rtracklayer: an R package for interfacing with genome browsers

Summary: The rtracklayer package supports the integration of existing genome browsers with experimental data analyses performed in R. The user may (i) transfer annotation tracks to and from a genome browser and (ii) create and manipulate browser views to focus on a particular set of annotations in a specific genomic region. Currently, the UCSC genome browser is supported

Flow cytometry data standards

<p>Abstract</p> <p>Background</p> <p>Flow cytometry is a widely used analytical technique for examining microscopic particles, such as cells. The Flow Cytometry Standard (FCS) was developed in 1984 for storing flow data and it is supported by all instrument and third party software vendors. However, FCS does not capture the full scope of flow cytometry (FCM)-related data and metadata, and data standards have recently been developed to address this shortcoming.</p> <p>Findings</p> <p>The Data Standards Task Force (DSTF) of the International Society for the Advancement of Cytometry (ISAC) has developed several data standards to complement the raw data encoded in FCS files. Efforts started with the Minimum Information about a Flow Cytometry Experiment, a minimal data reporting standard of details necessary to include when publishing FCM experiments to facilitate third party understanding. MIFlowCyt is now being recommended to authors by publishers as part of manuscript submission, and manuscripts are being checked by reviewers and editors for compliance. Gating-ML was then introduced to capture gating descriptions - an essential part of FCM data analysis describing the selection of cell populations of interest. The Classification Results File Format was developed to accommodate results of the gating process, mostly within the context of automated clustering. Additionally, the Archival Cytometry Standard bundles data with all the other components describing experiments. Here, we introduce these recent standards and provide the very first example of how they can be used to report FCM data including analysis and results in a standardized, computationally exchangeable form.</p> <p>Conclusions</p> <p>Reporting standards and open file formats are essential for scientific collaboration and independent validation. The recently developed FCM data standards are now being incorporated into third party software tools and data repositories, which will ultimately facilitate understanding and data reuse.</p

Ocean carbon sequestration: Particle fragmentation by copepods as a significant unrecognised factor?

Ocean biology helps regulate global climate by fixing atmospheric CO2 and exporting it to deep waters as sinking detrital particles. New observations demonstrate that particle fragmentation is the principal factor controlling the depth to which these particles penetrate the ocean's interior, and hence how long the constituent carbon is sequestered from the atmosphere. The underlying cause is, however, poorly understood. We speculate that small, particle‐associated copepods, which intercept and inadvertently break up sinking particles as they search for attached protistan prey, are the principle agents of fragmentation in the ocean. We explore this idea using a new marine ecosystem model. Results indicate that explicitly representing particle fragmentation by copepods in biogeochemical models offers a step change in our ability to understand the future evolution of biologically‐mediated ocean carbon storage. Our findings highlight the need for improved understanding of the distribution, abundance, ecology and physiology of particle‐associated copepods

Moments of spectral functions: Monte Carlo evaluation and verification

The subject of the present study is the Monte Carlo path-integral evaluation of the moments of spectral functions. Such moments can be computed by formal differentiation of certain estimating functionals that are infinitely-differentiable against time whenever the potential function is arbitrarily smooth. Here, I demonstrate that the numerical differentiation of the estimating functionals can be more successfully implemented by means of pseudospectral methods (e.g., exact differentiation of a Chebyshev polynomial interpolant), which utilize information from the entire interval $(-\beta \hbar / 2, \beta \hbar/2)$. The algorithmic detail that leads to robust numerical approximations is the fact that the path integral action and not the actual estimating functional are interpolated. Although the resulting approximation to the estimating functional is non-linear, the derivatives can be computed from it in a fast and stable way by contour integration in the complex plane, with the help of the Cauchy integral formula (e.g., by Lyness' method). An interesting aspect of the present development is that Hamburger's conditions for a finite sequence of numbers to be a moment sequence provide the necessary and sufficient criteria for the computed data to be compatible with the existence of an inversion algorithm. Finally, the issue of appearance of the sign problem in the computation of moments, albeit in a milder form than for other quantities, is addressed.Comment: 13 pages, 2 figure

ShortRead: a bioconductor package for input, quality assessment and exploration of high-throughput sequence data

Summary: ShortRead is a package for input, quality assessment, manipulation and output of high-throughput sequencing data. ShortRead is provided in the R and Bioconductor environments, allowing ready access to additional facilities for advanced statistical analysis, data transformation, visualization and integration with diverse genomic resources

Tools and collaborative environments for bioinformatics research

Advanced research requires intensive interaction among a multitude of actors, often possessing different expertise and usually working at a distance from each other. The field of collaborative research aims to establish suitable models and technologies to properly support these interactions. In this article, we first present the reasons for an interest of Bioinformatics in this context by also suggesting some research domains that could benefit from collaborative research. We then review the principles and some of the most relevant applications of social networking, with a special attention to networks supporting scientific collaboration, by also highlighting some critical issues, such as identification of users and standardization of formats. We then introduce some systems for collaborative document creation, including wiki systems and tools for ontology development, and review some of the most interesting biological wikis. We also review the principles of Collaborative Development Environments for software and show some examples in Bioinformatics. Finally, we present the principles and some examples of Learning Management Systems. In conclusion, we try to devise some of the goals to be achieved in the short term for the exploitation of these technologies

