Pairwise statistical significance of local sequence alignment using sequence-specific and position-specific substitution matrices

Pairwise sequence alignment is a central problem in bioinformatics, which forms the basis of various other applications. Two related sequences are expected to have a high alignment score, but relatedness is usually judged by statistical significance rather than by alignment score. Recently, it was shown that pairwise statistical significance gives promising results as an alternative to database statistical significance for getting individual significance estimates of pairwise alignment scores. The improvement was mainly attributed to making the statistical significance estimation process more sequence-specific and database-independent. In this paper, we use sequence-specific and position-specific substitution matrices to derive the estimates of pairwise statistical significance, which is expected to use more sequence-specific information in estimating pairwise statistical significance. Experiments on a benchmark database with sequence-specific substitution matrices at different levels of sequence-specific contribution were conducted, and results confirm that using sequence-specific substitution matrices for estimating pairwise statistical significance is significantly better than using a standard matrix like BLOSUM62, and than database statistical significance estimates reported by popular database search programs like BLAST, PSI-BLAST (without pretrained PSSMs), and SSEARCH on a benchmark database, but with pretrained PSSMs, PSI-BLAST results are significantly better. Further, using position-specific substitution matrices for estimating pairwise statistical significance gives significantly better results even than PSI-BLAST using pretrained PSSMs.     

Development of a finger biomechanical model and its considerations

The development of a biomechanical model for a human finger is faced with many challenges, such as extensor mechanism complexity, statistical indeterminacy and suitability of computational processes. Motivation for this work was to develop a computer model that is able to predict the internal loading patterns of tendons and joint surfaces experienced by the human finger, while mitigating these challenges. Proposed methodology was based on a non-linear optimising mathematical technique with a criterion of boundary conditions and equality equations, maximised against unknown parameters to reduce statistical indeterminacy. Initial validation was performed via the simulation of one dynamic and two static postures case studies. Past models and experiments were used, based on published literature, to verify the proposed model's methodology and results. The feasibility of the proposed methodology was deemed satisfactory as the simulated results were concordant with in-vivo results for the extrinsic flexors.     

Diffprot - software for non-parametric statistical analysis of differential proteomics data

Mass spectrometry-based global proteomics experiments generate large sets of data that can be converted into useful information only with an appropriate statistical approach. We present Diffprot - a software tool for statistical analysis of MS-derived quantitative data. With implemented resampling-based statistical test and local variance estimate, Diffprot allows to draw significant results from small scale experiments and effectively eliminates false positive results. To demonstrate the advantages of this software, we performed two spike-in tests with complex biological matrices, one label-free and one based on iTRAQ quantification; in addition, we performed an iTRAQ experiment on bacterial samples. In the spike-in tests, protein ratios were estimated and were in good agreement with theoretical values; statistical significance was assigned to spiked proteins and single or no false positive results were obtained with Diffprot. We compared the performance of Diffprot with other statistical tests - widely used t-test and non-parametric Wilcoxon test. In contrast to Diffprot, both generated many false positive hits in the spike-in experiment. This proved the superiority of the resampling-based method in terms of specificity, making Diffprot a rational choice for small scale high-throughput experiments, when the need to control the false positive rate is particularly pressing.     

两种统计方法在玉米种质综合评价中的应用

以玉米为研究对象,运用灰关联分析和因子分析对10份玉米种质的12个农艺性状进行综合评价,探讨这两种统计分析方法在玉米种质综合评价上的应用效果。结果表明,综合评价较好的2个品种分别是Suwan1和下层云优78,两种分析方法的结果基本一致,从而提高了综合评价的可靠性和科学性。     

Multi-locus test conditional on confirmed effects leads to increased power in genome-wide association studies

Complex diseases or phenotypes may involve multiple genetic variants and interactions between genetic, environmental and other factors. Current genome-wide association studies (GWAS) mostly used single-locus analysis and had identified genetic effects with multiple confirmations. Such confirmed single-nucleotide polymorphism (SNP) effects were likely to be true genetic effects and ignoring this information in testing new effects of the same phenotype results in decreased statistical power due to increased residual variance that has a component of the omitted effects. In this study, a multi-locus association test (MLT) was proposed for GWAS analysis conditional on SNPs with confirmed effects to improve statistical power. Analytical formulae for statistical power were derived and were verified by simulation for MLT accounting for confirmed SNPs and for single-locus test (SLT) without accounting for confirmed SNPs. Statistical power of the two methods was compared by case studies with simulated and the Framingham Heart Study (FHS) GWAS data. Results showed that the MLT method had increased statistical power over SLT. In the GWAS case study on four cholesterol phenotypes and serum metabolites, the MLT method improved statistical power by 5% to 38% depending on the number and effect sizes of the conditional SNPs. For the analysis of HDL cholesterol (HDL-C) and total cholesterol (TC) of the FHS data, the MLT method conditional on confirmed SNPs from GWAS catalog and NCBI had considerably more significant results than SLT.     

