JColorGrid: software for the visualization of biological measurements

Background  

Two-dimensional data colourings are an effective medium by which to represent three-dimensional data in two dimensions. Such "color-grid" representations have found increasing use in the biological sciences (e.g. microarray 'heat maps' and bioactivity data) as they are particularly suited to complex data sets and offer an alternative to the graphical representations included in traditional statistical software packages. The effectiveness of color-grids lies in their graphical design, which introduces a standard for customizable data representation. Currently, software applications capable of generating limited color-grid representations can be found only in advanced statistical packages or custom programs (e.g. micro-array analysis tools), often associated with steep learning curves and requiring expert knowledge.     

A fuzzy coding approach for the analysis of long-term ecological data

• 1 We present an unconventional procedure (fuzzy coding) to structure biological and environmental information, which uses positive scores to describe the affinity of a species for different modalities (i.e. categories) of a given variable. Fuzzy coding is essential for the synthesis of long-term ecological data because it enables analysis of diverse kinds of biological information derived from a variety of sources (e.g. samples, literature).
• 2 A fuzzy coded table can be processed by correspondence analysis. An example using aquatic beetles illustrates the properties of such a fuzzy correspondence analysis. Fuzzy coded tables were used in all articles of this issue to examine relationships between spatial-temporal habitat variability and species traits, which were obtained from a long-term study of the Upper Rhône River, France.
• 3 Fuzzy correspondence analysis can be programmed with the equations given in this paper or can be performed using ADE (Environmental Data Analysis) software that has been adapted to analyse such long-term ecological data. On Macintosh Apple^TM computers, ADE performs simple linear ordination, more recently developed methods (e.g. principal component analysis with respect to instrumental variables, canonical correspondence analysis, co-inertia analysis, local and spatial analyses), and provides a graphical display of results of these and other types of analysis (e.g. biplot, mapping, modelling curves).
• 4 ADE consists of a program library that exploits the potential of the HyperCard^TM interface. ADE in an open system, which offers the user a variety of facilities to create a specific sequence of programs. The mathematical background of ADE is supported by the algebraic model known as ‘duality diagram’.

     

Evaluating the Effectiveness of Self-Administration of Medication (SAM) Schemes in the Hospital Setting: A Systematic Review of the Literature

Background

Self-administration of medicines is believed to increase patients'' understanding about their medication and to promote their independence and autonomy in the hospital setting. The effect of inpatient self-administration of medication (SAM) schemes on patients, staff and institutions is currently unclear.

Objective

To systematically review the literature relating to the effect of SAM schemes on the following outcomes: patient knowledge, patient compliance/medication errors, success in self-administration, patient satisfaction, staff satisfaction, staff workload, and costs.

Design

Keyword and text word searches of online databases were performed between January and March 2013. Included articles described and evaluated inpatient SAM schemes. Case studies and anecdotal studies were excluded.

Results

43 papers were included for final analysis. Due to the heterogeneity of results and unclear findings it was not possible to perform a quantitative synthesis of results. Participation in SAM schemes often led to increased knowledge about drugs and drug regimens, but not side effects. However, the effect of SAM schemes on patient compliance/medication errors was inconclusive. Patients and staff were highly satisfied with their involvement in SAM schemes.

Conclusions

SAM schemes appear to provide some benefits (e.g. increased patient knowledge), but their effect on other outcomes (e.g. compliance) is unclear. Few studies of high methodological quality using validated outcome measures exist. Inconsistencies in both measuring and reporting outcomes across studies make it challenging to compare results and draw substantive conclusions about the effectiveness of SAM schemes.     

GUItars: A GUI Tool for Analysis of High-Throughput RNA Interference Screening Data

Background

High-throughput RNA interference (RNAi) screening has become a widely used approach to elucidating gene functions. However, analysis and annotation of large data sets generated from these screens has been a challenge for researchers without a programming background. Over the years, numerous data analysis methods were produced for plate quality control and hit selection and implemented by a few open-access software packages. Recently, strictly standardized mean difference (SSMD) has become a widely used method for RNAi screening analysis mainly due to its better control of false negative and false positive rates and its ability to quantify RNAi effects with a statistical basis. We have developed GUItars to enable researchers without a programming background to use SSMD as both a plate quality and a hit selection metric to analyze large data sets.

