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/.     

Sink Metabolism: A Conceptual Framework for Analysis

The basic objective of this study was to build a model thatdescribes the physiology of sinks and the process of unloadingassimilates from the phloem. The metabolic steps necessary todescribe a typical sink were obtained from the literature. Severalmethods to describe mathematically these metabolic steps areavailable but they were either too cumbersome and slow or toosimple. This necessitated the development of a new method todescribe multiple enzyme systems. This paper describes the developmentof that method. The method involves a rather simple enzyme analysisof coupled biochemical processes common to most types of sinks.A conceptual framework is presented to provide a basis for furtherquantification of the metabolism of various types of sinks throughtheir development sequence. sink metabolism, model-enzyme kinetics, King-Altman analysis, phloem unloading     

The RGG domain in hnRNP A2 affects subcellular localization

The heterogeneous nuclear ribonucleoproteins (hnRNP) associate with pre-mRNA in the nucleus and play an important role in RNA processing and splice site selection. In addition, hnRNP A proteins function in the export of mRNA to the cytoplasm. Although the hnRNP A proteins are predominantly nuclear, hnRNP A1 shuttles rapidly between the nucleus and the cytoplasm. HnRNP A2, whose cytoplasmic overexpression has been identified as an early biomarker of lung cancer, has been less well studied. Cytosolic hnRNP A2 overexpression has also been noted in brain tumors, in which it has been correlated with translational repression of Glucose Transporter-1 expression. We now examine the role of arginine methylation on the nucleocytoplasmic localization of hnRNP A2 in the HEK-293 and NIH-3T3 mammalian cell lines. Treatment of either cell line with the methyltransferase inhibitor adenosine dialdehyde dramatically shifts hnRNP A2 localization from the nuclear to the cytoplasmic compartment, as shown both by immunoblotting and by immunocytochemistry. In vitro radiolabeling with [(3)H]AdoMet of GST-tagged hnRNP A2 RGG mutants, using recombinant protein arginine methyltransferase (PRMT1), shows (i) that hnRNP A2 is a substrate for PRMT1 and (ii) that methylated residues are found only in the RGG domain. Deletion of the RGG domain (R191-G253) of hnRNP A2 results in a cytoplasmic localization phenotype, detected both by immunoblotting and by immunocytochemistry. These studies indicate that the RGG domain of hnRNP A2 contains sequences critical for cellular localization of the protein. The data suggest that hnRNP A2 may contain a novel nuclear localization sequence, regulated by arginine methylation, that lies in the R191-G253 region and may function independently of the M9 transportin-1-binding region in hnRNP A2.     

Stochastic simulation GUI for biochemical networks

MOTIVATION: This article describes the development of a useful graphical user interface for stochastic simulation of biochemical networks which allows model builders to run stochastic simulations of their models and perform statistical analysis on the results. These include the construction of correlations, power-spectral densities and transfer functions between selected inputs and outputs. AVAILABILITY: The software is licensed under the BSD open source license and is available at http://sourceforge.net/projects/jdesigner. In addition, a more detailed account of the algorithms employed in the tool can be found at the Wiki at http://www.sys-bio.org/sbwWiki. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Multiplexed Sequence Encoding: A Framework for DNA Communication

Synthetic DNA has great propensity for efficiently and stably storing non-biological information. With DNA writing and reading technologies rapidly advancing, new applications for synthetic DNA are emerging in data storage and communication. Traditionally, DNA communication has focused on the encoding and transfer of complete sets of information. Here, we explore the use of DNA for the communication of short messages that are fragmented across multiple distinct DNA molecules. We identified three pivotal points in a communication—data encoding, data transfer & data extraction—and developed novel tools to enable communication via molecules of DNA. To address data encoding, we designed DNA-based individualized keyboards (iKeys) to convert plaintext into DNA, while reducing the occurrence of DNA homopolymers to improve synthesis and sequencing processes. To address data transfer, we implemented a secret-sharing system—Multiplexed Sequence Encoding (MuSE)—that conceals messages between multiple distinct DNA molecules, requiring a combination key to reveal messages. To address data extraction, we achieved the first instance of chromatogram patterning through multiplexed sequencing, thereby enabling a new method for data extraction. We envision these approaches will enable more widespread communication of information via DNA.     

