SeeGH – A software tool for visualization of whole genome array comparative genomic hybridization data

Background  

Array comparative genomic hybridization (CGH) is a technique which detects copy number differences in DNA segments. Complete sequencing of the human genome and the development of an array representing a tiling set of tens of thousands of DNA segments spanning the entire human genome has made high resolution copy number analysis throughout the genome possible. Since array CGH provides signal ratio for each DNA segment, visualization would require the reassembly of individual data points into chromosome profiles.     

CGHPRO – A comprehensive data analysis tool for array CGH

Background  

Array CGH (Comparative Genomic Hybridisation) is a molecular cytogenetic technique for the genome wide detection of chromosomal imbalances. It is based on the co-hybridisation of differentially labelled test and reference DNA onto arrays of genomic BAC clones, cDNAs or oligonucleotides, and after correction for various intervening variables, loss or gain in the test DNA can be indicated from spots showing aberrant signal intensity ratios.     

“dendRoAnalyst”: A tool for processing and analysing dendrometer data

Dendrometers are vital tools for studying the response of trees to intra-annual environmental changes in different temporal resolutions, ranging from hourly, daily to weekly time resolution. Dendrometers are increasingly used in forest management and tree physiological studies. Besides the data analysis, data processing is also challenging, time-consuming and potentially error-prone due to the immense number of measurements generated by self-registering electronic dendrometers. We present the package ‘dendRoAnalyst’ based on R statistical software to process and analyse dendrometer data using various approaches. This package offers algorithms for handling and pre-cleaning of dendrometer data before the application of subsequent data analytical steps. This includes identifying and erasing artefacts in dendrometer datasets not related to actual stem circumference change, identifying data gaps within records, and the possibility of change(s) in temporal resolution. Furthermore, the package can calculate different daily statistics of dendrometer data, including the daily amplitude of tree growth. The package dendRoAnalyst is therefore intended to facilitate researchers with a collection of functions for handling and analysing dendrometer data.     

ExonVisualiser – application for visualization exon units in 2D and 3D protein structures

The web application oriented on identification and visualization of protein regions encoded by exons is presented. The Exon Visualiser can be used for visualisation on different levels of protein structure: at the primary (sequence) level and secondary structures level, as well as at the level of tertiary protein structure. The programme is suitable for processing data for all genes which have protein expressions deposited in the PDB database. The procedure steps implemented in the application: I) loading exons sequences and theirs coordinates from GenBank file as well as protein sequences: CDS from GenBank and aminoacid sequence from PDB II) consensus sequence creation (comparing amino acid sequences form PDB file with the CDS sequence from GenBank file) III) matching exon coordinates IV) visualisation in 2D and 3D protein structures. Presented web-tool among others provides the color-coded graphical display of protein sequences and chains in three dimensional protein structures which are correlated with the corresponding exons.

Availability

http://149.156.12.53/ExonVisualiser/     

TableButler – a Windows based tool for processing large data tables generated with high-throughput methods

Background  

High-throughput "omics" based data analysis play emerging roles in life sciences and molecular diagnostics. This emphasizes the urgent need for user-friendly windows-based software interfaces that could process the diversity of large tab-delimited raw data files generated by these methods. Depending on the study, dozens to hundreds of these data tables are generated. Before the actual statistical or cluster analysis, these data tables have to be combined and merged to expression matrices (e.g., in case of gene expression analysis). Gene annotations as well as information concerning the samples analyzed may be appended, renewed or extended. Often additional data values shall be computed or certain features must be filtered out.     

Elviz – exploration of metagenome assemblies with an interactive visualization tool

Background

Metagenomics, the sequencing of DNA collected from an entire microbial community, enables the study of natural microbial consortia in their native habitats. Metagenomics studies produce huge volumes of data, including both the sequences themselves and metadata describing their abundance, assembly, predicted functional characteristics and environmental parameters. The ability to explore these data visually is critically important to meaningful biological interpretation. Current genomics applications cannot effectively integrate sequence data, assembly metadata, and annotation to support both genome and community-level inquiry.

Results

Elviz (Environmental Laboratory Visualization) is an interactive web-based tool for the visual exploration of assembled metagenomes and their complex metadata. Elviz allows scientists to navigate metagenome assemblies across multiple dimensions and scales, plotting parameters such as GC content, relative abundance, phylogenetic affiliation and assembled contig length. Furthermore Elviz enables interactive exploration using real-time plot navigation, search, filters, axis selection, and the ability to drill from a whole-community profile down to individual gene annotations. Thus scientists engage in a rapid feedback loop of visual pattern identification, hypothesis generation, and hypothesis testing.

