dcGOR: An R Package for Analysing Ontologies and Protein Domain Annotations

I introduce an open-source R package ‘dcGOR’ to provide the bioinformatics community with the ease to analyse ontologies and protein domain annotations, particularly those in the dcGO database. The dcGO is a comprehensive resource for protein domain annotations using a panel of ontologies including Gene Ontology. Although increasing in popularity, this database needs statistical and graphical support to meet its full potential. Moreover, there are no bioinformatics tools specifically designed for domain ontology analysis. As an add-on package built in the R software environment, dcGOR offers a basic infrastructure with great flexibility and functionality. It implements new data structure to represent domains, ontologies, annotations, and all analytical outputs as well. For each ontology, it provides various mining facilities, including: (i) domain-based enrichment analysis and visualisation; (ii) construction of a domain (semantic similarity) network according to ontology annotations; and (iii) significance analysis for estimating a contact (statistical significance) network. To reduce runtime, most analyses support high-performance parallel computing. Taking as inputs a list of protein domains of interest, the package is able to easily carry out in-depth analyses in terms of functional, phenotypic and diseased relevance, and network-level understanding. More importantly, dcGOR is designed to allow users to import and analyse their own ontologies and annotations on domains (taken from SCOP, Pfam and InterPro) and RNAs (from Rfam) as well. The package is freely available at CRAN for easy installation, and also at GitHub for version control. The dedicated website with reproducible demos can be found at http://supfam.org/dcGOR.

This is a PLOS Computational Biology Software Article

     

parallelMCMCcombine: An R Package for Bayesian Methods for Big Data and Analytics

Recent advances in big data and analytics research have provided a wealth of large data sets that are too big to be analyzed in their entirety, due to restrictions on computer memory or storage size. New Bayesian methods have been developed for data sets that are large only due to large sample sizes. These methods partition big data sets into subsets and perform independent Bayesian Markov chain Monte Carlo analyses on the subsets. The methods then combine the independent subset posterior samples to estimate a posterior density given the full data set. These approaches were shown to be effective for Bayesian models including logistic regression models, Gaussian mixture models and hierarchical models. Here, we introduce the R package parallelMCMCcombine which carries out four of these techniques for combining independent subset posterior samples. We illustrate each of the methods using a Bayesian logistic regression model for simulation data and a Bayesian Gamma model for real data; we also demonstrate features and capabilities of the R package. The package assumes the user has carried out the Bayesian analysis and has produced the independent subposterior samples outside of the package. The methods are primarily suited to models with unknown parameters of fixed dimension that exist in continuous parameter spaces. We envision this tool will allow researchers to explore the various methods for their specific applications and will assist future progress in this rapidly developing field.     

phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

Background

The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data.

Results

Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research.

Conclusions

The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.     

A Bayesian Modelling Approach with Balancing Informative Prior for Analysing Imbalanced Data

When a dataset is imbalanced, the prediction of the scarcely-sampled subpopulation can be over-influenced by the population contributing to the majority of the data. The aim of this study was to develop a Bayesian modelling approach with balancing informative prior so that the influence of imbalance to the overall prediction could be minimised. The new approach was developed in order to weigh the data in favour of the smaller subset(s). The method was assessed in terms of bias and precision in predicting model parameter estimates of simulated datasets. Moreover, the method was evaluated in predicting optimal dose levels of tobramycin for various age groups in a motivating example. The bias estimates using the balancing informative prior approach were smaller than those generated using the conventional approach which was without the consideration for the imbalance in the datasets. The precision estimates were also superior. The method was further evaluated in a motivating example of optimal dosage prediction of tobramycin. The resulting predictions also agreed well with what had been reported in the literature. The proposed Bayesian balancing informative prior approach has shown a real potential to adequately weigh the data in favour of smaller subset(s) of data to generate robust prediction models.     

COPASutils: An R Package for Reading,Processing, and Visualizing Data from COPAS Large-Particle Flow Cytometers

The R package COPASutils provides a logical workflow for the reading, processing, and visualization of data obtained from the Union Biometrica Complex Object Parametric Analyzer and Sorter (COPAS) or the BioSorter large-particle flow cytometers. Data obtained from these powerful experimental platforms can be unwieldy, leading to difficulties in the ability to process and visualize the data using existing tools. Researchers studying small organisms, such as Caenorhabditis elegans, Anopheles gambiae, and Danio rerio, and using these devices will benefit from this streamlined and extensible R package. COPASutils offers a powerful suite of functions for the rapid processing and analysis of large high-throughput screening data sets.     

