Discriminant analysis some east Tennessee forest herb niches

Niche differences in four species of Galium were quantified by using discriminant function analysis (DFA) of site characteristics including biotic variables. Data were analyzed separately for a mesic hardwood site and cedar barrens. Significant differences in niche centroids were also determined for 17 co-occurring herbs in the mesic hardwood site using similar variables. Variables used in the analysis included site characteristics such as aspect and percent slope, biotic variables such as total woody basal area and litter composition, and soil characteristics (for the seventeen species) including pH and texture. Biotic variables were included as indicators of environmental variables and possible allelopathic influence.In the Galium data, variables highly correlated with discriminant axes included canopy density, litter type, and overstory type. In the co-occurring species data, litter composition, slope position, soil pH and texture, and steepness of slope were most correlated with discriminant axes. Discriminant axes derived from the Galium cedar barren data set proved a poor predictor of species occurrence in the mesic hardwood site.The utility of DFA in plant niche analysis is discussed.Nomenclature follows: Fernald, M. L., 1950. Gray's manual of botany. American Book Co., Atlanta, Georgia, USA.Research sponsored by the Office of Health and Environmental Research, U.S. Department of Energy, under contract W-7405-eng-26 with Union Carbide Corporation. Publication No. 2031, Environmental Sciences Division, ORNL. We would like to thank Lynn Tharp for assistance with computer problems, and Drs. Mac Post and Bob O'Neill for many useful comments. We are grateful to Tom Kitchings for providing overstory data.     

Comparison of phosphorylation patterns across eukaryotes by discriminative N-gram analysis

Background

How protein phosphorylation relates to kingdom/phylum divergence is largely unknown and the amino acid residues surrounding the phosphorylation site have profound importance on protein kinase–substrate interactions. Standard motif analysis is not adequate for large scale comparative analysis because each phophopeptide is assigned to a unique motif and perform poorly with the unbalanced nature of the input datasets.

Results

First the discriminative n-grams of five species from five different kingdom/phyla were identified. A signature with 5540 discriminative n-grams that could be found in other species from the same kingdoms/phyla was created. Using a test data set, the ability of the signature to classify species in their corresponding kingdom/phylum was confirmed using classification methods. Lastly, ortholog proteins among proteins with n-grams were identified in order to determine to what degree was the identity of the detected n-grams a property of phosphosites rather than a consequence of species-specific or kingdom/phylum-specific protein inventory. The motifs were grouped in clusters of equal physico-chemical nature and their distribution was similar between species in the same kingdom/phylum while clear differences were found among species of different kingdom/phylum. For example, the animal-specific top discriminative n-grams contained many basic amino acids and the plant-specific motifs were mainly acidic. Secondary structure prediction methods show that the discriminative n-grams in the majority of the cases lack from a regular secondary structure as on average they had 88 % of random coil compared to 66 % found in the phosphoproteins they were derived from.

Conclusions

The discriminative n-grams were able to classify organisms in their corresponding kingdom/phylum, they show different patterns among species of different kingdom/phylum and these regions can contribute to evolutionary divergence as they are in disordered regions that can evolve rapidly. The differences found possibly reflect group-specific differences in the kinomes of the different groups of species.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0657-2) contains supplementary material, which is available to authorized users.     

Α comparison of alternative techniques for prediction of the fauna of running-water sites in Great Britain

1. Early versions of the river invertebrate prediction and classification system (RIVPACS) used TWINSPAN to classify reference sites based on the macro-invertebrate fauna, followed by multiple discriminant analysis (MDA) for prediction of the fauna to be expected at new sites from environmental variables. This paper examines some alternative methods for the initial site classification and a different technique for prediction. 2. A data set of 410 sites from RIVPACS II was used for initial screening of seventeen alternative methods of site classification. Multiple discriminant analysis was used to predict classification group from environmental variables. 3. Five of the classification–prediction systems which showed promise were developed further to facilitate prediction of taxa at species and at Biological Monitoring Working Party (BMWP) family level. 4. The predictive capability of these new systems, plus RIVPACS II, was tested on an independent data set of 101 sites from locations throughout Great Britain. 5. Differences between the methods were often marginal but two gave the most consistently reliable outputs: the original TWINSPAN method, and the ordination method semi-strong hybrid multidimensional scaling (SSH) followed by K-means clustering. 6. Logistic regression, an alternative approach to prediction which does not require the prior development of a classification system, was also examined. Although its performance fell within the range offered by the other five systems tested, it conveyed no advantages over them. 7. This study demonstrated that several different multivariate methods were suitable for developing a reliable system for predicting expected probability of occurrence of taxa. This is because the prediction system involves a weighted average smoothing across site groupings. 8. Hence, the two most promising procedures for site classification, coupled to MDA, were both used in the exploratory analyses for RIVPACS III development, which utilized over 600 reference sites.     

