Detecting mutations in mixed sample sequencing data using empirical Bayes

We develop statistically based methods to detect single nucleotide DNA mutations in next generation sequencing data. Sequencing generates counts of the number of times each base was observed at hundreds of thousands to billions of genome positions in each sample. Using these counts to detect mutations is challenging because mutations may have very low prevalence and sequencing error rates vary dramatically by genome position. The discreteness of sequencing data also creates a difficult multiple testing problem: current false discovery rate methods are designed for continuous data, and work poorly, if at all, on discrete data. We show that a simple randomization technique lets us use continuous false discovery rate methods on discrete data. Our approach is a useful way to estimate false discovery rates for any collection of discrete test statistics, and is hence not limited to sequencing data. We then use an empirical Bayes model to capture different sources of variation in sequencing error rates. The resulting method outperforms existing detection approaches on example data sets.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS538 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Violation of Bell's inequality in electronic Mach-Zehnder interferometers

We propose a possible setup of testing the Bell's inequality in mesoscopic conductors. The particular implementation uses two coupled electronic Mach-Zehnder interferometers in which electrons are injected into the conductors in the quantum Hall regime. It is shown that the Bell's inequality is violated for an arbitrary coupling strength between the two interferometers.Comment: Submitted to Physica E as a proceeding paper of EP2DS-1

Laboratory Plasma Dynamos, Astrophysical Dynamos, and Magnetic Helicity Evolution

The term ``dynamo'' means different things to the laboratory fusion plasma and astrophysical plasma communities. To alleviate the resulting confusion and to facilitate interdisciplinary progress, we pinpoint conceptual differences and similarities between laboratory plasma dynamos and astrophysical dynamos. We can divide dynamos into three types: 1. magnetically dominated helical dynamos which sustain a large scale magnetic field against resistive decay and drive the magnetic geometry toward the lowest energy state, 2. flow-driven helical dynamos which amplify or sustain large scale magnetic fields in an otherwise turbulent flow, and 3. flow-driven nonhelical dynamos which amplify fields on scales at or below the driving turbulence. We discuss how all three types occur in astrophysics whereas plasma confinement device dynamos are of the first type. Type 3 dynamos requires no magnetic or kinetic helicity of any kind. Focusing on type 1 and 2 dynamos, we show how different limits of a unified set of equations for magnetic helicity evolution reveal both types. We explicitly describe a steady-state example of a type 1 dynamo, and three examples of type 2 dynamos: (i) closed volume and time dependent; (ii) steady-state with open boundaries; (iii) time dependent with open boundaries.Comment: accepted by MNRA

Identification of Insertion Deletion Mutations from Deep Targeted Resequencing

Taking advantage of the deep targeted sequencing capabilities of next generation sequencers, we have developed a novel two step insertion deletion (indel) detection algorithm (IDA) that can determine indels from single read sequences with high computational efficiency and sensitivity when indels are fractionally less compared to wild type reference sequence. First, it identifies candidate indel positions utilizing specific sequence alignment artifacts produced by rapid alignment programs. Second, it confirms the location of the candidate indel by using the Smith-Waterman (SW) algorithm on a restricted subset of Sequence reads. We demonstrate that IDA is applicable to indels of varying sizes from deep targeted sequencing data at low fractions where the indel is diluted by wild type sequence. Our algorithm is useful in detecting indel variants present at variable allelic frequencies such as may occur in heterozygotes and mixed normal-tumor tissue

The integral Novikov conjectures for linear groups containing torsion elements

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135682/1/topo0306.pd

Allele-Specific Copy Number Profiling by Next-Generation DNA Sequencing

The progression and clonal development of tumors often involve amplifications and deletions of genomic DNA. Estimation of allele-specific copy number, which quantifies the number of copies of each allele at each variant loci rather than the total number of chromosome copies, is an important step in the characterization of tumor genomes and the inference of their clonal history. We describe a new method, Falcon, for finding somatic allele-specific copy number changes by next generation sequencing of tumors with matched normals. Falcon is based on a change-point model on a bivariate mixed Binomial process, which explicitly models the copy numbers of the two chromosome haplotypes and corrects for local allele-specific coverage biases. By using the Binomial distribution rather than a normal approximation, Falcon more effectively pools evidence from sites with low coverage. A modified Bayesian information criterion is used to guide model selection for determining the number of copy number events. Falcon is evaluated on in silico spike-in data and applied to the analysis of a pre-malignant colon tumor sample and late-stage colorectal adenocarcinoma from the same individual. The allele-specific copy number estimates obtained by Falcon allows us to draw detailed conclusions regarding the clonal history of the individual\u27s colon cancer

Inhalation of high-concentration hydrogen gas attenuates cognitive deficits in a rat model of asphyxia induced-cardiac arrest.

Cognitive deficits are a devastating neurological outcome seen in survivors of cardiac arrest. We previously reported water electrolysis derived 67% hydrogen gas inhalation has some beneficial effects on short-term outcomes in a rat model of global brain hypoxia-ischemia induced by asphyxia cardiac arrest. In the present study, we further investigated its protective effects in long-term spatial learning memory function using the same animal model. Water electrolysis derived 67% hydrogen gas was either administered 1 hour prior to cardiac arrest for 1 hour and at 1-hour post-resuscitation for 1 hour (pre- & post-treatment) or at 1-hour post-resuscitation for 2 hours (post-treatment). T-maze and Morris water maze were used for hippocampal memory function evaluation at 7 and 14 days post-resuscitation, respectively. Neuronal degeneration within hippocampal Cornu Ammonis 1 (CA1) regions was examined by Fluoro-Jade staining ex vivo. Hippocampal deficits were detected at 7 and 18 days post-resuscitation, with increased neuronal degeneration within hippocampal CA1 regions. Both hydrogen gas treatment regimens significantly improved spatial learning function and attenuated neuronal degeneration within hippocampal CA1 regions at 18 days post-resuscitation. Our findings suggest that water electrolysis derived 67% hydrogen gas may be an effective therapeutic approach for improving cognitive outcomes associated with global brain hypoxia-ischemia following cardiac arrest. The study was approved by the Animal Health and Safety Committees of Loma Linda University, USA (approval number: IACUC #8170006) on March 2, 2017

Proton spin structure and the axial U(1) problem

We emphasise the relation between the spin structure of the proton and the axial U(1) problem. New experiments motivated by the proton spin problem which could shed light on the nature of U(1) symmetry breaking in QCD are discussed.Comment: Invited talk at the Workshop on the Spin Structure of the Proton and Polarized Collider Physics, Trento (July 23-28, 2001), 6 pages, 1 figur