Gendist: An R Package for Generated Probability Distribution Models

In this paper, we introduce the R package gendist that computes the probability density function, the cumulative distribution function, the quantile function and generates random values for several generated probability distribution models including the mixture model, the composite model, the folded model, the skewed symmetric model and the arc tan model. These models are extensively used in the literature and the R functions provided here are flexible enough to accommodate various univariate distributions found in other R packages. We also show its applications in graphing, estimation, simulation and risk measurements.     

CAPE: An R Package for Combined Analysis of Pleiotropy and Epistasis

Contemporary genetic studies are revealing the genetic complexity of many traits in humans and model organisms. Two hallmarks of this complexity are epistasis, meaning gene-gene interaction, and pleiotropy, in which one gene affects multiple phenotypes. Understanding the genetic architecture of complex traits requires addressing these phenomena, but interpreting the biological significance of epistasis and pleiotropy is often difficult. While epistasis reveals dependencies between genetic variants, it is often unclear how the activity of one variant is specifically modifying the other. Epistasis found in one phenotypic context may disappear in another context, rendering the genetic interaction ambiguous. Pleiotropy can suggest either redundant phenotype measures or gene variants that affect multiple biological processes. Here we present an R package, R/cape, which addresses these interpretation ambiguities by implementing a novel method to generate predictive and interpretable genetic networks that influence quantitative phenotypes. R/cape integrates information from multiple related phenotypes to constrain models of epistasis, thereby enhancing the detection of interactions that simultaneously describe all phenotypes. The networks inferred by R/cape are readily interpretable in terms of directed influences that indicate suppressive and enhancing effects of individual genetic variants on other variants, which in turn account for the variance in quantitative traits. We demonstrate the utility of R/cape by analyzing a mouse backcross, thereby discovering novel epistatic interactions influencing phenotypes related to obesity and diabetes. R/cape is an easy-to-use, platform-independent R package and can be applied to data from both genetic screens and a variety of segregating populations including backcrosses, intercrosses, and natural populations. The package is freely available under the GPL-3 license at http://cran.r-project.org/web/packages/cape.

This is a PLOS Computational Biology Software Article

     

Leaf Temperatures in a Gas Exchange Chamber and in the Open Air

Leaf temperatures in a Koch fully climatized gas-exchange chamberas designed by Siemens and in a similarly equipped open-airreference were measured with horizontally and vertically insertedthermocouples on Nerium oleander L. On a sunny day with onlylittle air movement and an average air temperature of 20.4 °C,leaf over-temperatures in the gas-exchange chamber were loweron average by 2.2 K. The extent of reduction of over-temperaturein the chamber is determined by the reduced global radiationin the chamber and the differences of wind velocities in chamberand reference. Differences in the ventilation intensity in thechamber have no demonstrable influence on the leaf over-temperatures.The over-temperatures of the reference leaves, on the otherhand, depend to a large degree on air velocity. The changedradiation and air flow conditions in the chamber as comparedwith open-air conditions have consequences for the physiologicalreactions of the enclosed plant and must be taken into accountwhen comparing results from gas-exchange measurements with open-airconditions. For further improvements of gas-exchange measurementequipment, air flow conditions and radiation quantity and qualitymight be starting points     

SWATH2stats: An R/Bioconductor Package to Process and Convert Quantitative SWATH-MS Proteomics Data for Downstream Analysis Tools

SWATH-MS is an acquisition and analysis technique of targeted proteomics that enables measuring several thousand proteins with high reproducibility and accuracy across many samples. OpenSWATH is popular open-source software for peptide identification and quantification from SWATH-MS data. For downstream statistical and quantitative analysis there exist different tools such as MSstats, mapDIA and aLFQ. However, the transfer of data from OpenSWATH to the downstream statistical tools is currently technically challenging. Here we introduce the R/Bioconductor package SWATH2stats, which allows convenient processing of the data into a format directly readable by the downstream analysis tools. In addition, SWATH2stats allows annotation, analyzing the variation and the reproducibility of the measurements, FDR estimation, and advanced filtering before submitting the processed data to downstream tools. These functionalities are important to quickly analyze the quality of the SWATH-MS data. Hence, SWATH2stats is a new open-source tool that summarizes several practical functionalities for analyzing, processing, and converting SWATH-MS data and thus facilitates the efficient analysis of large-scale SWATH/DIA datasets.     

