景观指数之间的相关分析

应用辽宁省1997~1998年的TM 5影像数据,编制了景观类型图,以78个县市区为单位,分割成78个景观,共计算39个景观格局指数,对它们进行了相关分析。总面积是最基本的景观指数,它决定景观总边界长度、斑块数、类型密度等基本指数,同时与多个指数有显著的相关关系(相关系数绝对值大于0.75)。形状指数的独立性强,极少数指数与其它指数有显著的相关关系;多样性指数和蔓延度指数之间信息重复量最多,都表示景观的异质性,但多样性指数以面积百分比表示景观异质性,而蔓延度指数以类型之间相邻边界的百分比表示景观异质性。研究发现,如果两个指数之间存在显著的相关关系,而由它们两个构成的指数与它们之间没有显著的相关关系。如果指数平均值之间存在显著的相关关系,则它们的变异系数之间不存在显著的相关关系。景观指数间的相关系数不仅与景观格局本身有关,还与空间尺度,分类系统、计算公式及其参数、计算单元和生态学意义关系密切。指数之间影响因子的相同之处越多,它们之间存在显著相关关系的概率越大。     

Correlations in one-dimensional fully developed chaos

Correlations in the baker map and the tent map as examples of one-dimensional, fully developed chaos are considered. It is shown, utilizing symbolic dynamical systems derived from these maps, that the vanishing second-order correlation function is not sufficient to guarantee uncorrelatedness. Importance of the higher-order, especially third-order, correlation functions is emphasized for chaotic systems. In search of the quantities that grasp correlational behaviors as a whole in chaotic systems, it is proposed to use the fixed-separation correlation integral, which is a modified quantity of the usual correlation integral devised to calculate the fractal dimension of strange attractors, for these maps. It is shown that the new quantity contains all the even-number orders of autocorrelation function that are commonly considered.     

General Derivation of Intraclass Correlation Coefficients

A general intraclass correlation coefficient is derived similarly to the general correlation coefficient given by KENDALL (1962). This coefficient II embraces as specific cases three intraclass correlations, related to Pearson's r, Kendall's tau and Spearman's rs, that were dealt with by FISHER (1921), WHITFIELD (1949), SHIRAHATA (1981) and SCHEMPER (1984). Formal relationships are presented and the qualification of the three coefficients for specific applications is discussed.     

A note on the measurement of redundancy

Plant Ecology - The present paper points out a simpler method for computing the redundancy coefficient proposed by Orlóci (1975) using the inverse of the variance-covariance matrix. It is...     

Cell and tissue deformation measurements: Texture correlation with third-order approximation of displacement gradients

Cells remarkably are capable of large deformations during motility and when subjected to mechanical force. Measurement of mechanical deformation (i.e. displacements, strain) is critical to understand functional changes in cells and biological tissues following disease, and to elucidate basic relationships between applied force and cellular biosynthesis. Microscopy-based imaging modalities provide the ability to noninvasively visualize small cell or tissue structures and track their motion over time, often using two-dimensional (2D) digital image (texture) correlation algorithms. For the measurement of complex and nonlinear motion in cells and tissues, implementation of texture correlation algorithms with high order approximations of displacement mapping terms are needed to minimize error. Here, we extend a texture correlation algorithm with up to third-order approximation of displacement mapping terms for the measurement of cell and tissue deformation. We additionally investigate relationships between measurement error and image texture, defined by subset entropy. Displacement measurement error is significantly reduced when the order of displacement mapping terms in the texture correlation algorithm matches or exceeds the order of the deformation observed. Displacement measurement error is also inversely proportional to subset entropy, with well-defined cell and tissue structures leading to high entropy and low error. For cell and tissue studies where complex or nonlinear displacements are expected, texture correlation algorithms with high order terms are required to best characterize the observed deformation.     