Conclusions

Compared to the current alternative of generating a succession of static figures, Elviz can greatly accelerate the speed of metagenome analysis. Elviz can be used to explore both user-submitted datasets and numerous metagenome studies publicly available at the Joint Genome Institute (JGI). Elviz is freely available at http://genome.jgi.doe.gov/viz and runs on most current web-browsers.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0566-4) contains supplementary material, which is available to authorized users.     

SpectralNET – an application for spectral graph analysis and visualization

Background  

Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks.     

4SALE – A tool for synchronous RNA sequence and secondary structure alignment and editing

Background  

In sequence analysis the multiple alignment builds the fundament of all proceeding analyses. Errors in an alignment could strongly influence all succeeding analyses and therefore could lead to wrong predictions. Hand-crafted and hand-improved alignments are necessary and meanwhile good common practice. For RNA sequences often the primary sequence as well as a secondary structure consensus is well known, e.g., the cloverleaf structure of the t-RNA. Recently, some alignment editors are proposed that are able to include and model both kinds of information. However, with the advent of a large amount of reliable RNA sequences together with their solved secondary structures (available from e.g. the ITS2 Database), we are faced with the problem to handle sequences and their associated secondary structures synchronously.     

caBIG™ VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data

Background

We sketch our species identification tool for palm sized computers that helps knowledgeable observers with census activities. An algorithm turns an identification matrix into a minimal length series of questions that guide the operator towards identification. Historic observation data from the census geographic area helps minimize question volume. We explore how much historic data is required to boost performance, and whether the use of history negatively impacts identification of rare species. We also explore how characteristics of the matrix interact with the algorithm, and how best to predict the probability of observing a previously unseen species.

Results

Point counts of birds taken at Stanford University's Jasper Ridge Biological Preserve between 2000 and 2005 were used to examine the algorithm. A computer identified species by correctly answering, and counting the algorithm's questions. We also explored how the character density of the key matrix and the theoretical minimum number of questions for each bird in the matrix influenced the algorithm. Our investigation of the required probability smoothing determined whether Laplace smoothing of observation probabilities was sufficient, or whether the more complex Good-Turing technique is required.

Conclusion

Historic data improved identification speed, but only impacted the top 25% most frequently observed birds. For rare birds the history based algorithms did not impose a noticeable penalty in the number of questions required for identification. For our dataset neither age of the historic data, nor the number of observation years impacted the algorithm. Density of characters for different taxa in the identification matrix did not impact the algorithms. Intrinsic differences in identifying different birds did affect the algorithm, but the differences affected the baseline method of not using historic data to exactly the same degree. We found that Laplace smoothing performed better for rare species than Simple Good-Turing, and that, contrary to expectation, the technique did not then adversely affect identification performance for frequently observed birds.     

Microbial pretreatment of coals: A tool for solubilization of lignite in organic solvent – quinoline

A method was developed for the conversion of low rank coals to products soluble in an organic solvent (quinoline). A selected group of polynuclear aromatic-compound-degrading and lignin-degrading facultative pure cultures and enriched anaerobic mixed microbial cultures developed for this purpose were used separately as well as together under co-culture conditions for stepwise treatment of Neyveli lignite (NL). This aerobic-anaerobic co-metabolic (co-culture) biodegradation (AACB) process resulted in the enhancement of quinoline extractability of the lignite, thereby yielding clean coal substance (the extract). The residual lignite obtained after quinoline extraction was subjected to a second step of AACB fermentation treatment. This resulted in further extraction of lignite in quinoline. The conditions were optimised for AACB fermentation treatment. The two-step AACB fermentation process under optimum conditions, resulted in an overall enhancement of yield of extract from 18% for the original lignite sample to 56% for the treated sample. The changes in the filtrate were evaluated using UV spectra, those in the residue were evaluated using FTIR spectroscopy and UV-reflectance and those in the extract using proton NMR spectra of the chloroform soluble fraction. The results indicated a decreased absorption in the carbonyl region in the AACB-treated residue and also a decrease in the overall mineral matter in the lignite samples. The mechanism of the AACB fermentation process is discussed. The process affords biosolubilization of lignite in organic solvent (quinoline) under milder conditions along with a simultaneous removal of a part of the mineral matter present in the coal. Uses for the clean coal extract obtained are suggested.     

Assessment of time patterns of activity and rest in full-shift recordings of trapezius muscle activity – Effects of the data processing procedure

The purpose of this paper was to compare the effects of different data reduction procedures on the values of variables characterizing the time pattern of trapezius muscle activity during full work shifts. Surface electromyography (EMG) of the right and left upper trapezius muscles were obtained from 40 young subjects in different occupations, mainly electricians, hairdressers and students. The target EMG variables were gap frequency, muscle rest, and the number and duration of episodes with sustained muscle activity (from 0.13 s to 30 min as minimum duration). These variables were derived from the EMG recordings using different Root Mean Square (RMS) windows (from 0.13 to 6.38 s), and discrimination levels between “activity” and “rest” (0.5%, 1% and 2% of maximal EMG).The results give basis for practical suggestions for EMG analyses of full work shifts. For most variables, a discrimination level of 0.5% EMG_max showed to be preferable. The time proportion of muscle rest and sustained muscle activity should, in general, be preferred over the corresponding frequency measures. Sustained muscle activity should be calculated using a RMS window between 1 and 3 s, and preferably be stated in terms of variables describing time proportions of activity. Uninterrupted activity episodes longer than 10 min proved not to be a useful variable due to limited occurrence in many work shifts.     

