Sublinear Algorithms for Approximating String Compressibility

We raise the question of approximating the compressibility of a string with respect to a fixed compression scheme, in sublinear time. We study this question in detail for two popular lossless compression schemes: run-length encoding (RLE) and a variant of Lempel-Ziv (LZ77), and present sublinear algorithms for approximating compressibility with respect to both schemes. We also give several lower bounds that show that our algorithms for both schemes cannot be improved significantly. Our investigation of LZ77 yields results whose interest goes beyond the initial questions we set out to study. In particular, we prove combinatorial structural lemmas that relate the compressibility of a string with respect to LZ77 to the number of distinct short substrings contained in it (its ℓth subword complexity , for small ℓ). In addition, we show that approximating the compressibility with respect to LZ77 is related to approximating the support size of a distribution.National Science Foundation (U.S.) (Award CCF-1065125)National Science Foundation (U.S.) (Award CCF-0728645)Marie Curie International Reintegration Grant PIRG03-GA-2008-231077Israel Science Foundation (Grant 1147/09)Israel Science Foundation (Grant 1675/09

Genotype-informed estimation of risk of coronary heart disease based on genome-wide association data linked to the electronic medical record

<p>Abstract</p> <p>Background</p> <p>Susceptibility variants identified by genome-wide association studies (GWAS) have modest effect sizes. Whether such variants provide incremental information in assessing risk for common 'complex' diseases is unclear. We investigated whether measured and imputed genotypes from a GWAS dataset linked to the electronic medical record alter estimates of coronary heart disease (CHD) risk.</p> <p>Methods</p> <p>Study participants (<it>n </it>= 1243) had no known cardiovascular disease and were considered to be at high, intermediate, or low 10-year risk of CHD based on the Framingham risk score (FRS) which includes age, sex, total and HDL cholesterol, blood pressure, diabetes, and smoking status. Of twelve SNPs identified in prior GWAS to be associated with CHD, four were genotyped in the participants as part of a GWAS. Genotypes for seven SNPs were imputed from HapMap CEU population using the program MACH. We calculated a multiplex genetic risk score for each patient based on the odds ratios of the susceptibility SNPs and incorporated this into the FRS.</p> <p>Results</p> <p>The mean (SD) number of risk alleles was 12.31 (1.95), range 6-18. The mean (SD) of the weighted genetic risk score was 12.64 (2.05), range 5.75-18.20. The CHD genetic risk score was not correlated with the FRS (<it>P </it>= 0.78). After incorporating the genetic risk score into the FRS, a total of 380 individuals (30.6%) were reclassified into higher-(188) or lower-risk groups (192).</p> <p>Conclusion</p> <p>A genetic risk score based on measured/imputed genotypes at 11 susceptibility SNPs, led to significant reclassification in the 10-y CHD risk categories. Additional prospective studies are needed to assess accuracy and clinical utility of such reclassification.</p

Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals

Background The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglycerides (TG). Results Our analysis consisted of a discovery phase using a merged dataset of five different cohorts (n = 12,853 to n = 16,849 depending on lipid phenotype) and a replication phase with ten independent cohorts totaling up to 36,938 additional samples. Filters are often applied before interaction testing to correct for the burden of testing all pairwise interactions. We used two different filters: 1. A filter that tested only single nucleotide polymorphisms (SNPs) with a main effect of p < 0.001 in a previous association study. 2. A filter that only tested interactions identified by Biofilter 2.0. Pairwise models that reached an interaction significance level of p < 0.001 in the discovery dataset were tested for replication. We identified thirteen SNP-SNP models that were significant in more than one replication cohort after accounting for multiple testing. Conclusions These results may reveal novel insights into the genetic etiology of lipid levels. Furthermore, we developed a pipeline to perform a computationally efficient interaction analysis with multi-cohort replication

A comparison of genomic profiles of complex diseases under different models

Background: Various approaches are being used to predict individual risk to polygenic diseases from data provided by genome-wide association studies. As there are substantial differences between the diseases investigated, the data sets used and the way they are tested, it is difficult to assess which models are more suitable for this task. Results: We compared different approaches for seven complex diseases provided by the Wellcome Trust Case Control Consortium (WTCCC) under a within-study validation approach. Risk models were inferred using a variety of learning machines and assumptions about the underlying genetic model, including a haplotype-based approach with different haplotype lengths and different thresholds in association levels to choose loci as part of the predictive model. In accordance with previous work, our results generally showed low accuracy considering disease heritability and population prevalence. However, the boosting algorithm returned a predictive area under the ROC curve (AUC) of 0.8805 for Type 1 diabetes (T1D) and 0.8087 for rheumatoid arthritis, both clearly over the AUC obtained by other approaches and over 0.75, which is the minimum required for a disease to be successfully tested on a sample at risk, which means that boosting is a promising approach. Its good performance seems to be related to its robustness to redundant data, as in the case of genome-wide data sets due to linkage disequilibrium. Conclusions: In view of our results, the boosting approach may be suitable for modeling individual predisposition to Type 1 diabetes and rheumatoid arthritis based on genome-wide data and should be considered for more in-depth research.This work was supported by the Spanish Secretary of Research, Development and Innovation [TIN2010-20900-C04-1]; the Spanish Health Institute Carlos III [PI13/02714]and [PI13/01527] and the Andalusian Research Program under project P08-TIC-03717 with the help of the European Regional Development Fund (ERDF). The authors are very grateful to the reviewers, as they believe that their comments have helped to substantially improve the quality of the paper