基于DNA序列数据挖掘算法研究

引入数据挖掘技术,研究DNA序列数据内在规律性,并给出DNA序列分类问题的算法．综合考虑碱基组的出现概率以及相邻氨基酸之间的关系,从DNA序列片段的个案中密码子分布密度角度出发,提取出已知类别的DNA序列片段的特征;应用分类的逐步判别分析方法,剔除判别能力不显著的变量,给出DNA序列分类的判别函数．仿真结果表明,该算法具有分类计算公式简单且分类结果精度的优点．     

Discriminative features of type I and type III secreted proteins from Gram-negative bacteria

The amino acid composition of sequences and structural attributes (α-helices, β-sheets) of C-and N-terminal fragments (50 amino acids) were compared to annotated (SWISS-PROT/ TrEMBL) type I (20 sequences) and type III (22 sequences) secreted proteins of Gram-negative bacteria. The discriminant analysis together with the stepwise forward and backward selection of variables revealed the frequencies of the residues Arg, Glu, Gly, Ile, Met, Pro, Ser, Tyr, Val as a set of strong (1-P < 0.001) predictor variables to discriminate between the sequences of type I and type III secreted proteins with a cross-validated accuracy of 98.6–100 %. The internal and external validity of discriminant analysis was confirmed by multiple (15 repeats) test-retest procedures using a randomly split original set of proteins; this validation method demonstrated an accuracy of 100 % for 191 non-selected (retest) sequences. The discriminant analysis was also applied using selected variables from the propensities for β-sheets and polarity of C-terminal fragments. This approach produced the next highest and comparable cross-validated classification accuracy for randomly selected and retest proteins (85.4–86.0 % and 82.4–84.5 %, respectively). The proposed sets of predictor variables could be used to assess the compatibility between secretion substrates and secretion pathways of Gram-negative bacteria by means of discriminant analysis.     

Morphometric stepwise discriminant analysis of three genetically identified species within Pseudoterranova decipiens (Krabbe, 1878) (Nematoda: Ascaridida)

Univariate and multivariate statistical analyses have been performed on 19 morphometric variables of adult male specimens belonging to three genetically identified species within Pseudoterranova decipiens (Nematoda: Ascaridida) parasitic in the digestive tract of seals. Two morphometric keys are proposed for the identification of the three species. One key, which uses two variables, determines a frequency of error of 3.8% (3/79). The second key, which uses two canonical discriminant functions based on seven variables previously selected with a stepwise procedure, gives 100% (76/76) accurate classification.     

Ferns and Melastomataceae as indicators of vascular plant composition in rain forests of Colombian Amazonia

In a case-study from Colombian Amazonia, species information from ferns and Melastomataceae was used to explain the compositional patterns of other vascular plant species in 40 widely distributed 0.1-ha plots. Canonical correspondence analysis was applied to regress vascular plant species composition in the forests against information from these two indicator groups (summarized as axes of principal coordinate analyses), together with that from soils, landscape, and the spatial sampling design. In total, 53,941 individuals of 2480 vascular plant species were recorded. Of these, 17,473 individuals and 132 species were from ferns and Melastomataceae. In 19 well-drained upland (tierra firme) plots 19,622 vascular plant individuals and 1716 species were found, with 3793 plants and 91 species from ferns and Melastomataceae. In both the set of all landscapes and the subset of tierra firme forests the principal PCoA axes of the two indicator groups were highly related to the main patterns of forest species composition. In principle, therefore, ferns and Melastomataceae can be used to detect and forecast changes in the forest composition of the study area. However, evidence was not obtained that ferns and Melastomataceae show more potential to predict the main patterns in species composition of forests than soil, landscape, and spatial variables. The partioning of the total variation in forest composition showed that the correlation of ferns and Melastomataceae with other forest plants was quite independent from that of soil, landscape, and space. Direct effects of ferns and Melastomataceae on other plants might be obtained from experimental studies of between-plant interactions, concentrating on the seedling or juvenile stages of trees and lianas, both above-ground as well as in the rooting environment.     