小麦籽粒品质性状的杂种优势和相关分析

以6个小麦品种（系）组配的6个杂交组合F1为供试材料,对其籽粒品质性状进行了杂种优化、性状相关和亲子相关分析。结果表明：（1）粉质参数中的形成时间和稳定时间杂种优势最强,分别为56.49％和32.23％;籽粒蛋白质含量和硬度的优势最弱,分别为-2.73％和-0.9046％;沉淀值和湿面筋含量的优势居中,分别为6.88％和5.88％。（2）粉质参数中的吸水率、稳定时间同其它几个指标之间呈显著或极显著相关;沉淀值与籽粒蛋白质含量呈正相关,但不显著,与湿面筋含量呈显著负相关;湿面筋含量与籽粒蛋白质含量呈显著负相关。（3）杂种F1的籽粒Zeleny沉淀值与高亲值,低亲值和中亲值呈显著和极显著正相关;籽粒蛋白质含量和湿面筋含量与高亲值,低亲值和中亲值呈负相关或不相关。     

一种基于数学期望的亲子与同胞相关系数的估计方法

本文在对亲本平方和、子代同胞间平方和、同胞内平方和与亲子间乘积和求数学期望的基础上,估计亲子与同胞相关系数,导出了两套不同的亲子与同胞相关系数的估计公式,其中之一与Srivastava（1984）提出的完全一致,但估计方法较之具有直接性,推导过程得到了简化．     

A general class of correlation coefficients for the 2 x 2 crossover design

The Pearson correlation coefficient and the Kendall correlation coefficient are two popular statistics for assessing the correlation between two variables in a bivariate sample. We indicate how both of these statistics are special cases of a general class of correlation statistics that is parameterized by gamma element of [0, 1]. The Pearson correlation coefficient is characterized by gamma = 1 and the Kendall correlation coefficient by gamma = 0, so they yield the upper and lower extremes of the class, respectively. The correlation coefficient characterized by gamma = 0.5 is of special interest because it only requires that first-order moments exist for the underlying bivariate distribution, whereas the Pearson correlation coefficient requires that second-order moments exist. We derive the asymptotic theory for the general class of sample correlation coefficients and then describe the use of this class of correlation statistics within the 2 x 2 crossover design. We illustrate the methodology using data from the CLIC trial of the Childhood Asthma Research and Education (CARE) Network.     

不结球白菜杂种优势及相关分析

以4个不结球白菜不育系与4个父本系以NCⅡ法配制16个杂交组合,研究了16个F1组合的杂种优势表现及其与亲本之间的相关关系,同时对性状间的遗传相关进行分析.结果表明:不结球白菜产量性状杂种优势＞农艺性状杂种优势＞光合性状杂种优势＞品质性状杂种优势.产量性状以超亲优势为主,农艺性状和光合性状以中亲优势为主,品质性状中可溶性糖含量以中亲优势为主, Vc含量和蛋白质含量均为弱的负向优势.亲子相关分析表明,一些性状F1与中亲值、低亲值或高亲值显著相关,因此在亲本选配时,注意亲本差异的同时,中亲值特别是低亲值不能过低,尤其是品质性状.性状间相关分析显示,光合性状与产量性状显著正相关,说明F1高效的光合同化作用是杂种高产的基础.品质性状中,可溶性糖含量与产量显著正相关,但Vc和蛋白质含量与产量负相关,在亲本选配时还应注意二者的协调.     

The role played by exons in genomic DNA sequence correlations

The codon structure inside exons imposes a strong modulation with period-3 for genomic composition correlations. A new formalism for calculating nucleotide correlations along DNA sequences in terms of an irreducible set of six correlation functions is presented. New procedures to extract the corresponding period-3 modulations are also developed. These modulations are seen to be stronger for the irreducible self-correlation C_zz(k), which accounts only for the binding strength of dinucleotides (z stands for adenine or thymine minus cytosine or guanine concentrations). We investigate and model the relationship between exon distribution and genomic period-3 correlations for the D. melanogaster genome.     

