Stacking weak lensing signals of SZ clusters to constrain cluster physics

We show how to place constraints on cluster physics by stacking the weak lensing signals from multiple clusters found through the Sunyaev-Zeldovich (SZ) effect. For a survey that covers about 200 sq. deg. both in SZ and weak lensing observations, the slope and amplitude of the mass vs. SZ luminosity relation can be measured with few percent error for clusters at z~0.5. This can be used to constrain cluster physics, such as the nature of feedback. For example, we can distinguish a pre-heated model from a model with a decreased accretion rate at more than 5sigma. The power to discriminate among different non-gravitational processes in the ICM becomes even stronger if we use the central Compton parameter y_0, which could allow one to distinguish between models with pre-heating, SN feedback and AGN feedback, for example, at more than 5sigma. Measurement of these scaling relations as a function of redshift makes it possible to directly observe e.g., the evolution of the hot gas in clusters. With this approach the mass-L_SZ relation can be calibrated and its uncertainties can be quantified, leading to a more robust determination of cosmological parameters from clusters surveys. The mass-L_SZ relation calibrated in this way from a small area of the sky can be used to determine masses of SZ clusters from very large SZ-only surveys and is nicely complementary to other techniques proposed in the literature.Comment: Submitted to Ap

ProbCD: enrichment analysis accounting for categorization uncertainty

As in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this field as enrichment (also over-representation or enhancement) analysis. In spite of efforts to create probabilistic annotations, especially in the Gene Ontology context, or to deal with uncertainty in high throughput-based datasets, current enrichment methods largely ignore this probabilistic information since they are mainly based on variants of the Fisher Exact Test. We developed an open-source R package to deal with probabilistic categorical data analysis, ProbCD, that does not require a static contingency table. The contingency table for
the enrichment problem is built using the expectation of a Bernoulli Scheme stochastic process given the categorization probabilities. An on-line interface was created to allow usage by non-programmers and is available at: http://xerad.systemsbiology.net/ProbCD/. We present an analysis framework and software tools to address the issue of uncertainty in categorical data analysis. In particular, concerning the enrichment analysis, ProbCD can accommodate: (i) the stochastic nature of the high-throughput experimental techniques and (ii) probabilistic gene annotation

Glutamate 301 of the mouse gonadotropin-releasing hormone receptor confers specificity for arginine 8 of mammalian gonadotropin-releasing hormone

The Arg residue at position 8 of mammalian GnRH is necessary for high affinity binding to mammalian GnRH receptors. This requirement has been postulated to derive from an electrostatic interaction of Arg8 with a negatively charged receptor residue. In order to identify such a residue, 8 conserved acidic residues of the mouse GnRH receptor were mutated to isosteric Asn or Gln. Mutant receptors were tested for decreased preference for Arg8-containing ligands by ligand binding and inositol phosphate production. One of the mutants, in which the Glu301 residue was mutated to Gln, exhibited a 56-fold decrease in apparent affinity for mammalian GnRH. The mutant receptor also exhibited decreased affinity for [Lys8]GnRH, but its affinity for [Gln8]GnRH was unchanged compared with the wild type receptor. The apparent affinity of the mutant receptor for the acidic analogue, [Glu8]GnRH, was increased more than 10-fold. The mutant receptor did not, therefore, distinguish mammalian GnRH from analogues with amino acid substitutions at position 8 as effectively as the wild type receptor. This loss of discrimination was specific for the residue at position 8, because the mutant receptor did distinguish mammalian GnRH from analogues with favorable substitutions at positions 5, 6, and 7. These findings show that Glu301 of the GnRH receptor plays a role in receptor recognition of Arg8 in the ligand and are consistent with an electrostatic interaction between these 2 residues

Smoothing spline primordial power spectrum reconstruction

We reconstruct the shape of the primordial power spectrum (PPS) using a smoothing spline. Our adapted smoothing spline technique provides a complementary method to existing efforts to search for smooth features in the PPS, such as a running spectral index. With this technique we find no significant indication with WMAP first-year data that the PPS deviates from Harrison-Zeldovich and no evidence for loss of power on large scales. We also examine the effect on the cosmological parameters of the additional PPS freedom. Smooth variations in the PPS are not significantly degenerate with other cosmological parameters, but the spline reconstruction greatly increases the errors on the optical depth and baryon fraction.Comment: 12 pages, 10 figures. Accepted to PR

Proteome Profiling of Breast Tumors by Gel Electrophoresis and Nanoscale Electrospray Ionization Mass Spectrometry

