redMaPPer III: A Detailed Comparison of the Planck 2013 and SDSS DR8 RedMaPPer Cluster Catalogs

We compare the Planck Sunyaev-Zeldovich (SZ) cluster sample (PSZ1) to the Sloan Digital Sky Survey (SDSS) redMaPPer catalog, finding that all Planck clusters within the redMaPPer mask and within the redshift range probed by redMaPPer are contained in the redMaPPer cluster catalog. These common clusters define a tight scaling relation in the richness-SZ mass ($\lambda$--$M_{SZ}$) plane, with an intrinsic scatter in richness of $\sigma_{\lambda|M_{SZ}} = 0.266 \pm 0.017$. The corresponding intrinsic scatter in true cluster halo mass at fixed richness is $\approx 21\%$. The regularity of this scaling relation is used to identify failures in both the redMaPPer and Planck cluster catalogs. Of the 245 galaxy clusters in common, we identify three failures in redMaPPer and 36 failures in the PSZ1. Of these, at least 12 are due to clusters whose optical counterpart was correctly identified in the PSZ1, but where the quoted redshift for the optical counterpart in the external data base used in the PSZ1 was incorrect. The failure rates for redMaPPer and the PSZ1 are $1.2\%$ and $14.7\%$ respectively, or 9.8% in the PSZ1 after subtracting the external data base errors. We have further identified 5 PSZ1 sources that suffer from projection effects (multiple rich systems along the line-of-sight of the SZ detection) and 17 new high redshift ($z\gtrsim 0.6$) cluster candidates of varying degrees of confidence. Should all of the high-redshift cluster candidates identified here be confirmed, we will have tripled the number of high redshift Planck clusters in the SDSS region. Our results highlight the power of multi-wavelength observations to identify and characterize systematic errors in galaxy cluster data sets, and clearly establish photometric data both as a robust cluster finding method, and as an important part of defining clean galaxy cluster samples.Comment: comments welcom

Independent Component Separation from incomplete spherical data using wavelets. Application to CMB data analysis

Spectral matching ICA (SMICA) is a source separation method based on covariance matching in Fourier space that was designed to address in a flexible way some of the general problems raised by Cosmic Microwave Background data analysis. However, a common issue in astronomical data analysis is that the observations are unevenly sampled or incomplete maps with missing patches or intentionally masked parts. In addition, many astrophysical emissions are not well modeled as stationary processes over the sky. These effects impair data processing techniques in the spherical harmonics representation. This paper describes a new wavelet transform for spherical maps and proposes an extension of SMICA in this space-scale representation

The XMM-LSS survey: the Class 1 cluster sample over the initial 5 square degrees and its cosmological modelling

We present a sample of 29 galaxy clusters from the XMM-LSS survey over an area of some 5deg2 out to a redshift of z=1.05. The sample clusters, which represent about half of the X-ray clusters identified in the region, follow well defined X-ray selection criteria and are all spectroscopically confirmed. For all clusters, we provide X-ray luminosities and temperatures as well as masses. The cluster distribution peaks around z=0.3 and T =1.5 keV, half of the objects being groups with a temperature below 2 keV. Our L-T(z) relation points toward self-similar evolution, but does not exclude other physically plausible models. Assuming that cluster scaling laws follow self-similar evolution, our number density estimates up to z=1 are compatible with the predictions of the concordance cosmology and with the findings of previous ROSAT surveys. Our well monitored selection function allowed us to demonstrate that the inclusion of selection effects is essential for the correct determination of the evolution of the L-T relation, which may explain the contradictory results from previous studies. Extensive simulations show that extending the survey area to 10deg2 has the potential to exclude the non-evolution hypothesis, but that constraints on more refined ICM models will probably be limited by the large intrinsic dispersion of the L-T relation. We further demonstrate that increasing the dispersion in the scaling laws increases the number of detectable clusters, hence generating further degeneracy [in addition to sigma8, Omega_m, L(M,z) and T(M,z)] in the cosmological interpretation of the cluster number counts. We provide useful empirical formulae for the cluster mass-flux and mass-count-rate relations as well as a comparison between the XMM-LSS mass sensitivity and that of forthcoming SZ surveys.Comment: Accepted for publication by MNRAS. Full resolution images as well as additional cluster data are available through a dedicated database at http://l3sdb.in2p3.fr:8080/l3sdb

Academic team formation as evolving hypergraphs

This paper quantitatively explores the social and socio-semantic patterns of constitution of academic collaboration teams. To this end, we broadly underline two critical features of social networks of knowledge-based collaboration: first, they essentially consist of group-level interactions which call for team-centered approaches. Formally, this induces the use of hypergraphs and n-adic interactions, rather than traditional dyadic frameworks of interaction such as graphs, binding only pairs of agents. Second, we advocate the joint consideration of structural and semantic features, as collaborations are allegedly constrained by both of them. Considering these provisions, we propose a framework which principally enables us to empirically test a series of hypotheses related to academic team formation patterns. In particular, we exhibit and characterize the influence of an implicit group structure driving recurrent team formation processes. On the whole, innovative production does not appear to be correlated with more original teams, while a polarization appears between groups composed of experts only or non-experts only, altogether corresponding to collectives with a high rate of repeated interactions