HDACs的统计偶联分析

组蛋白去乙酰化酶HDACs是调控基因的关键蛋白酶。基于生物信息学中的统计偶联分析方法,构建了统计偶联分析平台。基于该平台对HDACs进行了统计偶联分析。预测了HDAC8中关键氨基酸位点以及和H143偶联的氨基酸位点,有利于人们更深入地认识HDACs的结构和功能,为HDACs抑制剂的研究提供新的思路。     

Statistical optimization for immobilized metal affinity purification of secreted human erythropoietin from Drosophila S2 cells

We used a novel approach to affinity purify human erythropoietin (hEPO) following its secretion from Drosophila melanogaster S2 cells. Immobilized metal affinity purification of hEPO was optimized using a two-step serial statistical optimization strategy. After determining the elution conditions (based on preliminary batch-type purification experiments), the first optimization step considered three purification factors; resin, equilibrium, and washing. The results of this analysis showed that the resin amount was the major factor influencing yield and purity in both model equations and the washing factor lowered the confidence limits of the acquired model equations. The washing conditions were then set based on the results of the first step optimization and the second step then optimized three factors; resin, equilibrium, and elution. The yield and purity of hEPO were then compared following purification using three different approaches; batch-type purification based upon the conditions determined by serial statistical optimization, batch-type purification performed in preliminary experiments, and FPLC column chromatography-type purification. We found that the serial statistical optimization approach provided the best combination of yield and purity. These findings indicate that serial statistical optimization strategies can be successfully employed for immobilized metal affinity protein purification using either batch-type or column approaches.     

Effect of moonlight on detection of Whip-poor-wills: implications for long-term monitoring strategies

ABSTRACT.   Understanding variation in the detectability of birds is fundamental to determining the reliability of survey methods. We examined the influence of lunar light conditions on the detection probability of Whip-poor-wills through repeated sampling of 78 point count stations over two lunar cycles. The probability of detection was positively related to moonlight intensity measured as the percentage of moon-face illuminated and moon height above the horizon. These results were used to show how the reliability of long-term monitoring strategies can be improved by sampling design. Surveys conducted on nights when the moon-face was >50% illuminated were less variable and provided more statistical power to long-term monitoring results compared to surveys that were conducted across all nights. Stratifying surveys for Whip-poor-wills during bright moonlight provides greater statistical power for monitoring programs, which inevitably allows better scientific conclusions to be drawn from collected data.     

Studies on the rules of β-strand alignment in a protein β-sheet structure

To further disclose the underlying mechanisms of protein β-sheet formation, studies were made on the rules of β-strands alignment forming β-sheet structure using statistical and machine learning approaches. Firstly, statistical analysis was performed on the sum of β-strands between each β-strand pairs in protein sequences. The results showed a propensity of near-neighbor pairing (or called “first come first pair”) in the β-strand pairs. Secondly, based on the same dataset, the pairwise cross-combinations of real β-strand pairs and four pseudo-β-strand contained pairs were classified by support vector machine (SVM). A novel feature extracting approach was designed for classification using the average amino acid pairing encoding matrix (APEM). Analytical results of the classification indicated that a segment of β-strand had the ability to distinguish β-strands from segments of α-helix and coil. However, the result also showed that a β-strand was not strongly conserved to choose its real partner from all the alternative β-strand partners, which was corresponding with the ordination results of the statistical analysis each other. Thus, the rules of “first come first pair” propensity and the non-conservative ability to choose real partner, were possible important factors affecting the β-strands alignment forming β-sheet structures.     

Statistical methods for efficiency adjusted real-time PCR quantification

The statistical treatment for hypothesis testing using real-time PCR data is a challenge for quantification of gene expression. One has to consider two key factors in precise statistical analysis of real-time PCR data: a well-defined statistical model and the integration of amplification efficiency (AE) into the model. Previous publications in real-time PCR data analysis often fall short in integrating the AE into the model. Novel, user-friendly, and universal AE-integrated statistical methods were developed for real-time PCR data analysis with four goals. First, we addressed the definition of AE, introduced the concept of efficiency-adjusted Delta Delta Ct, and developed a general mathematical method for its calculation. Second, we developed several linear combination approaches for the estimation of efficiency adjusted Delta Delta Ct and statistical significance for hypothesis testing based on different mathematical formulae and experimental designs. Statistical methods were also adopted to estimate the AE and its equivalence among the samples. A weighted Delta Delta Ct method was introduced to analyze the data with multiple internal controls. Third, we implemented the linear models with SAS programs and analyzed a set of data for each model. In order to allow other researchers to use and compare different approaches, SAS programs are included in the Supporting Information. Fourth, the results from analysis of different statistical models were compared and discussed. Our results underline the differences between the efficiency adjusted Delta Delta Ct methods and previously published methods, thereby better identifying and controlling the source of errors introduced by real-time PCR data analysis.     

