Pre-processing and differential expression analysis of Agilent microRNA arrays using the AgiMicroRna Bioconductor library

<p>Abstract</p> <p>Background</p> <p>The main research tool for identifying microRNAs involved in specific cellular processes is gene expression profiling using microarray technology. Agilent is one of the major producers of microRNA arrays, and microarray data are commonly analyzed by using R and the functions and packages collected in the Bioconductor project. However, an analytical package that integrates the specific characteristics of microRNA Agilent arrays has been lacking.</p> <p>Results</p> <p>This report presents the new bioinformatic tool <it>AgiMicroRNA </it>for the pre-processing and differential expression analysis of Agilent microRNA array data. The software is implemented in the open-source statistical scripting language R and is integrated in the Bioconductor project (<url>http://www.bioconductor.org</url>) under the GPL license. For the pre-processing of the microRNA signal, <it>AgiMicroRNA </it>incorporates the <it>robust multiarray average algorithm</it>, a method that produces a summary measure of the microRNA expression using a linear model that takes into account the probe affinity effect. To obtain a normalized microRNA signal useful for the statistical analysis, <it>AgiMicroRna </it>offers the possibility of employing either the processed signal estimated by the <it>robust multiarray average algorithm </it>or the processed signal produced by the Agilent image analysis software. The <it>AgiMicroRNA </it>package also incorporates different graphical utilities to assess the quality of the data. <it>AgiMicroRna </it>uses the linear model features implemented in the <it>limma </it>package to assess the differential expression between different experimental conditions and provides links to the <it>miRBase </it>for those microRNAs that have been declared as significant in the statistical analysis.</p> <p>Conclusions</p> <p><it>AgiMicroRna </it>is a rational collection of Bioconductor functions that have been wrapped into specific functions in order to ease and systematize the pre-processing and statistical analysis of Agilent microRNA data. The development of this package contributes to the Bioconductor project filling the gap in microRNA array data analysis.</p

Sperm storage and mating in the deep-sea squid Taningia danae Joubin, 1931 (Oegopsida:Octopoteuthidae)

Spermatangium implantation is reported in the large oceanic squid Taningia danae, based on ten mated females from the stomachs of sperm whales. Implanted spermatangia were located in the mantle, head and neck (on both sides) or above the nuchal cartilage, under the neck collar and were often associated with incisions. These cuts ranged from 30 to 65 mm in length and were probably made by males, using the beak or arm hooks. This is the first time wounds facilitating spermatangium storage have been observed in the internal muscle layers (rather than external, as observed in some other species of squid). The implications of these observations for the mating behavior of the rarely encountered squid T. danae are discussed

Vehicle Systems Panel deliberations

The Vehicle Systems Panel addressed materials and structures technology issues related to launch and space vehicle systems not directly associated with the propulsion or entry systems. The Vehicle Systems Panel was comprised of two subpanels - Expendable Launch Vehicles & Cryotanks (ELVC) and Reusable Vehicles (RV). Tom Bales, LaRC, and Tom Modlin, JSC, chaired the expendable and reusable vehicles subpanels, respectively, and co-chaired the Vehicle Systems Panel. The following four papers are discussed in this section: (1) Net Section components for Weldalite Cryogenic Tanks, by Don Bolstad; (2) Build-up Structures for Cryogenic Tanks and Dry Bay Structural Applications, by Barry Lisagor; (3) Composite Materials Program, by Robert Van Siclen; (4) Shuttle Technology (and M&S Lessons Learned), by Stan Greenberg

Basic Test Framework for the Evaluation of Text Line Segmentation and Text Parameter Extraction

Text line segmentation is an essential stage in off-line optical character recognition (OCR) systems. It is a key because inaccurately segmented text lines will lead to OCR failure. Text line segmentation of handwritten documents is a complex and diverse problem, complicated by the nature of handwriting. Hence, text line segmentation is a leading challenge in handwritten document image processing. Due to inconsistencies in measurement and evaluation of text segmentation algorithm quality, some basic set of measurement methods is required. Currently, there is no commonly accepted one and all algorithm evaluation is custom oriented. In this paper, a basic test framework for the evaluation of text feature extraction algorithms is proposed. This test framework consists of a few experiments primarily linked to text line segmentation, skew rate and reference text line evaluation. Although they are mutually independent, the results obtained are strongly cross linked. In the end, its suitability for different types of letters and languages as well as its adaptability are its main advantages. Thus, the paper presents an efficient evaluation method for text analysis algorithms

Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks

The availability of nitrogen represents a key constraint on carbon cycling in terrestrial ecosystems, and it is largely in this capacity that the role of N in the Earth\u27s climate system has been considered. Despite this, few studies have included continuous variation in plant N status as a driver of broad-scale carbon cycle analyses. This is partly because of uncertainties in how leaf-level physiological relationships scale to whole ecosystems and because methods for regional to continental detection of plant N concentrations have yet to be developed. Here, we show that ecosystem CO2 uptake capacity in temperate and boreal forests scales directly with whole-canopy N concentrations, mirroring a leaf-level trend that has been observed for woody plants worldwide. We further show that both CO2 uptake capacity and canopy N concentration are strongly and positively correlated with shortwave surface albedo. These results suggest that N plays an additional, and overlooked, role in the climate system via its influence on vegetation reflectivity and shortwave surface energy exchange. We also demonstrate that much of the spatial variation in canopy N can be detected by using broad-band satellite sensors, offering a means through which these findings can be applied toward improved application of coupled carbon cycle–climate models

Modelling the spatial distribution of DEM Error

Assessment of a DEM’s quality is usually undertaken by deriving a measure of DEM accuracy – how close the DEM’s elevation values are to the true elevation. Measures such as Root Mean Squared Error and standard deviation of the error are frequently used. These measures summarise elevation errors in a DEM as a single value. A more detailed description of DEM accuracy would allow better understanding of DEM quality and the consequent uncertainty associated with using DEMs in analytical applications. The research presented addresses the limitations of using a single root mean squared error (RMSE) value to represent the uncertainty associated with a DEM by developing a new technique for creating a spatially distributed model of DEM quality – an accuracy surface. The technique is based on the hypothesis that the distribution and scale of elevation error within a DEM are at least partly related to morphometric characteristics of the terrain. The technique involves generating a set of terrain parameters to characterise terrain morphometry and developing regression models to define the relationship between DEM error and morphometric character. The regression models form the basis for creating standard deviation surfaces to represent DEM accuracy. The hypothesis is shown to be true and reliable accuracy surfaces are successfully created. These accuracy surfaces provide more detailed information about DEM accuracy than a single global estimate of RMSE

The influence of the NOD Nss1/Idd5 loci on sialadenitis and gene expression in salivary glands of congenic mice

The nonobese diabetic (NOD) Nss1 and Idd5 loci have been associated with sialadenitis development in mice. In this study the NOD Nss1 and Idd5 loci were backcrossed onto the healthy control strain B10.Q by using the speed congenic breeding strategy, resulting in three congenic strains: B10.Q.Nss1, B10.Q.Nss1/Idd5 heterozygous and B10.Q.Nss1/Idd5 homozygous. We investigated the effects of the Nss1 and Idd5 loci on sialadenitis and gene expression in NOD congenic mice. One submandibular salivary gland from each mouse was used for histological analysis of sialadenitis, whereas the contralateral salivary gland was used for gene expression profiling with the Applied Biosystems Mouse Genome Survey chip v.1.0. The results were validated using quantitative reverse transcriptase PCR. The NOD Nss1 and Idd5 loci had clear influence on the onset and progression of sialadenitis in congenic mice. Double congenic mice exhibited the most severe phenotype. We successfully identified several genes that are located in the NOD congenic regions to be differentially expressed between the congenic strains and the control strain. Several of these were found to be co-regulated, such as Stat1, complement component C1q genes and Tlr12. Also, a vast contingency of interferon-regulated genes (such as Ltb, Irf7 and Irf8) and cytokine and chemokine genes (such as Ccr7 and Ccl19) were differentially expressed between the congenic strains and the control strain. Over-representation of inflammatory signalling pathways was observed among the differentially expressed genes. We have found that the introgression of the NOD loci Nss1 and Idd5 on a healthy background caused sialadenitis in NOD congenic mouse strains, and we propose that genes within these loci are important factors in the pathogenesis. Furthermore, gene expression profiling has revealed several differentially expressed genes within and outside the NOD loci that are similar to genes found to be differentially expressed in patients with Sjögren's syndrome, and as such are interesting candidates for investigation to enhance our understanding of disease mechanisms and to develop future therapies