Results

The software is accompanied by an intuitive graphical user interface for easy and rapid analysis workflow. SSMD analysis methods have been provided to the users along with traditionally-used z-score, normalized percent activity, and t-test methods for hit selection. GUItars is capable of analyzing large-scale data sets from screens with or without replicates. The software is designed to automatically generate and save numerous graphical outputs known to be among the most informative high-throughput data visualization tools capturing plate-wise and screen-wise performances. Graphical outputs are also written in HTML format for easy access, and a comprehensive summary of screening results is written into tab-delimited output files.

Conclusion

With GUItars, we demonstrated robust SSMD-based analysis workflow on a 3840-gene small interfering RNA (siRNA) library and identified 200 siRNAs that increased and 150 siRNAs that decreased the assay activities with moderate to stronger effects. GUItars enables rapid analysis and illustration of data from large- or small-scale RNAi screens using SSMD and other traditional analysis methods. The software is freely available at http://sourceforge.net/projects/guitars/.     

Improving the production of S-adenosyl-L-methionine in Escherichia coli by overexpressing metk

S-adenosyl-L-methionine (SAM) has important applications in many fields including chemical therapy and pharmaceutical industry. In this study, the recombinant Escherichia coli strain was constructed for effective production of SAM by introducing the SAM synthase gene (metK). This strain produced 34.5?mg/L of SAM in basic medium in shake flask. Yeast extract, pH, and loaded volume had a significant positive effect on the yield of SAM. Their optimal values were 35?g/L, 7.5, and 30?mL, respectively. The final conditions optimized were as follows: glucose 20, g/L; peptone, 40?g/L; yeast extract, 35?g/L; NaCl, 10?g/L; MgSO₄, 1.2?g/L; L-methionine, 1?g/L; rotate speed, 220?rpm; loaded volume, 30?mL; inoculation, 1%; temperature, 37°C; and initial medium, pH 7.5. The recombinant strain produced 128.2?mg/L of SAM under the above conditions in shake flask. The production of SAM in a 5?L fermentor was also investigated. The maximal biomass of the recombinant strain was 60.4?g/L after the cells were cultured for 20?hr, and the highest yield of SAM was 300.9?mg/L after induction for 8?hr in a 5?L fermentor. This study provides a good foundation for the future production and use of SAM.     

BicAT: a biclustering analysis toolbox

SUMMARY: Besides classical clustering methods such as hierarchical clustering, in recent years biclustering has become a popular approach to analyze biological data sets, e.g. gene expression data. The Biclustering Analysis Toolbox (BicAT) is a software platform for clustering-based data analysis that integrates various biclustering and clustering techniques in terms of a common graphical user interface. Furthermore, BicAT provides different facilities for data preparation, inspection and postprocessing such as discretization, filtering of biclusters according to specific criteria or gene pair analysis for constructing gene interconnection graphs. The possibility to use different biclustering algorithms inside a single graphical tool allows the user to compare clustering results and choose the algorithm that best fits a specific biological scenario. The toolbox is described in the context of gene expression analysis, but is also applicable to other types of data, e.g. data from proteomics or synthetic lethal experiments. AVAILABILITY: The BicAT toolbox is freely available at http://www.tik.ee.ethz.ch/sop/bicat and runs on all operating systems. The Java source code of the program and a developer's guide is provided on the website as well. Therefore, users may modify the program and add further algorithms or extensions.     

MPSA: integrated system for multiple protein sequence analysis with client/server capabilities

SUMMARY: MPSA is a stand-alone software intended to protein sequence analysis with a high integration level and Web clients/server capabilities. It provides many methods and tools, which are integrated into an interactive graphical user interface. It is available for most Unix/Linux and non-Unix systems. MPSA is able to connect to a Web server (e.g. http://pbil.ibcp.fr/NPSA) in order to perform large-scale sequence comparison on up-to-date databanks. AVAILABILITY: Free to academic http://www.ibcp.fr/mpsa/ CONTACT: c.blanchet@ibcp.fr     

The Effect of S-Adenosylmethionine on Cognitive Performance in Mice: An Animal Model Meta-Analysis

Background

Alzheimer''s disease (AD) is the most frequently diagnosed form of dementia resulting in cognitive impairment. Many AD mouse studies, using the methyl donor S-adenosylmethionine (SAM), report improved cognitive ability, but conflicting results between and within studies currently exist. To address this, we conducted a meta-analysis to evaluate the effect of SAM on cognitive ability as measured by Y maze performance. As supporting evidence, we include further discussion of improvements in cognitive ability, by SAM, as measured by the Morris water maze (MWM).