对应用几种统计模型评价甘蔗品种稳定性的初步比较

利用广东省2009年甘蔗品种区域试验产量数据,对线性回归模型、AMMI模型和LR-PCA模型在评价甘蔗品种稳定性方面的应用进行了初步比较,结果发现,回归法计算简便、直观,AMMI模型和LR-PCA模型的分析结果则更全面、深入,而这两种模型之间仍存在着一定差异.实际操作中,在根据不同的数据资料选择相适宜的分析方法的同时,也可以采用不同的方法进行分析,通过比较选择较为合理的结果.     

不同统计方法对豆科牧草种质资源适应性评价的比较

以澳大利亚引进的豆科牧草为研究对象,运用灰关联分析、隶属函数分析、聚类分析和主成分分析法,对15份豆科牧草种质的8个主要农艺性状进行综合评价,探讨不同的分析方法在牧草种质资源评价中的应用。结果表明,4种方法综合评价较好的品种(系)为Nina柱花草、Temprano柱花草、Stylo540、Stylo541;4种综合评价方法结果基本一致,说明这4种综合评价方法均可单独应用于牧草种质资源评价,其中隶属函数分析方法简单,在大量的种质资源适应性评价中可优先使用。     

Statistical Use in Clinical Studies: Is There Evidence of a Methodological Shift?

Background

Several studies indicate that the statistical education model and level in medical training fails to meet the demands of clinicians, especially when they want to understand published clinical research. We investigated how study designs and statistical methods in clinical studies have changed in the last twenty years, and we identified the current trends in study designs and statistical methods in clinical studies.

Methods

We reviewed 838 eligible clinical study articles that were published in 1990, 2000, and 2010 in four journals New England Journal of Medicine, Lancet, Journal of the American Medical Association and Nature Medicine. The study types, study designs, sample designs, data quality controls, statistical methods and statistical software were examined.

Results

Substantial changes occurred in the past twenty years. The majority of the studies focused on drug trials (61.6%, n = 516). In 1990, 2000, and 2010, there was an incremental increase in RCT studies (74.4%, 82.8%, and 84.0%, respectively, p = 0.013). Over time, there was increased attention on the details of selecting a sample and controlling bias, and there was a higher frequency of utilizing complex statistical methods. In 2010, the most common statistical methods were confidence interval for superiority and non-inferiority comparison (41.6%), survival analysis (28.5%), correction analysis for covariates (18.8%) and Logistic regression (15.3%).

Conclusions

These findings indicate that statistical measures in clinical studies are continuously developing and that the credibility of clinical study results is increasing. These findings provide information for future changes in statistical training in medical education.     

Spatial pattern analysis in ecology based on Ripley's K-function: Introduction and methods of edge correction

Abstract. Spatial pattern analysis based on Ripley's K-function is a second-order analysis of point patterns in a twodimensional space. The method is increasingly used in studies of spatial distribution patterns of plant communities, but the statistical methods involved are sometimes poorly understood or have been modified without evaluating the effects on results. The procedures of field data acquisition, statistical analysis, and the test for the null hypothesis of complete spatial randomness are described and the presentation of results is discussed. Different methods of edge correction were tested on a computer-generated random pattern and a mapped distribution of a Mediterranean shrubland. The inclusion of buffer zones around mapped plots describes the spatial pattern most accurately, but may not warrant the additional labour involved. Three variations of the weighted edge correction yielded comparable results for the distribution patterns tested. The toroidal edge correction may give biased results for non-random patterns. Recommendations for standardisation of the statistical procedures and data presentation are given.     

An evaluation of Salmonella (Ames) test data in the published literature: application of statistical procedures and analysis of mutagenic potency