Measuring the flow of molecules in cells

No methods proposed thus far have the capability to measure molecular flow in live cells at the single molecule level. Here, we review the potentiality of a newly established method based on the spatial correlation of fluorescence fluctuations at a pair of points in the sample (pair correlation method). The pair correlation function (pCF) offers a unique tool to probe the directionality of intracellular traffic, by measuring the accessibility of the cellular landscape and its role in determining the diffusive routes adopted by molecules. The sensitivity of the pCF method toward detection of barriers means that different structural elements of the cell can be tested in terms of penetrability and mechanisms of regulation imparted on molecular flow. This has been recently demonstrated in a series of studies looking at molecular transport inside live cells. Here, we will review the theory behind detection of barriers to molecular flow, the rules to interpret pCF data, and relevant applications to intracellular transport.     

Sequential1H and13C resonance assignments for an octa- and decasaccharide of theN-acetyllactosamine type by multiple-step relayed correlation and heteronuclear correlation nuclear magnetic resonance

400 MHz¹H-NMR and 100 MHz¹³C-NMR spectra of a neutral octasaccharide and of a disialyldecasaccharide of theN-acetyllactosamine type were studied. The resonance assignments were made by combining multiple-relayed coherence-transfer chemical-shift-correlated spectroscopy (multiple-RELAY-COSY) and¹H/¹³C-shift correlated 2D experiments. The complete analysis of the¹H and¹³C spectra was performed.     

Study of statistical correlations in DNA sequences

Here we present a study of statistical correlations among different positions in DNA sequences and their implications by directly using the autocorrelation function. Such an analysis is possible now because of the availability of large sequences or even complete genomes of many organisms. After describing the way in which the autocorrelation function can be applied to DNA-sequence analysis, we show that long-range correlations, implying scale independence, appear in several bacterial genomes as well as in long human chromosome contigs. The source for such correlations in bacteria, which may extend up to 60 kb in Bacillus subtilis, may be related to massive lateral transfer of compositionally biased genes from other genomes. In the human genome, correlations extend for more than five decades and may be related to the evolution of the ’neogenome’, a modern evolutionary acquisition composed by GC-rich isochores displaying long-range correlations and scale invariance.     

Do Molecular Markers Inform About Pleiotropy?

The availability of dense panels of common single-nucleotide polymorphisms and sequence variants has facilitated the study of statistical features of the genetic architecture of complex traits and diseases via whole-genome regressions (WGRs). At the onset, traits were analyzed trait by trait, but recently, WGRs have been extended for analysis of several traits jointly. The expectation is that such an approach would offer insight into mechanisms that cause trait associations, such as pleiotropy. We demonstrate that correlation parameters inferred using markers can give a distorted picture of the genetic correlation between traits. In the absence of knowledge of linkage disequilibrium relationships between quantitative or disease trait loci and markers, speculating about genetic correlation and its causes (e.g., pleiotropy) using genomic data is conjectural.     

Estimating a multivariate familial correlation using joint models for canonical correlations: application to memory score analysis from familial Hispanic Alzheimer's disease study

Summary .  Analysis of multiple traits can provide additional information beyond analysis of a single trait, allowing better understanding of the underlying genetic mechanism of a common disease. To accommodate multiple traits in familial correlation analysis adjusting for confounders, we develop a regression model for canonical correlation parameters and propose joint modeling along with mean and scale parameters. The proposed method is more powerful than the regression method modeling pairwise correlations because it captures familial aggregation manifested in multiple traits through maximum canonical correlation.     

