Å), the DPM-HMM method performs as well or better than the best templates, demonstrating that our automated method recaptures these canonical loops without inclusion of any IgG specific terms or manual intervention. In cases with poor or few good templates (mean RMSD >7.0 Å), this sampling method produces a population of loop structures to around 3.66 Å for loops up to 17 residues. In a direct test of sampling to the Loopy algorithm, our method demonstrates the ability to sample nearer native structures for both the canonical CDRH1 and non-canonical CDRH3 loops. Lastly, in the realistic test conditions of the CASP9 experiment, successful application of DPM-HMM for 90 loops from 45 TBM targets shows the general applicability of our sampling method in loop modeling problem. These results demonstrate that our DPM-HMM produces an advantage by consistently sampling near native loop structure. The software used in this analysis is available for download at http://www.stat.tamu.edu/~dahl/software/cortorgles/.     

Cell volume measurement using scanning ion conductance microscopy

We report a novel scanning ion conductance microscopy (SICM) technique for assessing the volume of living cells, which allows quantitative, high-resolution characterization of dynamic changes in cell volume while retaining the cell functionality. The technique can measure a wide range of volumes from 10(-19) to 10(-9) liter. The cell volume, as well as the volume of small cellular structures such as lamelopodia, dendrites, processes, or microvilli, can be measured with the 2.5 x 10(-20) liter resolution. The sample does not require any preliminary preparation before cell volume measurement. Both cell volume and surface characteristics can be simultaneously and continuously assessed during relatively long experiments. The SICM method can also be used for rapid estimation of the changes in cell volume. These are important when monitoring the cell responses to different physiological stimuli.     

不同采样设计评估鱼类群落效果比较

鱼类群落生态学研究结果的准确性很大程度上依赖于采样设计的合理性和准确性,正确的采样调查设计不仅可以降低调查成本,其结果也对渔业资源的评估或者管理起到相当重要的作用.本文利用计算机模拟定点采样、简单随机采样和分层采样,比较了3种采样设计的采样效果、相对误差及相对偏差.结果表明： 定点采样设计的采样效果 (采样效果平均值为3.37)要弱于简单随机采样和分层随机采样 (采样效果平均值为0.961).3种采样设计中,分层采样设计在鱼类群落丰富度评估时表现最好,其采样效果、相对误差和相对偏差表现最佳.随着采样数的增加,分层采样设计的采样效果有所下降,但其采样精度提高.     

Improved procedures for estimation of disease prevalence using ranked set sampling

Ranked set sampling (RSS) is a sampling procedure that can be considerably more efficient than simple random sampling (SRS). When the variable of interest is binary, ranking of the sample observations can be implemented using the estimated probabilities of success obtained from a logistic regression model developed for the binary variable. The main objective of this study is to use substantial data sets to investigate the application of RSS to estimation of a proportion for a population that is different from the one that provides the logistic regression. Our results indicate that precision in estimation of a population proportion is improved through the use of logistic regression to carry out the RSS ranking and, hence, the sample size required to achieve a desired precision is reduced. Further, the choice and the distribution of covariates in the logistic regression model are not overly crucial for the performance of a balanced RSS procedure.