Characterization and Differentiation of Filamentous Fungi Based on Fatty Acid Composition

Cellular fatty acid composition of 100 different filamentous fungi, including oomycetes, zygomycetes, ascomycetes, basidiomycetes, and sterile mycelia, was analyzed to determine if they can be differentiated from one another on this basis and how minor variations in culture temperature and age affect this characteristic. Many fungi were found to possess the same fatty acids but produced different relative concentrations of each. Some fungi differed in both the fatty acids produced and in the relative concentrations of others. Multivariate discriminant analysis demonstrated that all of the species included in this study had significantly different (P < 0.001) fatty acid profiles. Each of the three phyla from which representative species were analyzed and the sterile forms had distinctive fatty acid profiles. Significant differences in fatty acid composition were also found at the intraspecific level. Both culture temperature and age affected fatty acid composition in the fungi examined, but when these factors were held constant, variance in fatty acid composition was not a problem and fungal fatty acid profiles could be differentiated statistically.     

Culturable Bacterial Symbionts Isolated from Two Distinct Sponge Species (Pseudoceratina clavata and Rhabdastrella globostellata) from the Great Barrier Reef Display Similar Phylogenetic Diversity

The diversity of the culturable microbial communities was examined in two sponge species—Pseudoceratina clavata and Rhabdastrella globostellata. Isolates were characterized by 16S rRNA gene sequencing and phylogenetic analysis. The bacterial community structures represented in both sponges were found to be similar at the phylum level by the same four phyla in this study and also at a finer scale at the species level in both Firmicutes and Alphaproteobacteria. The majority of the Alphaproteobacteria isolates were most closely related to isolates from other sponge species including alpha proteobacterium NW001 sp. and alpha proteobacterium MBIC3368. Members of the low %G + C gram-positive (phylum Firmicutes), high %G + C gram-positive (phylum Actinobacteria), and Cytophaga–Flavobacterium–Bacteroides (phylum Bacteroidetes) phyla of domain Bacteria were also represented in both sponges. In terms of culturable organisms, taxonomic diversity of the microbial community in the two sponge species displays similar structure at phylum level. Within phyla, isolates often belonged to the same genus-level monophyletic group. Community structure and taxonomic composition in the two sponge species P. clavata and Rha. globostellata share significant features with those of other sponge species including those from widely separated geographical and climatic regions of the sea.     

Linear Discrimination,Ordination, and the Visualization of Selection Gradients in Modern Morphometrics

Linear discriminant analysis (LDA) is a multivariate classification technique frequently applied to morphometric data in various biomedical disciplines. Canonical variate analysis (CVA), the generalization of LDA for multiple groups, is often used in the exploratory style of an ordination technique (a low-dimensional representation of the data). In the rare case when all groups have the same covariance matrix, maximum likelihood classification can be based on these linear functions. Both LDA and CVA require full-rank covariance matrices, which is usually not the case in modern morphometrics. When the number of variables is close to the number of individuals, groups appear separated in a CVA plot even if they are samples from the same population. Hence, reliable classification and assessment of group separation require many more organisms than variables. A simple alternative to CVA is the projection of the data onto the principal components of the group averages (between-group PCA). In contrast to CVA, these axes are orthogonal and can be computed even when the data are not of full rank, such as for Procrustes shape coordinates arising in samples of any size, and when covariance matrices are heterogeneous. In evolutionary quantitative genetics, the selection gradient is identical to the coefficient vector of a linear discriminant function between the populations before vs. after selection. When the measured variables are Procrustes shape coordinates, discriminant functions and selection gradients are vectors in shape space and can be visualized as shape deformations. Except for applications in quantitative genetics and in classification, however, discriminant functions typically offer no interpretation as biological factors.     

Microbial community analysis of a biogas-producing completely stirred tank reactor fed continuously with fodder beet silage as mono-substrate

The bioconversion of renewable raw material to biogas by anaerobic microbial fermentation processes in completely stirred tank reactors (CSTR) is a valuable alternative resource of energy especially for rural areas. However, knowledge about the microorganisms involved in the degradation of plant biomass is still poor. In this study, a first analysis of the biogas-forming process within a CSTR fed continuously with fodder beet silage as mono-substrate is presented in the context of molecular data on the microbial community composition. As indicated by the conventional process parameters like pH value, content of volatile fatty acids, N:P ratio and the biogas yield, the biogas-forming process within the CSTR occurred with a stable and efficient performance. The average biogas yield based on volatile solids was 0.87m(3)kg(-1) at an organic loading rate of 1.2-2.3kgm(-3)d(-1). This amounts to 94% of the theoretical maximum. In order to identify microorganisms within the CSTR, a 16S rDNA clone library was constructed by PCR amplification applying a prokaryote-specific primer set. One hundred and forty seven clones were obtained and subsequently characterized by amplified rDNA restriction analysis (ARDRA). The sequences of 60 unique ARDRA patterns were estimated in a length of approximately 800-900bp each. Four of them were assigned to the domain Archaea and 56 to the domain Bacteria. Within the domain Archaea, all clones showed a close relationship to methanogenic species. Major bacterial groups represented in the clone library were the class Clostridia of the phylum Firmicutes (22% of all 16S rDNA clones), the class Deltaproteobacteria of the phylum Proteobacteria (24%), the class Bacilli of the phylum Firmicutes (22%) and members of the phylum Bacteroidetes (21%). Within these major groups, the highest biodiversity was found within the class Clostridia (35% of all operational taxonomic units). Members of the phyla Actinobacteria and Spirochaetes were represented only by 5 and 2 clonal sequences, respectively.     