Methods

We conducted a comprehensive literature review up to April 2014 based on searches querying MEDLINE, EMBASE, Web of Science, the Cochrane Library and Proquest Theses and Dissertation databases. We identified three studies containing a total of 12 experiments that met our inclusion criteria and one study for qualitative review. The data from these studies were used to evaluate the effect of SAM on cognitive performance according to two scenarios: 1. SAM supplemented folate deficient (SFD) diet compared to a folate deficient (FD) diet and 2. SFD diet compared to a nutrient complete (NC) diet. Hedge''s g was used to calculate effect sizes and mixed effects model meta-regression was used to evaluate moderating factors.

Results

Our findings showed that the SFD diet was associated with improvements in cognitive performance. SFD diet mice also had superior cognitive performance compared to mice on an NC diet. Further to this, meta-regression analyses indicated a significant positive effect of study quality score and treatment duration on the effect size estimate for both the FD vs SFD analysis and the SFD vs NC analysis.

Conclusion

The findings of this meta-analysis demonstrate efficacy of SAM in acting as a cognitive performance-enhancing agent. As a corollary, SAM may be useful in improving spatial memory in patients suffering from many dementia forms including AD.     

Whole genome transcriptome polymorphisms in Arabidopsis thaliana

ArrayPlex is a software package that centrally provides a large number of flexible toolsets useful for functional genomics, including microarray data storage, quality assessments, data visualization, gene annotation retrieval, statistical tests, genomic sequence retrieval and motif analysis. It uses a client-server architecture based on open source components, provides graphical, command-line, and programmatic access to all needed resources, and is extensible by virtue of a documented application programming interface. ArrayPlex is available at http://sourceforge.net/projects/arrayplex/.     

In silico Biochemical Reaction Network Analysis (IBRENA): a package for simulation and analysis of reaction networks

Summary: We present In silico Biochemical Reaction Network Analysis(IBRENA), a software package which facilitates multiple functionsincluding cellular reaction network simulation and sensitivityanalysis (both forward and adjoint methods), coupled with principalcomponent analysis, singular-value decomposition and model reduction.The software features a graphical user interface that aids simulationand plotting of in silico results. While the primary focus isto aid formulation, testing and reduction of theoretical biochemicalreaction networks, the program can also be used for analysisof high-throughput genomic and proteomic data. Availability: The software package, manual and examples areavailable at http://www.eng.buffalo.edu/~neel/ibrena Contact: neel{at}eng.buffalo.edu Associate Editor: Limsoon Wong     

cljam: a library for handling DNA sequence alignment/map (SAM) with parallel processing

Background

Next-generation sequencing can determine DNA bases and the results of sequence alignments are generally stored in files in the Sequence Alignment/Map (SAM) format and the compressed binary version (BAM) of it. SAMtools is a typical tool for dealing with files in the SAM/BAM format. SAMtools has various functions, including detection of variants, visualization of alignments, indexing, extraction of parts of the data and loci, and conversion of file formats. It is written in C and can execute fast. However, SAMtools requires an additional implementation to be used in parallel with, for example, OpenMP (Open Multi-Processing) libraries. For the accumulation of next-generation sequencing data, a simple parallelization program, which can support cloud and PC cluster environments, is required.

Results

We have developed cljam using the Clojure programming language, which simplifies parallel programming, to handle SAM/BAM data. Cljam can run in a Java runtime environment (e.g., Windows, Linux, Mac OS X) with Clojure.

Conclusions

Cljam can process and analyze SAM/BAM files in parallel and at high speed. The execution time with cljam is almost the same as with SAMtools. The cljam code is written in Clojure and has fewer lines than other similar tools.

     

Evaluation of methods for detecting conversion events in gene clusters

Background

Several platforms for the analysis of genome-wide association data are available. However, these platforms focus on the evaluation of the genotype inherited by affected (i.e. case) individuals, whereas for some conditions (e.g. birth defects) the genotype of the mothers of affected individuals may also contribute to risk. For such conditions, it is critical to evaluate associations with both the maternal and the inherited (i.e. case) genotype. When genotype data are available for case-parent triads, a likelihood-based approach using log-linear modeling can be used to assess both the maternal and inherited genotypes. However, available software packages for log-linear analyses are not well suited to the analysis of typical genome-wide association data (e.g. including missing data).