Direct and Indirect Relationships Between Specific Leaf Area, Leaf Nitrogen and Leaf Gas Exchange. Effects of Irradiance and Nutrient Supply

We present a series of competing path models relating interspecificpatterns between specific leaf area, leaf nitrogen content,net photosynthesis and stomatal conductance and test these againstdata from 22 species of herbaceous plants grown under controlledconditions with contrasting irradiance and nutrient supply rates.We then compare these results with two previous data sets, onebased on field measures and one based on glasshouse measures,to determine the robustness of the results. Only one model wasable to account for the patterns of direct and indirect effectsbetween the four variables to all data sets. In this model specificleaf area is the forcing variable that directly affects bothleaf nitrogen levels and net photosynthetic rates. Leaf nitrogenthen directly affects net photosynthetic rates which in turnthen affect stomatal conductance to water. Copyright 2001 Annalsof Botany Company Comparative ecology, modelling, path analysis, photosynthesis, plant strategies, SLA, specific leaf area, stomatal conductance     

不同温度处理对虎耳草叶片气体交换及叶肉结构的影响

在人工气候箱中对盆栽虎耳草进行处理,测定不同温度条件下虎耳草叶片光合特征、叶绿素含量、抗氧化酶活性、叶肉结构等生理形态指标。结果表明：低温处理后,虎耳草叶片净光合速率、气孔导度下降迅速,叶绿素含量最少,SOD、CAT活性最低,MDA含量最高,栅栏组织排列更紧密,移置正常温度下,光合速率能在短时间内恢复;高温处理的净光合速率下降速度不及低温处理,但叶片海绵组织显著增加,光合速率恢复较慢。     

Leaf Gas Exchange and Water Relations of Grapevines Grown in Three Different Conditions

Diurnal and seasonal changes in the leaf water potential (), stomatal conductance (g _s), net CO₂ assimilation rate (P _N), transpiration rate (E), internal CO₂ concentration (C _i), and intrinsic water use efficiency (P _N/g _s) were studied in grapevines (Vitis vinifera L. cv. Touriga Nacional) growing in low, moderate, and severe summer stress at Vila Real (VR), Pinhão (PI), and Almendra (AL) experimental sites, respectively. In VR and PI site the limitation to photosynthesis was caused more by stomatal limitations, while in AL mesophyll limitations were also responsible for the summer decline in P _N.     

Relationship between Leaf Structure and Gas Exchange in Wheat Leaves at Different Insertion Levels

Net photosynthesis rate (P_n), stomatal conductance to CO₂ andresidual conductance to CO₂ were measured in the last six leaves(the sixth or flag leaf and the preceding five leaves) of Triticumaestivum L. cv. Kolibri plants grown in Mediterranean conditions.Recently fully expanded leaves of well-watered plants were alwaysused. Measurements were made at saturating photosynthetic photonflux density, and at ambient CO₂ and O₂ levels. The specificleaf area, total organic nitrogen content, some anatomical characteristics,and other parameters, were measured on the same leaves usedfor gas exchange experiments. A progressive xeromorphic adaptation in the leaf structure wasobserved with increasing leaf insertion levels. Furthermore,mesophyll cell volume per unit leaf area (V_mes/A) decreasedby 52·6% from the first leaf to the flag leaf. Mesophyllcell area per unit leaf area also decreased, but only by 24·5%.However, nitrogen content per unit mesophyll cell volume increasedby 50·6% from the first leaf to the flag leaf. This increasecould be associated to an observed higher number of chloroplastcross-sections per mm² of mesophyll cell cross-sectional areain the flag leaf: values of 23000 in the first leaf and 48000in the flag leaf were obtained. P_n per unit leaf area remainedfairly constant at the different insertion levels: values of33·83±0·93 mg dm^–2 h^–1 and32·32±1·61 mg dm^–2 h^–1 wereobtained for the first leaf and the flag leaf, respectively.Residual conductance, however, decreased by 18·2% fromthe first leaf to the flag leaf. Stomatal conductance increasedby 41·7%. The steadiness in P_n per unit leaf area across the leaf insertionlevels could be mainly accounted for by an opposing effect betweena decrease in V_mes/A and a more closely packed arrangement ofphotosynthetic apparatus. Adaptative significance of structuralchanges with increasing leaf insertion levels and the steadinessin P_n per unit leaf area was studied. Key words: Photosynthesis, structure, wheat     