A Genetic-Pathophysiological Framework for Craniosynostosis

Craniosynostosis, the premature fusion of one or more cranial sutures of the skull, provides a paradigm for investigating the interplay of genetic and environmental factors leading to malformation. Over the past 20 years molecular genetic techniques have provided a new approach to dissect the underlying causes; success has mostly come from investigation of clinical samples, and recent advances in high-throughput DNA sequencing have dramatically enhanced the study of the human as the preferred “model organism.” In parallel, however, we need a pathogenetic classification to describe the pathways and processes that lead to cranial suture fusion. Given the prenatal onset of most craniosynostosis, investigation of mechanisms requires more conventional model organisms; principally the mouse, because of similarities in cranial suture development. We present a framework for classifying genetic causes of craniosynostosis based on current understanding of cranial suture biology and molecular and developmental pathogenesis. Of note, few pathologies result from complete loss of gene function. Instead, biochemical mechanisms involving haploinsufficiency, dominant gain-of-function and recessive hypomorphic mutations, and an unusual X-linked cellular interference process have all been implicated. Although few of the genes involved could have been predicted based on expression patterns alone (because the genes play much wider roles in embryonic development or cellular homeostasis), we argue that they fit into a limited number of functional modules active at different stages of cranial suture development. This provides a useful approach both when defining the potential role of new candidate genes in craniosynostosis and, potentially, for devising pharmacological approaches to therapy.     

FunctSNP: an R package to link SNPs to functional knowledge and dbAutoMaker: a suite of Perl scripts to build SNP databases

Background  

Whole genome association studies using highly dense single nucleotide polymorphisms (SNPs) are a set of methods to identify DNA markers associated with variation in a particular complex trait of interest. One of the main outcomes from these studies is a subset of statistically significant SNPs. Finding the potential biological functions of such SNPs can be an important step towards further use in human and agricultural populations (e.g., for identifying genes related to susceptibility to complex diseases or genes playing key roles in development or performance). The current challenge is that the information holding the clues to SNP functions is distributed across many different databases. Efficient bioinformatics tools are therefore needed to seamlessly integrate up-to-date functional information on SNPs. Many web services have arisen to meet the challenge but most work only within the framework of human medical research. Although we acknowledge the importance of human research, we identify there is a need for SNP annotation tools for other organisms.     

Scholarometer: A Social Framework for Analyzing Impact across Disciplines

The use of quantitative metrics to gauge the impact of scholarly publications, authors, and disciplines is predicated on the availability of reliable usage and annotation data. Citation and download counts are widely available from digital libraries. However, current annotation systems rely on proprietary labels, refer to journals but not articles or authors, and are manually curated. To address these limitations, we propose a social framework based on crowdsourced annotations of scholars, designed to keep up with the rapidly evolving disciplinary and interdisciplinary landscape. We describe a system called Scholarometer, which provides a service to scholars by computing citation-based impact measures. This creates an incentive for users to provide disciplinary annotations of authors, which in turn can be used to compute disciplinary metrics. We first present the system architecture and several heuristics to deal with noisy bibliographic and annotation data. We report on data sharing and interactive visualization services enabled by Scholarometer. Usage statistics, illustrating the data collected and shared through the framework, suggest that the proposed crowdsourcing approach can be successful. Secondly, we illustrate how the disciplinary bibliometric indicators elicited by Scholarometer allow us to implement for the first time a universal impact measure proposed in the literature. Our evaluation suggests that this metric provides an effective means for comparing scholarly impact across disciplinary boundaries.     