Novel bacterial lineages associated with boreal moss species

Mosses are critical components of boreal ecosystems where they typically account for a large proportion of net primary productivity and harbour diverse bacterial communities that can be the major source of biologically‐fixed nitrogen in these ecosystems. Despite their ecological importance, we have limited understanding of how microbial communities vary across boreal moss species and the extent to which local site conditions may influence the composition of these bacterial communities. We used marker gene sequencing to analyze bacterial communities associated with seven boreal moss species collected near Fairbanks, AK, USA. We found that host identity was more important than site in determining bacterial community composition and that mosses harbour diverse lineages of potential N₂‐fixers as well as an abundance of novel taxa assigned to understudied bacterial phyla (including candidate phylum WPS‐2). We performed shotgun metagenomic sequencing to assemble genomes from the WPS‐2 candidate phylum and found that these moss‐associated bacteria are likely anoxygenic phototrophs capable of carbon fixation via RuBisCo with an ability to utilize byproducts of photorespiration from hosts via a glyoxylate shunt. These results give new insights into the metabolic capabilities of understudied bacterial lineages that associate with mosses and the importance of plant hosts in shaping their microbiomes.     

Sexual dimorphism in human skulls. A comparison of sexual dimorphism in different populations

Application and comparison of sex discriminant functions in different populations led to the conclusion that a certain combination and weighting of a few sex dimorphism variables (in this study we only used craniometric variables) can give a good discrimination between male and female individuals, independent of the racial group to which this function is applied. In our study, the sex-discriminatory power of five discriminant functions which were based on different ordination and selection procedures (e.g. professional knowledge, stepwise discriminant analysis, literature) of the cranial variables is compared. These discriminant functions were applied to three different data sets, the first being skull measurements from an Amsterdam series (Europids), the second skull measurements of a Zulu series (Negrids) and the third skull measurements of a Japan series (Mongolids). Our decision as to whether a function is a good or less good sex-discriminating function is determined by the Dt values (these values give an idea about the discriminatory value of the discriminant function when applied to a new test sample), the number of variables necessary to obtain this Dt and the location of the sectioning point (i.e. comparison between the estimation of the sectioning point and the ”real” sectioning point). These discriminant functions were compared withGiles Elliot's (1962, 1963) “race-independent” sex function.     

五种鳗鲡的含肉率及肌肉营养成分分析

研究利用营养测试方法对日本鳗鲡、欧洲鳗鲡、美洲鳗鲡、花鳗鲡和太平洋双色鳗鲡共5种养殖鳗鲡的含肉率及肌肉营养成分进行了分析比较。结果表明: 5种鳗鲡含肉率61.77%69.22%, 日本鳗鲡和太平洋双色鳗鲡显著高于欧洲鳗鲡和花鳗鲡 (P0.05); 水分含量为62.34%71.80%, 粗蛋白含量为11.31% 18.47%, 脂肪含量为8.62% 24.48%, 灰分含量为0.92%1.06%; 均含有18种氨基酸, 其中包括8种人体必须氨基酸, 总氨基酸含量存在差异, 鲜味氨基酸含量占37.43%38.77%, 必需氨基酸指数(EAAI)为65.2574.77, 其构成比例符合FAO/ WHO的标准, 色氨酸、异亮氨基酸和缬氨酸等氨基酸为限制性氨基酸; 富含磷、钾、铁和锌等多种矿物元素, 日本鳗鲡和花鳗鲡含量最高; 均含有16种脂肪酸, 其中饱和脂肪酸(SFA) 7种, 不饱和脂肪酸(UFA)9种; 脂肪酸中多不饱和脂肪酸(PUFA)和二十二碳六烯酸(DHA)含量较高, 分别占总量的41.92%48.27%和6.63%16.87%。研究结果表明: 5种鳗鲡的肌肉为高蛋白、鲜味氨基酸与必需氨基酸含量高的优质蛋白源; 富含磷、钾、铁、锌等矿物元素, 可作为补充人体矿物质营养的膳食来源; 脂肪酸以不饱和脂肪酸为主, 多不饱和脂肪酸和DHA比值高。因此, 5种鳗鲡具有较高的营养价值且有益人体健康, 均是优良的水产养殖种类。       