The XMM-LSS cluster sample and its cosmological applications. Prospects for the XMM next decade

The well defined selection function of the XMM-LSS survey enables a simultaneous modelling of the observed cluster number counts and of the evolution of the L-T relation. We present results pertaining to the first 5 deg2 for a well controlled sample comprising 30 objects: they are compatible with the WMAP3 parameter set along with cluster self-similar evolution. Extending such a survey to 200 deg2 would (1) allow discriminating between the major scenarios of the cluster L-T evolution and (2) provide a unique self-sufficient determination of sigma8 and Gamma with an accuracy of ~ 5% and 10% respectively, when adding mass information from weak lensing and S-Z observations.Comment: Proceedings of the "XMM-Newton: the next decade", to appear in Astronomische Nachrichte

Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7×10-8, HR = 1.14, 95% CI: 1.09-1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4×10-8, HR = 1.27, 95% CI: 1.17-1.38) and 4q32.3 (rs4691139, P = 3.4×10-8, HR = 1.20, 95% CI: 1.17-1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific associat

An original phylogenetic approach identified mitochondrial haplogroup T1a1 as inversely associated with breast cancer risk in BRCA2 mutation carriers

Introduction: Individuals carrying pathogenic mutations in the BRCA1 and BRCA2 genes have a high lifetime risk of breast cancer. BRCA1 and BRCA2 are involved in DNA double-strand break repair, DNA alterations that can be caused by exposure to reactive oxygen species, a main source of which are mitochondria. Mitochondrial genome variations affect electron transport chain efficiency and reactive oxygen species production. Individuals with different mitochondrial haplogroups differ in their metabolism and sensitivity to oxidative stress. Variability in mitochondrial genetic background can alter reactive oxygen species production, leading to cancer risk. In the present study, we tested the hypothesis that mitochondrial haplogroups modify breast cancer risk in BRCA1/2 mutation carriers. Methods: We genotyped 22,214 (11,421 affected, 10,793 unaffected) mutation carriers belonging to the Consortium of Investigators of Modifiers of BRCA1/2 for 129 mitochondrial polymorphisms using the iCOGS array. Haplogroup inference and association detection were performed using a phylogenetic approach. ALTree was applied to explore the reference mitochondrial evolutionary tree and detect subclades enriched in affected or unaffected individuals. Results: We discovered that subclade T1a1 was depleted in affected BRCA2 mutation carriers compared with the rest of clade T (hazard ratio (HR) = 0.55; 95% confidence interval (CI), 0.34 to 0.88; P = 0.01). Compared with the most frequent haplogroup in the general population (that is, H and T clades), the T1a1 haplogroup has a HR of 0.62 (95% CI, 0.40 to 0.95; P = 0.03). We also identified three potential susceptibility loci, including G13708A/rs28359178, which has demonstrated an inverse association with familial breast cancer risk. Conclusions: This study illustrates how original approaches such as the phylogeny-based method we used can empower classical molecular epidemiological studies aimed at identifying association or risk modification effects.Peer reviewe

Evidence for SMAD3 as a modifier of breast cancer risk in BRCA2 mutation carriers

Abstract Introduction Current attempts to identify genetic modifiers of BRCA1 and BRCA2 associated risk have focused on a candidate gene approach, based on knowledge of gene functions, or the development of large genome-wide association studies. In this study, we evaluated 24 SNPs tagged to 14 candidate genes derived through a novel approach that analysed gene expression differences to prioritise candidate modifier genes for association studies. Methods We successfully genotyped 24 SNPs in a cohort of up to 4,724 BRCA1 and 2,693 BRCA2 female mutation carriers from 15 study groups and assessed whether these variants were associated with risk of breast cancer in BRCA1 and BRCA2 mutation carriers. Results SNPs in five of the 14 candidate genes showed evidence of association with breast cancer risk for BRCA1 or BRCA2 carriers (P < 0.05). Notably, the minor alleles of two SNPs (rs7166081 and rs3825977) in high linkage disequilibrium (r 2 = 0.77), located at the SMAD3 locus (15q22), were each associated with increased breast cancer risk for BRCA2 mutation carriers (relative risk = 1.25, 95% confidence interval = 1.07 to 1.45, P trend = 0.004; and relative risk = 1.20, 95% confidence interval = 1.03 to 1.40, P trend = 0.018). Conclusions This study provides evidence that the SMAD3 gene, which encodes a key regulatory protein in the transforming growth factor beta signalling pathway and is known to interact directly with BRCA2, may contribute to increased risk of breast cancer in BRCA2 mutation carriers. This finding suggests that genes with expression associated with BRCA1 and BRCA2 mutation status are enriched for the presence of common genetic modifiers of breast cancer risk in these populations