Results

An integrated platform, Maternal and Inherited Analyses for Genome-wide Association Studies (MI-GWAS) for log-linear analyses of maternal and inherited genetic effects in large, genome-wide datasets, is described. MI-GWAS uses SAS and LEM software in combination to appropriately format data, perform the log-linear analyses and summarize the results. This platform was evaluated using existing genome-wide data and was shown to perform accurately and relatively efficiently.

Conclusions

The MI-GWAS platform provides a valuable tool for the analysis of association of a phenotype or condition with maternal and inherited genotypes using genome-wide data from case-parent triads. The source code for this platform is freely available at http://www.sph.uth.tmc.edu/sbrr/mi-gwas.htm.     

N-Methylation of quinolizidine alkaloids: an S-adenosyl-l-methionine: cytisine N-methyltransferase from Laburnum anagyroides plants and cell cultures of L. alpinum and Cytisus canariensis

An S-adenosyl-l-methionine (SAM): cytisine N-methyltransferase could be demonstrated in crude enzyme preparations from Laburnum anagyroides plants and cell cultures of L. alpinum and Cytisus canariensis. The transferase specifically catalyzes the transfer of a methyl group from SAM to cytisine. The apparent K_m values are 60 mol l^-1 for cytisine and 17 mol l^-1 for SAM. Other quinolizidine alkaloids, e.g. angustifoline and albine, are N-methylated by only 10–15%. The transferase shows a pH optimum at pH 8.5. It is activated by dithioerythritol and inhibited by thiol reagents and Fe²⁺ and Fe³⁺. The reaction product S-adenosylhomocysteine is a powerful inhibitor of the transferase reaction. Cell cultures of L. alpinum which have an active SAM: cytisine N-methyltransferase and which are able to N-methylate exogenous cytisine in vivo, do not accumulate cytisine or N-methylcytisine to a detectable degree.Abbreviations GLC gas-liquid chromatography - SAM S-adenosylmethionine - TLC thin-layer chromatography     

VIP Barcoding: composition vector‐based software for rapid species identification based on DNA barcoding

Species identification based on short sequences of DNA markers, that is, DNA barcoding, has emerged as an integral part of modern taxonomy. However, software for the analysis of large and multilocus barcoding data sets is scarce. The Basic Local Alignment Search Tool (BLAST) is currently the fastest tool capable of handling large databases (e.g. >5000 sequences), but its accuracy is a concern and has been criticized for its local optimization. However, current more accurate software requires sequence alignment or complex calculations, which are time‐consuming when dealing with large data sets during data preprocessing or during the search stage. Therefore, it is imperative to develop a practical program for both accurate and scalable species identification for DNA barcoding. In this context, we present VIP Barcoding: a user‐friendly software in graphical user interface for rapid DNA barcoding. It adopts a hybrid, two‐stage algorithm. First, an alignment‐free composition vector (CV) method is utilized to reduce searching space by screening a reference database. The alignment‐based K2P distance nearest‐neighbour method is then employed to analyse the smaller data set generated in the first stage. In comparison with other software, we demonstrate that VIP Barcoding has (i) higher accuracy than Blastn and several alignment‐free methods and (ii) higher scalability than alignment‐based distance methods and character‐based methods. These results suggest that this platform is able to deal with both large‐scale and multilocus barcoding data with accuracy and can contribute to DNA barcoding for modern taxonomy. VIP Barcoding is free and available at http://msl.sls.cuhk.edu.hk/vipbarcoding/ .     