AusRivAS: using macroinvertebrates to assess ecological condition of rivers in Western Australia

1. AusRivAS (Australian River Assessment Scheme) models were developed, using macroinvertebrates as indicators, to assess the ecological condition of rivers in Western Australia as part of an Australia-wide program. The models were based on data from 188 minimally disturbed reference sites and are similar to RIVPACS models used in Britain. The major habitats in the rivers (macrophyte, channel) were sampled separately and macroinvertebrates collected were identified to family level. 2. Laboratory sorting of preserved macroinvertebrate samples recovered about 90% of families present when 150 animals were collected, whereas live picking in the field recovered only 76%. 3. Reference sites clustered into five groups on the basis of macroinvertebrate families present. Using seven physical variables, a discriminant function allocated 73% of sites to the correct classification group. A discriminant function based on seven physical and two chemical variables allocated 81% of sites to the correct group. However, when the same reference sites were re-sampled the following year, the nine variable discriminant function misallocated more sites than the seven variable function, owing to annual fluctuations in water chemistry that were not accompanied by changes in fauna. 4. In preliminary testing, the wet season channel model correctly assessed 80% of reference sites as undisturbed in the year subsequent to model building (10% of sites were expected to rate as disturbed because the 10th percentile was used as the threshold for disturbance). Nine sites from an independent data set, all thought to be disturbed, were assessed as such by the model. Results from twenty test sites, chosen because they represented a wide range of ecological condition, were less clear-cut. In its current state the model reliably distinguishes undisturbed and severely disturbed sites. Subtle impacts are either detected inconsistently or do not affect ecological condition.     

Prediction of operator-binding protein by discriminant analysis

A number of operator-binding proteins contain similar sequence features to Cro and cI repressors of bacteriophage and CAP protein of Escherichia coli, such as conserved amino acids at constant positions. However, these sequence patterns also occur in proteins that are not operator-binding. We use sequence analogy information in conjunction with a pattern recognition algorithm. The functional and structural properties, e.g., distributions of hydrophobicity, hydrophilicity, charged amino acids, electrostatic free energy, and helical structures of protein are also considered. Within the framework of discriminant analysis, we calculate the above variables and search for a better combination of variables. To assess the discriminatory power of these variables, we allocated additional sequences and predict DNA-binding regions of regulatory proteins not included in the training set.     

A Novel Technique for Identifying the Instar of Field-Collected Insect Larvae

Many field studies of insects have focused on the adult stage alone, likely because immature stages are unknown in most insect species. Molecular species identification (e.g., DNA barcoding) has helped ascertain the immature stages of many insects, but larval developmental stages (instars) cannot be identified. The identification of the growth stages of collected individuals is indispensable from both ecological and taxonomic perspectives. Using a larval–adult body size relationship across species, I present a novel technique for identifying the instar of field-collected insect larvae that are identified by molecular species identification technique. This method is based on the assumption that classification functions derived from discriminant analyses, performed with larval instar as a response variable and adult and larval body sizes as explanatory variables, can be used to determine the instar of a given larval specimen that was not included in the original data set, even at the species level. This size relationship has been demonstrated in larval instars for many insects (Dyar’s rule), but no attempt has been made to include the adult stage. Analysis of a test data set derived from the beetle family Carabidae (Coleoptera) showed that classification functions obtained from data sets derived from related species had a correct classification rate of 81–100%. Given that no reliable method has been established to identify the instar of field-collected insect larvae, these values may have sufficient accuracy as an analytical method for field-collected samples. The chief advantage of this technique is that the instar can be identified even when only one specimen is available per species if classification functions are determined for groups to which the focal species belongs. Similar classification functions should be created for other insect groups. By using those functions together with molecular species identification, future studies could include larval stages as well as adults.     

Conditional Quadratic Discrimination in the Identification of Biological Markers for Disease Screening

Conditional multivariate normal density functions are used to construct conditional quadratic discriminant functions that adjust for covariate differences between disease groups. An expected actual error rate for the conditional discriminant function is defined. The purpose of this paper is to use the conditional quadratic discriminant function and its misolassification error rate in order to help determine if a set of discriminators is a good biological marker for disease screening. The conditional quadratic discriminant analysis is illustrated using data from two alcoholism classification problems. It is shown how the discriminant functions can identify a set of variables that can be used as biological markers.