We searched the published literature for Salmonella test data on some 450 chemicals. Only 137 of more than 400 articles containing original data satisfied minimum criteria for a quantitative analysis [1751 experiments, comprising data on 152 chemicals (Table 1)]. Many of these papers did not report basic information about the test protocol (Table 2). We used previously described statistical procedures (Bernstein et al., 1982) to estimate the initial slopes of the dose-response curves and corresponding standard errors. We also applied tests for significance and linear goodness-of-fit. We then used the results of these analyses to examine several issues: (1) Linearity of the low dose region of the dose-response curve. We found that the overwhelming majority of curves were linear, though ability to detect non-linearity of dose-response curves in the standard plate test is only limited. 7% of all experiments to which the goodness-of-fit test was applied were curves of increasing slope, and with a few possible exceptions, these were not obviously associated with any particular mutagens, even those generally considered to produce non-linear effects such as MNNG and EMS (Table 3). (2) Performance of the statistical test for significance. Results of the statistical test for significance of the dose-response were compared with author's opinions as to positivity. In almost all cases (94%) results of the statistical test and authors opinions were the same. In the examples of conflicting opinions, the reasons were: (a) the statistical test places more weight than do most authors on the presence of a linear dose-response; (b) most authors tend to require at least a 2-fold increase over the spontaneous background for 'significance', and (c) when the number of spontaneous revertants is small (e.g., TA1537), authors tend to require a larger increase in induced revertants than when the spontaneous background is large, whereas the statistical procedure makes no such distinction. These factors result in the statistical test tending to identify more experiments as positive than do authors, provided there is a linear dose-response, and authors tending to judge more experiments as positive when the dose-response is not linear. (3) Reproducibility. Among the 1751 experiments there were 122 data-sets (a total of 333 experiments) in which the same chemical was tested by two or more different laboratories under the same protocol. 21 of the 122 data-sets had some disagreement between experiments as to whether results were positive or negative (Table 4).(ABSTRACT TRUNCATED AT 400 WORDS)     

乌司他丁在急性呼吸窘迫综合征的临床应用研究

目的:观察乌司他丁(UTI)对急性呼吸窘迫综合征(acute respiratory distress syndrome,ARDS)的临床应用。方法:选择我院ICU自2008年1月至2011年1月收治的160例ARDS患者作为研究对象,采用随机对照的方法,并且经患者或患者家属知情并签字同意分组。分为UTI组(A组)和对照组(B组)。两组均给予相同综合治疗措施,A组除综合治疗外还给予注射用乌司他丁,每次30万U,每日2次。分别记录两组患者开始治疗、治疗后第3天、治疗第7天的生命体征,动脉血气分析、血生化检查结果、并且记录患者在ICU治疗的转归,应用SPSS13.0软件对结果进行统计学分析。结果:经治疗3天A组呼吸频率低于B组,动脉血气分析提示两组PO2、PO2/FiO2、SaO2均有上升。比较后发现A组PO2、PO2/FiO2、SaO2高于B组(P<0.05),两组PO2、SaO2比较有统计学差异。经治疗3天A组与B组生化指标比较、白细胞计数、肾功及血乳酸均有下降,有统计学差异,P<0.05。全部治疗结束后A组与B组死亡率比较(UTI组34.29%,对照组38.26%,P=0.0097)及机械通气时间比较(UTI组7.54±3.27天,对照组11.78±2.69天,P=0.0086),均有统计学差异。结论:大剂量UTI用于ARDS的临床治疗可有效改善患者氧合指数,减少机械通气时间,降低患者的病死率。     

The Importance of Integrating Clinical Relevance and Statistical Significance in the Assessment of Quality of Care –Illustrated Using the Swedish Stroke Register

BackgroundWhen profiling hospital performance, quality inicators are commonly evaluated through hospital-specific adjusted means with confidence intervals. When identifying deviations from a norm, large hospitals can have statistically significant results even for clinically irrelevant deviations while important deviations in small hospitals can remain undiscovered. We have used data from the Swedish Stroke Register (Riksstroke) to illustrate the properties of a benchmarking method that integrates considerations of both clinical relevance and level of statistical significance.MethodsThe performance measure used was case-mix adjusted risk of death or dependency in activities of daily living within 3 months after stroke. A hospital was labeled as having outlying performance if its case-mix adjusted risk exceeded a benchmark value with a specified statistical confidence level. The benchmark was expressed relative to the population risk and should reflect the clinically relevant deviation that is to be detected. A simulation study based on Riksstroke patient data from 2008–2009 was performed to investigate the effect of the choice of the statistical confidence level and benchmark value on the diagnostic properties of the method.ResultsSimulations were based on 18,309 patients in 76 hospitals. The widely used setting, comparing 95% confidence intervals to the national average, resulted in low sensitivity (0.252) and high specificity (0.991). There were large variations in sensitivity and specificity for different requirements of statistical confidence. Lowering statistical confidence improved sensitivity with a relatively smaller loss of specificity. Variations due to different benchmark values were smaller, especially for sensitivity. This allows the choice of a clinically relevant benchmark to be driven by clinical factors without major concerns about sufficiently reliable evidence.ConclusionsThe study emphasizes the importance of combining clinical relevance and level of statistical confidence when profiling hospital performance. To guide the decision process a web-based tool that gives ROC-curves for different scenarios is provided.     

互联网教育对超声住培教学的影响及思考

目的 分析互联网教育对超声专业住培医师教学的影响.方法 将我科接受超声专业住院医师规范化培训的50名住培医师为研究对象,其中以2019年1～4月的住培医师为对照组,以2020年1～4月的住培医师为实验组.对照组以传统教学方式教学,实验组以互联网教学为主要教学方式,两组住培医师通过考试成绩(笔试及技能)及问卷调查方法评估...