Regulation of retrochalcone biosynthesis: Activity changes of O-methyltransferases in the yeast extract-induced Glycyrrhiza echinata cells

Three O-methyltransferases which catalyze S-adenosyl-L-methionine (SAM)-dependent O-methylation of licodione (LMT), flavone/flavonol (FMT), and caffeic acid (CMT) were separated from the callus culture of Glycyrrhiza echinata, and characteristic differences between their pH optima and Mg²⁺ requirement for activity were demonstrated. The activity of LMT, which is involved in retrochalcone (echinatin) biosynthesis, but not of FMT or CMT, was found to be stimulated when suspension-cultured G. echinata cells were treated with yeast extract (YE), which causes rapid production of echinatin in the cells. Cycloheximide suppressed both the YE-induced echinatin formation and LMT enhancement. The results indicate a selective induction of retrochalcone pathway in Glycyrrhiza cells in response to stress.Abbreviations SAM S-adenosyl-L-methionine - LMT, SAM licodione 2-O-methyltransferase - FMT, SAM flavone/flavonol O-methyltransferase - CMT, SAM caffeate 3-O-methyltransferase - OMT O-methyltransferase - CH cycloheximide - YE yeast extract This paper is Part 47 in the series Studies on Plant Tissue Cultures. For Part 46, see Ayabe S, Iida K, Furuya T (1986) Phytochemistry: in press     

Turning publicly available gene expression data into discoveries using gene set context analysis

Gene Set Context Analysis (GSCA) is an open source software package to help researchers use massive amounts of publicly available gene expression data (PED) to make discoveries. Users can interactively visualize and explore gene and gene set activities in 25,000+ consistently normalized human and mouse gene expression samples representing diverse biological contexts (e.g. different cells, tissues and disease types, etc.). By providing one or multiple genes or gene sets as input and specifying a gene set activity pattern of interest, users can query the expression compendium to systematically identify biological contexts associated with the specified gene set activity pattern. In this way, researchers with new gene sets from their own experiments may discover previously unknown contexts of gene set functions and hence increase the value of their experiments. GSCA has a graphical user interface (GUI). The GUI makes the analysis convenient and customizable. Analysis results can be conveniently exported as publication quality figures and tables. GSCA is available at https://github.com/zji90/GSCA. This software significantly lowers the bar for biomedical investigators to use PED in their daily research for generating and screening hypotheses, which was previously difficult because of the complexity, heterogeneity and size of the data.     

Comprehensive analysis of NMR data using advanced line shape fitting

NMR spectroscopy is uniquely suited for atomic resolution studies of biomolecules such as proteins, nucleic acids and metabolites, since detailed information on structure and dynamics are encoded in positions and line shapes of peaks in NMR spectra. Unfortunately, accurate determination of these parameters is often complicated and time consuming, in part due to the need for different software at the various analysis steps and for validating the results. Here, we present an integrated, cross-platform and open-source software that is significantly more versatile than the typical line shape fitting application. The software is a completely redesigned version of PINT (https://pint-nmr.github.io/PINT/). It features a graphical user interface and includes functionality for peak picking, editing of peak lists and line shape fitting. In addition, the obtained peak intensities can be used directly to extract, for instance, relaxation rates, heteronuclear NOE values and exchange parameters. In contrast to most available software the entire process from spectral visualization to preparation of publication-ready figures is done solely using PINT and often within minutes, thereby, increasing productivity for users of all experience levels. Unique to the software are also the outstanding tools for evaluating the quality of the fitting results and extensive, but easy-to-use, customization of the fitting protocol and graphical output. In this communication, we describe the features of the new version of PINT and benchmark its performance.     

SATCHMO: sequence alignment and tree construction using hidden Markov models

MOTIVATION:Aligning multiple proteins based on sequence information alone is challenging if sequence identity is low or there is a significant degree of structural divergence. We present a novel algorithm (SATCHMO) that is designed to address this challenge. SATCHMO simultaneously constructs a tree and a set of multiple sequence alignments, one for each internal node of the tree. The alignment at a given node contains all sequences within its sub-tree, and predicts which positions in those sequences are alignable and which are not. Aligned regions therefore typically get shorter on a path from a leaf to the root as sequences diverge in structure. Current methods either regard all positions as alignable (e.g. ClustalW), or align only those positions believed to be homologous across all sequences (e.g. profile HMM methods); by contrast SATCHMO makes different predictions of alignable regions in different subgroups. SATCHMO generates profile hidden Markov models at each node; these are used to determine branching order, to align sequences and to predict structurally alignable regions. RESULTS: In experiments on the BAliBASE benchmark alignment database, SATCHMO is shown to perform comparably to ClustalW and the UCSC SAM HMM software. Results using SATCHMO to identify protein domains are demonstrated on potassium channels, with implications for the mechanism by which tumor necrosis factor alpha affects potassium current. AVAILABILITY: The software is available for download from http://www.drive5.com/lobster/index.htm