Dynamical Systems and Depression: A Framework for Theoretical Perspectives

The theory of dynamical systems allows one to describe the change in a system's macroscopic behavior as a bifurcation in the underlying dynamics. We show here, from the example of depressive syndrome, the existence of a correspondence between clinical and electro-physiological dimensions and the association between clinical remission and brain dynamics reorganization (i.e. bifurcation). On the basis of this experimental study, we discuss the interest of such results concerning the question of normality versus pathology in psychiatry and the relationship between mind and brain.     

PATHLOGIC-S: A Scalable Boolean Framework for Modelling Cellular Signalling

Curated databases of signal transduction have grown to describe several thousand reactions, and efficient use of these data requires the development of modelling tools to elucidate and explore system properties. We present PATHLOGIC-S, a Boolean specification for a signalling model, with its associated GPL-licensed implementation using integer programming techniques. The PATHLOGIC-S specification has been designed to function on current desktop workstations, and is capable of providing analyses on some of the largest currently available datasets through use of Boolean modelling techniques to generate predictions of stable and semi-stable network states from data in community file formats. PATHLOGIC-S also addresses major problems associated with the presence and modelling of inhibition in Boolean systems, and reduces logical incoherence due to common inhibitory mechanisms in signalling systems. We apply this approach to signal transduction networks including Reactome and two pathways from the Panther Pathways database, and present the results of computations on each along with a discussion of execution time. A software implementation of the framework and model is freely available under a GPL license.     

IdBean: a Java GUI application for conversion of biological identifiers

We have developed a biologist-friendly, stand-alone Java GUI application, IdBean, for ID conversion. Our tool integrated most of the widely used ID conversion services that provide programmatic access. It is the first GUI ID conversion application that supports the direct merging as well as comparison of conversion results from multiple ID conversion services without manual effort. This tool will greatly help biologists who handle multiple ID types for the analyses of gene or gene product lists. By referring to multiple conversion services, the number of failed IDs can be reduced. By accessing ID conversion service online, it will potentially provide the most up-to-date conversion results. The application was developed in modular form; however, it can be re-packaged into plug-in form. For the development of a bioinformatics analysis tool, the module can be used as a built-in ID conversion component. It is available at http://neon.gachon.ac.kr/IdBean/.     

PyroTrimmer: a software with GUI for pre-processing 454 amplicon sequences

The ultimate goal of metagenome research projects is to understand the ecological roles and physiological functions of the microbial communities in a given natural environment. The 454 pyrosequencing platform produces the longest reads among the most widely used next generation sequencing platforms. Since the relatively longer reads of the 454 platform provide more information for identification of microbial sequences, this platform is dedicated to microbial community and population studies. In order to accurately perform the downstream analysis of the 454 multiplex datasets, it is necessary to remove artificially designed sequences located at either ends of individual reads and to correct low-quality sequences. We have developed a program called PyroTrimmer that removes the barcodes, linkers, and primers, trims sequence regions with low quality scores, and filters out low-quality sequence reads. Although these functions have previously been implemented in other programs as well, PyroTrimmer has novelty in terms of the following features: i) more sensitive primer detection using Levenstein distance and global pairwise alignment, ii) the first stand-alone software with a graphic user interface, and iii) various options for trimming and filtering out the low-quality sequence reads. PyroTrimmer, written in JAVA, is compatible with multiple operating systems and can be downloaded free at http://pyrotrimmer.kobic.re.kr.     

SPRINT: A new parallel framework for R

Background  

Microarray analysis allows the simultaneous measurement of thousands to millions of genes or sequences across tens to thousands of different samples. The analysis of the resulting data tests the limits of existing bioinformatics computing infrastructure. A solution to this issue is to use High Performance Computing (HPC) systems, which contain many processors and more memory than desktop computer systems. Many biostatisticians use R to process the data gleaned from microarray analysis and there is even a dedicated group of packages, Bioconductor, for this purpose. However, to exploit HPC systems, R must be able to utilise the multiple processors available on these systems. There are existing modules that enable R to use multiple processors, but these are either difficult to use for the HPC novice or cannot be used to solve certain classes of problems. A method of exploiting HPC systems, using R, but without recourse to mastering parallel programming paradigms is therefore necessary to analyse genomic data to its fullest.