Effects of Angular Leaf Spot and Rust on Leaf Gas Exchange and Yield of Common Bean (Phaseolus Vulgaris)

Isolated and interactive effects of angular leaf spot (caused by Phaeoisariopsis griseola) and rust (caused by Uromyces appendiculatus) on leaf gas exchange and yield was studied in common bean (Phaseolus vulgaris L. cv. Carioca) plants. Gas exchange was measured on 37, 44, 51, and 58 d after planting using a portable photosynthesis system. The inoculation of plants with P. griseola (P), U. appendiculatus (U), and the combination of both pathogens (P+U) caused a significant reduction of net photosynthetic rate (P _N) and yield. The reduction of stomatal conductance (g _s), P _N, and yield was higher under P and combination of P+U than under U treatment. By effect of U, the reduction on yield was higher than the reductions on gas exchange parameters. On the treatment P+U, a reduction of 23 % in P _N and a correspondent reduction of 32 % in yield was observed. The interactive effects of the pathogens on yield could be explained in part by the decreases in g _s and in P _N of diseased bean leaves. The combined effect of both diseases on yield and gas exchange parameters suggests an antagonistic interaction.     

Optimal Regulation of Gas Exchange: Evidence from Field Data

Since the work of Cowan in 1977 it has been assumed that plantsregulate their stomata in a way that maximizes photosynthesisat a constant average rate of transpiration. The approach wasfurther developed by Hari et al. (1986) by introducing additionalassumptions which enabled the mathematical solution of the optimizationproblem using the Lagrangian method. The solution is testedfor Scots pine seedlings against field data. The results supportthe optimization hypothesis.Copyright 1993, 1999 Academic Press Pinus sylvestris (L.), stomatal conductance, photosynthesis, transpiration, optimization, field measurements, mathematical model, Lagrangian method     

Interspecific Differences of Leaf Gas Exchange and Water Relations of Three Evergreen Mediterranean Shrub Species

Leaf gas exchange and plant water relations of three co-occurring evergreen Mediterranean shrubs species, Quercus ilex L. and Phillyrea latifolia L. (typical evergreen sclerophyllous shrubs) and Cistus incanus L. (a drought semi-deciduous shrub), were investigated in order to evaluate possible differences in their adaptive strategies, in particular with respect to drought stress. C. incanus showed the highest annual rate of net photosynthetic rate (P _N) and stomatal conductance (g _s) decreasing by 67 and 69 %, respectively, in summer. P. latifolia and Q. ilex showed lower annual maximum P _N and g _s, although P _N was less lowered in summer (40 and 37 %, respectively). P. latifolia reached the lowest midday leaf water potential (₁) during the drought period (–3.54±0.36 MPa), 11 % lower than in C. incanus and 19 % lower than in Q. ilex. Leaf relative water content (RWC) showed the same trend as ₁. C. incanus showed the lowest RWC values during the drought period (60 %) while they were never below 76 % in P. latifolia and Q. ilex; moreover C. incanus showed the lowest recovery of ₁ at sunset. Hence the studied species are well adapted to the prevailing environment in Mediterranean climate areas, but they show different adaptive strategies that may be useful for their co-occurrence in the same habitat. However, Q. ilex and P. latifolia by their water use strategy seem to be less sensitive to drought stress than C. incanus.     

Relationships Between Nitrogen Content and Net Gas Exchange Components of a Cotton Leaf During Ontogeny

Relationships between leaf nitrogen (N) content and leaf gas exchange components of a single cotton (Gossypium hirsutum L.) leaf subtending the fruit during ontogeny were investigated under field conditions. A 20-d old leaf exhibited the highest physiological activity characterized by net photosynthetic (PN) and transpiration (E) rates, stomatal conductances to CO2 exchange (gsCO2) and water vapor transfer (gsH2O), and nitrogen (N) content. With the advent of leaf senescence, the gas exchange rates declined as exhibited by the 30-, 40-, and 60-d old leaves. Regression analysis indicated close relationships between gsCO2 and PN, and gsH2O and E as the leaves advanced towards senescence. Both PN and gsCO2 were related to N as they declined with leaf age. Thus, the declines in PN were associated with stomatal closure and removal of N during leaf ontogeny.