The Color-Flavor Transformation and Lattice QCD

We present the color-flavor transformation for gauge group SU(N_c) and discuss its application to lattice QCD.Comment: 6 pages, Lattice2002(theoretical), typo in Ref.[1] correcte

(1+1)-dimensional Baryons from the SU(N) Color-Flavor Transformation

The color-flavor transformation, an identity that connects two integrals, each of which is over one of a dual pair of Lie groups acting in the fermionic Fock space, is extended to the case of the special unitary group. Using this extension, a toy model of lattice QCD is studied: N_f species of spinless fermions interacting with strongly coupled SU(N_c) lattice gauge fields in 1+1 dimensions. The color-flavor transformed theory is expressed in terms of gauge singlets, the meson fields, organized into sectors distinguished by the distribution of baryonic flux. A comprehensive analytical and numerical search is made for saddle-point configurations of the meson fields, with various topological charges, in the vacuum and single-baryon sectors. Two definitions of the static baryon on the square lattice, straight and zigzag, are investigated. The masses of the baryonic states are estimated using the saddle-point approximation for large N_c.Comment: LateX, 53 pages, 13 figure

Robust detection and verification of linear relationships to generate metabolic networks using estimates of technical errors

<p>Abstract</p> <p>Background</p> <p>The size and magnitude of the metabolome, the ratio between individual metabolites and the response of metabolic networks is controlled by multiple cellular factors. A tight control over metabolite ratios will be reflected by a linear relationship of pairs of metabolite due to the flexibility of metabolic pathways. Hence, unbiased detection and validation of linear metabolic variance can be interpreted in terms of biological control. For robust analyses, criteria for rejecting or accepting linearities need to be developed despite technical measurement errors. The entirety of all pair wise linear metabolic relationships then yields insights into the network of cellular regulation.</p> <p>Results</p> <p>The Bayesian law was applied for detecting linearities that are validated by explaining the residues by the degree of technical measurement errors. Test statistics were developed and the algorithm was tested on simulated data using 3–150 samples and 0–100% technical error. Under the null hypothesis of the existence of a linear relationship, type I errors remained below 5% for data sets consisting of more than four samples, whereas the type II error rate quickly raised with increasing technical errors. Conversely, a filter was developed to balance the error rates in the opposite direction. A minimum of 20 biological replicates is recommended if technical errors remain below 20% relative standard deviation and if thresholds for false error rates are acceptable at less than 5%. The algorithm was proven to be robust against outliers, unlike Pearson's correlations.</p> <p>Conclusion</p> <p>The algorithm facilitates finding linear relationships in complex datasets, which is radically different from estimating linearity parameters from given linear relationships. Without filter, it provides high sensitivity and fair specificity. If the filter is activated, high specificity but only fair sensitivity is yielded. Total error rates are more favorable with deactivated filters, and hence, metabolomic networks should be generated without the filter. In addition, Bayesian likelihoods facilitate the detection of multiple linear dependencies between two variables. This property of the algorithm enables its use as a discovery tool and to generate novel hypotheses of the existence of otherwise hidden biological factors.</p

Ioncopy: an R Shiny app to call copy number alterations in targeted NGS data

Background: Somatic copy number alterations (CNAs) contribute to the clinically targetable aberrations in the tumor genome. For both routine diagnostics and biomarkers research, CNA analysis in a single assay together with somatic mutations is highly desirable. Results: Ioncopy is a validated method and easy-to-use software for CNA calling from targeted NGS data. Copy number and significance of CNA are estimated for each gene in each sample. Copy number gains and losses are called after multiple testing corrections controlling FWER or FDR. Conclusions: Ioncopy facilitates calling of CNAs in a cohort of tumors tissues with or without using normal (germline) DNA controls

The Color--Flavor Transformation of induced QCD

The Zirnbauer's color-flavor transformation is applied to the $U(N_c)$ lattice gauge model, in which the gauge theory is induced by a heavy chiral scalar field sitting on lattice sites. The flavor degrees of freedom can encompass several `generations' of the auxiliary field, and for each generation, remaining indices are associated with the elementary plaquettes touching the lattice site. The effective, color-flavor transformed theory is expressed in terms of gauge singlet matrix fields carried by lattice links. The effective action is analyzed for a hypercubic lattice in arbitrary dimension. We investigate the corresponding d=2 and d=3 dual lattices. The saddle points equations of the model in the large-$N_c$ limit are discussed.Comment: 24 pages, 6 figures, to appear in Int. J. Mod. Phys.