We have conducted proteome-wide analysis of fresh surgery specimens derived from breast cancer patients, using an approach that integrates size-based intact protein fractionation, nanoscale liquid separation of peptides, electrospray ion trap mass spectrometry, and bioinformatics. Through this approach, we have acquired a large amount of peptide fragmentation spectra from size-resolved fractions of the proteomes of several breast tumors, tissue peripheral to the tumor, and samples from patients undergoing noncancer surgery. Label-free quantitation was used to generate protein abundance maps for each proteome and perform comparative analyses. The mass spectrometry data revealed distinct qualitative and quantitative patterns distinguishing the tumors from healthy tissue as well as differences between metastatic and non-metastatic human breast cancers including many established and potential novel candidate protein biomarkers. Selected proteins were evaluated by Western blotting using tumors grouped according to histological grade, size, and receptor expression but differing in nodal status. Immunohistochemical analysis of a wide panel of breast tumors was conducted to assess expression in different types of breast cancers and the cellular distribution of the candidate proteins. These experiments provided further insights and an independent validation of the data obtained by mass spectrometry and revealed the potential of this approach for establishing multimodal markers for early metastasis, therapy outcomes, prognosis, and diagnosis in the future. © 2008 American Chemical Society

The acceleration of the universe and the physics behind it

Using a general classification of dark enegy models in four classes, we discuss the complementarity of cosmological observations to tackle down the physics beyond the acceleration of our universe. We discuss the tests distinguishing the four classes and then focus on the dynamics of the perturbations in the Newtonian regime. We also exhibit explicitely models that have identical predictions for a subset of observations.Comment: 18 pages, 18 figure

GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists

<p>Abstract</p> <p>Background</p> <p>Since the inception of the GO annotation project, a variety of tools have been developed that support exploring and searching the GO database. In particular, a variety of tools that perform GO enrichment analysis are currently available. Most of these tools require as input a target set of genes and a background set and seek enrichment in the target set compared to the background set. A few tools also exist that support analyzing ranked lists. The latter typically rely on simulations or on union-bound correction for assigning statistical significance to the results.</p> <p>Results</p> <p><it>GOrilla </it>is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets. This is particularly useful in many typical cases where genomic data may be naturally represented as a ranked list of genes (e.g. by level of expression or of differential expression). <it>GOrilla </it>employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the <it>top </it>of a ranked gene list. Building on a complete theoretical characterization of the underlying distribution, called mHG, <it>GOrilla </it>computes an exact p-value for the observed enrichment, taking threshold multiple testing into account without the need for simulations. This enables rigorous statistical analysis of thousand of genes and thousands of GO terms in order of seconds. The output of the enrichment analysis is visualized as a hierarchical structure, providing a clear view of the relations between enriched GO terms.</p> <p>Conclusion</p> <p><it>GOrilla </it>is an efficient GO analysis tool with unique features that make a useful addition to the existing repertoire of GO enrichment tools. <it>GOrilla</it>'s unique features and advantages over other threshold free enrichment tools include rigorous statistics, fast running time and an effective graphical representation. <it>GOrilla </it>is publicly available at: <url>http://cbl-gorilla.cs.technion.ac.il</url></p

The Atacama Cosmology Telescope: Dynamical Masses and Scaling Relations for a Sample of Massive Sunyaev-Zel'dovich Effect Selected Galaxy Clusters

We present the first dynamical mass estimates and scaling relations for a sample of Sunyaev-Zel'dovich effect (SZE) selected galaxy clusters. The sample consists of 16 massive clusters detected with the Atacama Cosmology Telescope (ACT) over a 455 sq. deg. area of the southern sky. Deep multi-object spectroscopic observations were taken to secure intermediate-resolution (R~700-800) spectra and redshifts for ~60 member galaxies on average per cluster. The dynamical masses M_200c of the clusters have been calculated using simulation-based scaling relations between velocity dispersion and mass. The sample has a median redshift z=0.50 and a median mass M_200c~12e14 Msun/h70 with a lower limit M_200c~6e14 Msun/h70, consistent with the expectations for the ACT southern sky survey. These masses are compared to the ACT SZE properties of the sample, specifically, the match-filtered central SZE amplitude y, the central Compton parameter y0, and the integrated Compton signal Y_200c, which we use to derive SZE-Mass scaling relations. All SZE estimators correlate with dynamical mass with low intrinsic scatter (<~20%), in agreement with numerical simulations. We explore the effects of various systematic effects on these scaling relations, including the correlation between observables and the influence of dynamically disturbed clusters. Using the 3-dimensional information available, we divide the sample into relaxed and disturbed clusters and find that ~50% of the clusters are disturbed. There are hints that disturbed systems might bias the scaling relations but given the current sample sizes these differences are not significant; further studies including more clusters are required to assess the impact of these clusters on the scaling relations.Comment: 15 pages, 4 figures. Accepted for publication in The Astrophysical Journal; matches published version. Full Table 8 with complete spectroscopic member sample available in machine-readable form in the journal site and upon request to C. Sif\'o