The IAEA Radiotracer Biodistribution Template – A community resource for supporting the standardization and reporting of radionuclide pre-dosimetry data

Radionuclide absorbed-dose dosimetry is an active area of development and has the potential to positively impact molecular radiotherapies. At present, many of the operations required to perform dosimetry calculations are unstandardized and unestablished. While the current methodology allows reasonable dosimetry estimates to be derived and published, it can be difficult to understand, and reproduce, each others’ work. To help alleviate this we have identified the collection of biodistribution information as a key step in all internal dosimetry calculations, and present a template that can be used to standardize its documentation and reporting.A generalized biodistribution template entitled the IAEA Radiotracer Biodistribution Template (IAEA RaBiT) has been built and distributed for users performing biodistribution measurements in the community. The template enables robust recording of dosimetry-relevant information through standardization of details and their format. It has been designed to be simple and easy to use, and establish a structured recording of a common reference point in dosimetry operations – biodistribution data documentation. Improved documentation procedures may benefit organization of in house data, or be used to disseminate details throughout the community – for example to supplement dosimetry related publications. The standard format information may also enable the creation of new dosimetry related tools and protocols and support robust population databases.As dosimetry in nuclear medicine becomes more routinely applied in clinical applications, we need to develop the infrastructure for robustly handling large amounts of these data. Our IAEA RaBiT can be used as a standard format structure for data collection, organization, and dissemination.     

MRCZ – A file format for cryo-TEM data with fast compression

The introduction of fast CMOS detectors is moving the field of transmission electron microscopy into the computer science field of big data. Automated data pipelines control the instrument and initial processing steps which imposes more onerous data transfer and archiving requirements. Here we conduct a technical demonstration whereby storage and read/write times are improved 10× at a dose rate of 1 e^?/pix/frame for data from a Gatan K2 direct-detection device by combination of integer decimation and lossless compression. The example project is hosted at github.com/em-MRCZ and released under the BSD license.     

IRAP — A system for the retrieval and analysis of orthopaedic implant data

An interactive computer system for the storage, retrieval and analysis of standardized clinical and material characterization data associated with orthopaedic implants is described. The system consists basically of four independent modules. The essence of the system centers on the cross-referencing capabilities which are virtually unlimited. The system has been designed for use by non-computer trained personnel.     

Drosophila pupal macrophages – A versatile tool for combined ex vivo and in vivo imaging of actin dynamics at high resolution

Molecular understanding of actin dynamics requires a genetically traceable model system that allows live cell imaging together with high-resolution microscopy techniques. Here, we used Drosophila pupal macrophages that combine many advantages of cultured cells with a genetic in vivo model system. Using structured illumination microscopy together with advanced spinning disk confocal microscopy we show that these cells provide a powerful system for single gene analysis. It allows forward genetic screens to characterize the regulatory network controlling cell shape and directed cell migration in a physiological context. We knocked down components regulating lamellipodia formation, including WAVE, single subunits of Arp2/3 complex and CPA, one of the two capping protein subunits and demonstrate the advantages of this model system by imaging mutant macrophages ex vivo as well as in vivo upon laser-induced wounding.     

BIND – An algorithm for loss-less compression of nucleotide sequence data

Recent advances in DNA sequencing technologies have enabled the current generation of life science researchers to probe deeper into the genomic blueprint. The amount of data generated by these technologies has been increasing exponentially since the last decade. Storage, archival and dissemination of such huge data sets require efficient solutions, both from the hardware as well as software perspective. The present paper describes BIND-an algorithm specialized for compressing nucleotide sequence data. By adopting a unique 'block-length' encoding for representing binary data (as a key step), BIND achieves significant compression gains as compared to the widely used general purpose compression algorithms (gzip, bzip2 and lzma). Moreover, in contrast to implementations of existing specialized genomic compression approaches, the implementation of BIND is enabled to handle non-ATGC and lowercase characters. This makes BIND a loss-less compression approach that is suitable for practical use. More importantly, validation results of BIND (with real-world data sets) indicate reasonable speeds of compression and decompression that can be achieved with minimal processor/ memory usage. BIND is available for download at http://metagenomics.atc.tcs.com/compression/BIND. No license is required for academic or non-profit use.