Data Quality Assessment of Ungated Flow Cytometry Data in High

Background: The recent development of semi-automated techniques for staining and analyzing flow cytometry samples has presented new challenges. Quality control and quality assessment are critical when developing new high throughput technologies and their associated information services. Our experience suggests that significant bottlenecks remain in the development of high throughput flow cytometry methods for data analysis and display. Especially, data quality control and quality assessment are crucial steps in processing and analyzing high throughput flow cytometry data. Methods: We propose a variety of graphical exploratory data analytic tools for exploring ungated flow cytometry data. We have implemented a number of specialized functions and methods in the Bioconductor package rflowcyt. We demonstrate the use of these approaches by investigating two independent sets of high throughput flow cytometry data. Results: We found that graphical representations can reveal substantial non-biological differences in samples. Empirical Cumulative Distribution Function and summary scatterplots were especially useful in the rapid identification of problems not identified by manual review. Conclusions: Graphical exploratory data analytic tools are quick and useful means of assessing data quality. We propose that the described visualizations should be used as quality assessment tools and where possible, be used for quality control

Modelling background intensity in Affymetrix Genechips

DNA microarrays are devices that are able, in principle, to detect and quantify the presence of specific nucleic acid sequences in complex biological mixtures. The measurement consists in detecting fluorescence signals from several spots on the microarray surface onto which different probe sequences are grafted. One of the problems of the data analysis is that the signal contains a noisy background component due to non-specific binding. This paper presents a physical model for background estimation in Affymetrix Genechips. It combines two different approaches. The first is based on the sequence composition, specifically its sequence dependent hybridization affinity. The second is based on the strong correlation of intensities from locations which are the physical neighbors of a specific spot on the chip. Both effects are incorporated in a background functional which contains 24 free parameters, fixed by minimization on a training data set. In all data analyzed the sequence specific parameters, obtained by minimization, are found to strongly correlate with empirically determined stacking free energies for RNA/DNA hybridization in solution. Moreover, there is an overall agreement with experimental background data and we show that the physics-based model proposed in this paper performs on average better than purely statistical approaches for background calculations. The model thus provides an interesting alternative method for background subtraction schemes in Affymetrix Genechips.Comment: 8 pages, 4 figure

Properties of continuous Fourier extension of the discrete cosine transform and its multidimensional generalization

A versatile method is described for the practical computation of the discrete Fourier transforms (DFT) of a continuous function $g(t)$ given by its values $g_{j}$ at the points of a uniform grid $F_{N}$ generated by conjugacy classes of elements of finite adjoint order $N$ in the fundamental region $F$ of compact semisimple Lie groups. The present implementation of the method is for the groups SU(2), when $F$ is reduced to a one-dimensional segment, and for $SU(2)\times ... \times SU(2)$ in multidimensional cases. This simplest case turns out to result in a transform known as discrete cosine transform (DCT), which is often considered to be simply a specific type of the standard DFT. Here we show that the DCT is very different from the standard DFT when the properties of the continuous extensions of these two discrete transforms from the discrete grid points $t_j; j=0,1, ... N$ to all points $t \in F$ are considered. (A) Unlike the continuous extension of the DFT, the continuous extension of (the inverse) DCT, called CEDCT, closely approximates $g(t)$ between the grid points $t_j$. (B) For increasing $N$, the derivative of CEDCT converges to the derivative of $g(t)$. And (C), for CEDCT the principle of locality is valid. Finally, we use the continuous extension of 2-dimensional DCT to illustrate its potential for interpolation, as well as for the data compression of 2D images.Comment: submitted to JMP on April 3, 2003; still waiting for the referee's Repor

Faster disease progression in Parkinson's disease with type 2 diabetes is not associated with increased α-synuclein, tau, amyloid-β or vascular pathology

AIMS: Growing evidence suggests a shared pathogenesis between Parkinson's disease and diabetes although the underlying mechanisms remain unknown. The aim of this study is to evaluate the effect of type 2 diabetes on Parkinson's disease progression and to correlate neuropathological findings to elucidate pathogenic mechanisms. METHODS: In this cohort study, medical records were retrospectively reviewed of cases with pathologically-confirmed Parkinson's disease with and without pre-existing type 2 diabetes. Time to disability milestones (recurrent falls, wheelchair dependence, dementia, and care home placement) and survival were compared to assess disease progression and their risk estimated using Cox hazard regression models. Correlation with pathological data was performed, including quantification of α-synuclein in key brain regions and staging of vascular, Lewy and Alzheimer's pathologies. RESULTS: Patients with PD and diabetes (male 76%; age at death 78.6 ± 6.2 years) developed earlier falls (P < 0.001), wheelchair dependence (P = 0.004), dementia (P < 0.001), care home admission (P < 0.001) and had reduced survival (P < 0.001). Predating diabetes was independently associated with a two to three-fold increase in the risk of disability and death. Neuropathological assessment did not show any differences in global or regional vascular pathology, α-synuclein load in key brain areas, staging of Lewy pathology or Alzheimer's disease pathology. CONCLUSIONS: Pre-existing type 2 diabetes contributes to faster disease progression and reduced survival in Parkinson's disease which is not driven by increased vascular, Lewy or Alzheimer's pathologies. Additional non-specific neurodegeneration related to chronic brain insulin resistance may be involved