CGHnormaliter: an iterative strategy to enhance normalization of array CGH data with imbalanced aberrations

Background: Array comparative genomic hybridization (aCGH) is a popular technique for detection of genomic copy number imbalances. These play a critical role in the onset of various types of cancer. In the analysis of aCGH data, normalization is deemed a critical pre-processing step. In general, aCGH normalization approaches are similar to those used for gene expression data, albeit both data-types differ inherently. A particular problem with aCGH data is that imbalanced copy numbers lead to improper normalization using conventional methods. Results: In this study we present a novel method, called CGHnormaliter, which addresses this issue by means of an iterative normalization procedure. First, provisory balanced copy numbers are identified and subsequently used for normalization. These two steps are then iterated to refine the normalization. We tested our method on three well-studied tumor-related aCGH datasets with experimentally confirmed copy numbers. Results were compared to a conventional normalization approach and two more recent state-of-the-art aCGH normalization strategies. Our findings show that, compared to these three methods, CGHnormaliter yields a higher specificity and precision in terms of identifying the 'true' copy numbers. Conclusion: We demonstrate that the normalization of aCGH data can be significantly enhanced using an iterative procedure that effectively eliminates the effect of imbalanced copy numbers. This also leads to a more reliable assessment of aberrations. An R-package containing the implementation of CGHnormaliter is available at http://www.ibi.vu.nl/programs/cghnormaliterwww. © 2009 van Houte et al; licensee BioMed Central Ltd

The complete mitogenome of Cylindrus obtusus (Helicidae, Ariantinae) using Illumina next generation sequencing

Animal science

Surface Core Level Shifts of Clean and Oxygen Covered Ru(0001)

We have performed high resolution XPS experiments of the Ru(0001) surface, both clean and covered with well-defined amounts of oxygen up to 1 ML coverage. For the clean surface we detected two distinct components in the Ru 3d_{5/2} core level spectra, for which a definite assignment was made using the high resolution Angle-Scan Photoelectron Diffraction approach. For the p(2x2), p(2x1), (2x2)-3O and (1x1)-O oxygen structures we found Ru 3d_{5/2} core level peaks which are shifted up to 1 eV to higher binding energies. Very good agreement with density functional theory calculations of these Surface Core Level Shifts (SCLS) is reported. The overriding parameter for the resulting Ru SCLSs turns out to be the number of directly coordinated O atoms. Since the calculations permit the separation of initial and final state effects, our results give valuable information for the understanding of bonding and screening at the surface, otherwise not accessible in the measurement of the core level energies alone.Comment: 16 pages including 10 figures. Submitted to Phys. Rev. B. Related publications can be found at http://www.fhi-berlin.mpg.de/th/paper.htm

Direct measurement of the ionization quenching factor of nuclear recoils in germanium in the keV energy range

This article reports the measurement of the ionization quenching factor in germanium for nuclear recoil energies between 0.4 and 6.3 keV$_{nr}$. Precise knowledge of this factor in this energy range is relevant for coherent elastic neutrino-nucleus scattering and low mass dark matter searches with germanium-based detectors. Nuclear recoils were produced in a thin high-purity germanium target with a very low energy threshold via irradiation with monoenergetic neutron beams. The energy dependence of the ionization quenching factor was directly measured via kinematically constrained coincidences with surrounding liquid scintillator based neutron detectors. The systematic uncertainties of the measurements are discussed in detail. With measured quenching factors between 0.16 and 0.23 in the [0.4, 6.3] keV$_{nr}$ energy range, the data are compatible with the Lindhard theory with a parameter $k$ of 0.162 $\pm$ 0.004 (stat+sys)

Towards Reliable Automatic Protein Structure Alignment

A variety of methods have been proposed for structure similarity calculation, which are called structure alignment or superposition. One major shortcoming in current structure alignment algorithms is in their inherent design, which is based on local structure similarity. In this work, we propose a method to incorporate global information in obtaining optimal alignments and superpositions. Our method, when applied to optimizing the TM-score and the GDT score, produces significantly better results than current state-of-the-art protein structure alignment tools. Specifically, if the highest TM-score found by TMalign is lower than (0.6) and the highest TM-score found by one of the tested methods is higher than (0.5), there is a probability of (42%) that TMalign failed to find TM-scores higher than (0.5), while the same probability is reduced to (2%) if our method is used. This could significantly improve the accuracy of fold detection if the cutoff TM-score of (0.5) is used. In addition, existing structure alignment algorithms focus on structure similarity alone and simply ignore other important similarities, such as sequence similarity. Our approach has the capacity to incorporate multiple similarities into the scoring function. Results show that sequence similarity aids in finding high quality protein structure alignments that are more consistent with eye-examined alignments in HOMSTRAD. Even when structure similarity itself fails to find alignments with any consistency with eye-examined alignments, our method remains capable of finding alignments highly similar to, or even identical to, eye-examined alignments.Comment: Peer-reviewed and presented as part of the 13th Workshop on Algorithms in Bioinformatics (WABI2013