Time domain measures of inter-channel EEG correlations: a comparison of linear, nonparametric and nonlinear measures

Correlations between ten-channel EEGs obtained from thirteen healthy adult participants were investigated. Signals were obtained in two behavioral states: eyes open no task and eyes closed no task. Four time domain measures were compared: Pearson product moment correlation, Spearman rank order correlation, Kendall rank order correlation and mutual information. The psychophysiological utility of each measure was assessed by determining its ability to discriminate between conditions. The sensitivity to epoch length was assessed by repeating calculations with 1, 2, 3, …, 8 s epochs. The robustness to noise was assessed by performing calculations with noise corrupted versions of the original signals (SNRs of 0, 5 and 10 dB). Three results were obtained in these calculations. First, mutual information effectively discriminated between states with less data. Pearson, Spearman and Kendall failed to discriminate between states with a 1 s epoch, while a statistically significant separation was obtained with mutual information. Second, at all epoch durations tested, the measure of between-state discrimination was greater for mutual information. Third, discrimination based on mutual information was more robust to noise. The limitations of this study are discussed. Further comparisons should be made with frequency domain measures, with measures constructed with embedded data and with the maximal information coefficient.     

Components of juvenile-mature correlations in forest trees

Summary Juvenile-mature correlation has played an important role in indirect selection for size traits in forest trees. The juvenile size of a tree is a part of the mature size, and the juvenile-mature correlation is an example of a part-whole type of correlation. As is the case with any other part-whole type of correlation, the juvenile-mature correlation can be subdivided into two components; one is a function of variance only, and the other a function of variance and covariance. In this paper the components of the juvenile-mature correlation is described, the basic properties and the dynamics of its components analyzed, and the role of these components in explaining the gain from indirect juvenile selection discussed. Six forest tree populations were used to review the various properties of the model. The most important applied conclusions were: (1) even if two populations have the same juvenile-mature correlations, different selection strategies can be used depending on the nature of correlation components. (2) Choosing the proper mature age is as important as choosing juvenile age. (3) Understanding the growth curves of mean and variance is essential to developing selection strategies Annotation: Describes a new way of interpreting juvenile-mature correlation in forest tree species.     

Fluorescence Correlation Spectroscopy Measures Molecular Transport in Cells

Fluorescence correlation spectroscopy (FCS) can measure dynamics of fluorescent molecules in cells. FCS measures the fluctuations in the number of fluorescent molecules in a small volume illuminated by a thin beam of excitation light. These fluctuations are processed statistically to yield an autocorrelation function from which rates of diffusion, convection, chemical reaction, and other processes can be extracted. The advantages of this approach include the ability to measure the mobility of a very small number of molecules, even down to the single molecule level, over a wide range of rates in very small regions of a cell. In addition to rates of diffusion and convection, FCS also provides unique information about the local concentration, states of aggregation and molecular interaction using fluctuation amplitude and cross-correlation methods. Recent advances in technology have rendered these once difficult measurements accessible to routine use in cell biology and biochemistry. This review provides a summary of the FCS method and describes current areas in which the FCS approach is being extended beyond its original scope.     

Covariate Adjusted Correlation Analysis with Application to FMR1 Premutation Female Carrier Data

Summary .  Motivated by molecular data on female premutation carriers of the fragile X mental retardation 1 ( FMR1 ) gene, we present a new method of covariate adjusted correlation analysis to examine the association of messenger RNA (mRNA) and number of CGG repeat expansion in the  FMR1  gene. The association between the molecular variables in female carriers needs to adjust for activation ratio (ActRatio), a measure which accounts for the protective effects of one normal X chromosome in females carriers. However, there are inherent uncertainties in the exact effects of ActRatio on the molecular measures of interest. To account for these uncertainties, we develop a flexible adjustment that accommodates both additive and multiplicative effects of ActRatio nonparametrically. The proposed adjusted correlation uses local conditional correlations, which are local method of moments estimators, to estimate the Pearson correlation between two variables adjusted for a third observable covariate. The local method of moments estimators are averaged to arrive at the final covariate adjusted correlation estimator, which is shown to be consistent. We also develop a test to check the nonparametric joint additive and multiplicative adjustment form. Simulation studies illustrate the efficacy of the proposed method. (Application to  FMR1  premutation data on 165 female carriers indicates that the association between mRNA and CGG repeat after adjusting for ActRatio is stronger.) Finally, the results provide independent support for a specific jointly additive and multiplicative adjustment form for ActRatio previously proposed in the literature.