Demonstration of Protein-Based Human Identification Using the Hair Shaft Proteome

YesHuman identification from biological material is largely dependent on the ability to characterize genetic polymorphisms in DNA. Unfortunately, DNA can degrade in the environment, sometimes below the level at which it can be amplified by PCR. Protein however is chemically more robust than DNA and can persist for longer periods. Protein also contains genetic variation in the form of single amino acid polymorphisms. These can be used to infer the status of non-synonymous single nucleotide polymorphism alleles. To demonstrate this, we used mass spectrometry-based shotgun proteomics to characterize hair shaft proteins in 66 European-American subjects. A total of 596 single nucleotide polymorphism alleles were correctly imputed in 32 loci from 22 genes of subjects’ DNA and directly validated using Sanger sequencing. Estimates of the probability of resulting individual non-synonymous single nucleotide polymorphism allelic profiles in the European population, using the product rule, resulted in a maximum power of discrimination of 1 in 12,500. Imputed non-synonymous single nucleotide polymorphism profiles from European–American subjects were considerably less frequent in the African population (maximum likelihood ratio = 11,000). The converse was true for hair shafts collected from an additional 10 subjects with African ancestry, where some profiles were more frequent in the African population. Genetically variant peptides were also identified in hair shaft datasets from six archaeological skeletal remains (up to 260 years old). This study demonstrates that quantifiable measures of identity discrimination and biogeographic background can be obtained from detecting genetically variant peptides in hair shaft protein, including hair from bioarchaeological contexts.The Technology Commercialization Innovation Program (Contracts #121668, #132043) of the Utah Governors Office of Commercial Development, the Scholarship Activitie

Coma hipopotasémico: a propósito de un caso

Introduction: coma is the extreme degradation of consciousness. A syndrome characterized by a loss of vegetative functions, as an expression of acute and severe brain dysfunction.Presentation of the case: a 65-year-old male patient who two years ago commenced showing signs of loss of consciousness for two days In inter-crisis periods the studies did not confirm positive results. He was brought to the emergency room in a state of hyporeflexic coma. All parameters were normal except for a very discrete metabolic alkalosis and severe hypokalemia with 1,3 millimoles of potassium. General measures and complementary examinations were performed. Potassium values were replenished. As the potassium values standardized, a process of consciousness recovery was initiated. It was interpreted as a hypokalemic coma.Conclusions: hypopotassemia is a common imbalance, with repercussions in the different systems; this imbalance can result in alterations of the cardiovascular dynamics, progressive muscle weakness and coma. Therefore, in case of symptoms similar to hypokalemia, it is required to work on its diagnosis and treatment.Introducción: El coma es la máxima degradación del estado de conciencia. Síndrome caracterizado por una pérdida de las funciones de la vida de relación y conservación de las de la vida vegetativa, como expresión de una disfunción cerebral aguda y grave.Presentación del caso: paciente masculino de 65 años de edad que hace dos años comenzó con cuadros de pérdida de conciencia por espacio de dos días. En períodos intercrisis los estudios no arrojaron resultados positivos. Es traído a servicio de urgencia en estado de coma hiporrefléctico. Se tomaron medidas generales y se realizaron complementarios. Todo en parámetros de normalidad excepto por una muy discreta alcalosis metabólica y una hipocaliemia severa con 1,3 mili moles de potasio. Se reponen valores de potasio. En la medida que los valores de potasio se recuperaban se iniciaba un proceso de recuperación de la conciencia. Se interpreta como un coma hipopotasémico.Conclusiones: la hipopotasemia es un desbalance común, con repercusiones en los diferentes sistemas, que puede causar desde alteraciones de la dinámica cardiovascular, debilidad muscular progresiva y coma.  De ahí que ante sintomatologías similares a una hipopotasemia se deba trabajar en su diagnóstico y tratamiento.

Resolvins suppress tumor growth and enhance cancer therapy

National Cancer Institute grants RO1 01CA170549-02 (to D. Panigrahy and C.N. Serhan), ROCA148633-01A4 (to D. Panigrahy), and GM095467 (to C.N. Serhan); the Stop and Shop Pediatric Brain Tumor Fund (to M.W. Kieran); the CJ Buckley Pediatric Brain Tumor Fund (to M.W. Kieran); Alex Lemonade Stand (to M.W. Kieran); Molly’s Magic Wand for Pediatric Brain Tumors (to M.W. Kieran); the Markoff Foundation Art-In-Giving Foundation (to M.W. Kieran); the Kamen Foundation (to M.W. Kieran); Jared Branfman Sunflowers for Life (to M.W.K.); and The Wellcome Trust program 086867/Z/08 (to M. Perretti)