A computational framework to emulate the human perspective in flow cytometric data analysis

Background: In recent years, intense research efforts have focused on developing methods for automated flow cytometric data analysis. However, while designing such applications, little or no attention has been paid to the human perspective that is absolutely central to the manual gating process of identifying and characterizing cell populations. In particular, the assumption of many common techniques that cell populations could be modeled reliably with pre-specified distributions may not hold true in real-life samples, which can have populations of arbitrary shapes and considerable inter-sample variation. <p/>Results: To address this, we developed a new framework flowScape for emulating certain key aspects of the human perspective in analyzing flow data, which we implemented in multiple steps. First, flowScape begins with creating a mathematically rigorous map of the high-dimensional flow data landscape based on dense and sparse regions defined by relative concentrations of events around modes. In the second step, these modal clusters are connected with a global hierarchical structure. This representation allows flowScape to perform ridgeline analysis for both traversing the landscape and isolating cell populations at different levels of resolution. Finally, we extended manual gating with a new capacity for constructing templates that can identify target populations in terms of their relative parameters, as opposed to the more commonly used absolute or physical parameters. This allows flowScape to apply such templates in batch mode for detecting the corresponding populations in a flexible, sample-specific manner. We also demonstrated different applications of our framework to flow data analysis and show its superiority over other analytical methods. <p/>Conclusions: The human perspective, built on top of intuition and experience, is a very important component of flow cytometric data analysis. By emulating some of its approaches and extending these with automation and rigor, flowScape provides a flexible and robust framework for computational cytomics

Model-generated lexical activity predicts graded ERP amplitudes in lexical decision

Recent neurocognitive studies of visual word recognition provide information about neuronal networks correlated with processes involved in lexical access and their time course (e.g., [Holcomb, Ph.J., Grainger J. and O'Rourke, T. (2002). An Electrophysiological Study of the Effects of Orthographic Neighborhood Size on Printed Word Perception, J. of Cogn. Neurosci. 14 938–950; Binder, J.R., McKiernan, K.A., Parsons, M.E., Westbury, C.F., Possing, E.T., Kaufman, J.N. and Buchanan, L. (2003). Neural Correlates of Lexical Access during Visual Word Recognition, J. Cogn. Neurosci. 15 372–393.]). These studies relate the orthographic neighborhood density of letter strings to the amount of global lexical activity in the brain, generated by a hypothetical mental lexicon as speculated in an early paper by [Jacobs, A.M. and Carr, T.H. (1995). Mind mappers and cognitive modelers: Toward cross-fertilization, Behav. Brain. Sci. 18 362–363]. The present study uses model-generated stimuli theoretically eliciting graded global lexical activity and relates this activity to activation of lexical processing networks using event-related potentials (ERPs). The results from a lexical decision task provide evidence for an effect of lexicality around 350 ms post-stimulus and also a graded effect of global lexical activity for nonwords around 500 ms post-stimulus. The data are interpreted as reflecting two different decision processes: an identification process based on local lexical activity underlying the ‘yes’ response to words and a temporal deadline process underlying the ‘no’ response to nonwords based on global lexical activity

Boson-fermion mappings for odd systems from supercoherent states

We extend the formalism whereby boson mappings can be derived from generalized coherent states to boson-fermion mappings for systems with an odd number of fermions. This is accomplished by constructing supercoherent states in terms of both complex and Grassmann variables. In addition to a known mapping for the full so(2$N$+1) algebra, we also uncover some other formal mappings, together with mappings relevant to collective subspaces.Comment: 40 pages, REVTE

Pseudo-Hermitian Hamiltonians, indefinite inner product spaces and their symmetries

We extend the definition of generalized parity $P$, charge-conjugation $C$ and time-reversal $T$ operators to nondiagonalizable pseudo-Hermitian Hamiltonians, and we use these generalized operators to describe the full set of symmetries of a pseudo-Hermitian Hamiltonian according to a fourfold classification. In particular we show that $TP$ and $CTP$ are the generators of the antiunitary symmetries; moreover, a necessary and sufficient condition is provided for a pseudo-Hermitian Hamiltonian $H$ to admit a $P$-reflecting symmetry which generates the $P$-pseudounitary and the $P$-pseudoantiunitary symmetries. Finally, a physical example is considered and some hints on the $P$-unitary evolution of a physical system are also given.Comment: 20 page

Tank-Circuit Assisted Coupling Method for Sympathetic Laser Cooling

We discuss the coupling of the motion of two ion species in separate Penning traps via a common tank circuit. The enhancement of the coupling assisted by the tank circuit is demonstrated by an avoided crossing behavior measurement of the motional modes of two coupled ions. We propose an intermittent laser cooling method for sympathetic cooling and provide a theoretical description. The technique enables tuning of the coupling strength between two ion species in separate traps and thus allows for efficient sympathetic cooling of an arbitrary type of single ion for high-precision Penning-trap experiments

Importing ArrayExpress datasets into R/Bioconductor

Summary:ArrayExpress is one of the largest public repositories of microarray datasets. R/Bioconductor provides a comprehensive suite of microarray analysis and integrative bioinformatics software. However, easy ways for importing datasets from ArrayExpress into R/Bioconductor have been lacking. Here, we present such a tool that is suitable for both interactive and automated use

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