Atom gravimeters and gravitational redshift

In a recent paper, H. Mueller, A. Peters and S. Chu [A precision measurement of the gravitational redshift by the interference of matter waves, Nature 463, 926-929 (2010)] argued that atom interferometry experiments published a decade ago did in fact measure the gravitational redshift on the quantum clock operating at the very high Compton frequency associated with the rest mass of the Caesium atom. In the present Communication we show that this interpretation is incorrect.Comment: 2 pages, Brief Communication appeared in Nature (2 September 2010

A constrained polynomial regression procedure for estimating the local False Discovery Rate

<p>Abstract</p> <p>Background</p> <p>In the context of genomic association studies, for which a large number of statistical tests are performed simultaneously, the local False Discovery Rate (<it>lFDR</it>), which quantifies the evidence of a specific gene association with a clinical or biological variable of interest, is a relevant criterion for taking into account the multiple testing problem. The <it>lFDR </it>not only allows an inference to be made for each gene through its specific value, but also an estimate of Benjamini-Hochberg's False Discovery Rate (<it>FDR</it>) for subsets of genes.</p> <p>Results</p> <p>In the framework of estimating procedures without any distributional assumption under the alternative hypothesis, a new and efficient procedure for estimating the <it>lFDR </it>is described. The results of a simulation study indicated good performances for the proposed estimator in comparison to four published ones. The five different procedures were applied to real datasets.</p> <p>Conclusion</p> <p>A novel and efficient procedure for estimating <it>lFDR </it>was developed and evaluated.</p

Re-sampling strategy to improve the estimation of number of null hypotheses in FDR control under strong correlation structures

<p>Abstract</p> <p>Background</p> <p>When conducting multiple hypothesis tests, it is important to control the number of false positives, or the False Discovery Rate (FDR). However, there is a tradeoff between controlling FDR and maximizing power. Several methods have been proposed, such as the q-value method, to estimate the proportion of true null hypothesis among the tested hypotheses, and use this estimation in the control of FDR. These methods usually depend on the assumption that the test statistics are independent (or only weakly correlated). However, many types of data, for example microarray data, often contain large scale correlation structures. Our objective was to develop methods to control the FDR while maintaining a greater level of power in highly correlated datasets by improving the estimation of the proportion of null hypotheses.</p> <p>Results</p> <p>We showed that when strong correlation exists among the data, which is common in microarray datasets, the estimation of the proportion of null hypotheses could be highly variable resulting in a high level of variation in the FDR. Therefore, we developed a re-sampling strategy to reduce the variation by breaking the correlations between gene expression values, then using a conservative strategy of selecting the upper quartile of the re-sampling estimations to obtain a strong control of FDR.</p> <p>Conclusion</p> <p>With simulation studies and perturbations on actual microarray datasets, our method, compared to competing methods such as q-value, generated slightly biased estimates on the proportion of null hypotheses but with lower mean square errors. When selecting genes with controlling the same FDR level, our methods have on average a significantly lower false discovery rate in exchange for a minor reduction in the power.</p

Combinatorial CRISPR-Cas9 screens for de novo mapping of genetic interactions.

We developed a systematic approach to map human genetic networks by combinatorial CRISPR-Cas9 perturbations coupled to robust analysis of growth kinetics. We targeted all pairs of 73 cancer genes with dual guide RNAs in three cell lines, comprising 141,912 tests of interaction. Numerous therapeutically relevant interactions were identified, and these patterns replicated with combinatorial drugs at 75% precision. From these results, we anticipate that cellular context will be critical to synthetic-lethal therapies

Evaluating Statistical Methods Using Plasmode Data Sets in the Age of Massive Public Databases: An Illustration Using False Discovery Rates

Plasmode is a term coined several years ago to describe data sets that are derived from real data but for which some truth is known. Omic techniques, most especially microarray and genomewide association studies, have catalyzed a new zeitgeist of data sharing that is making data and data sets publicly available on an unprecedented scale. Coupling such data resources with a science of plasmode use would allow statistical methodologists to vet proposed techniques empirically (as opposed to only theoretically) and with data that are by definition realistic and representative. We illustrate the technique of empirical statistics by consideration of a common task when analyzing high dimensional data: the simultaneous testing of hundreds or thousands of hypotheses to determine which, if any, show statistical significance warranting follow-on research. The now-common practice of multiple testing in high dimensional experiment (HDE) settings has generated new methods for detecting statistically significant results. Although such methods have heretofore been subject to comparative performance analysis using simulated data, simulating data that realistically reflect data from an actual HDE remains a challenge. We describe a simulation procedure using actual data from an HDE where some truth regarding parameters of interest is known. We use the procedure to compare estimates for the proportion of true null hypotheses, the false discovery rate (FDR), and a local version of FDR obtained from 15 different statistical methods

Two chemically similar stellar overdensities on opposite sides of the plane of the Galaxy

Our Galaxy is thought to have undergone an active evolutionary history dominated by star formation, the accretion of cold gas, and, in particular, mergers up to 10 gigayear ago. The stellar halo reveals rich fossil evidence of these interactions in the form of stellar streams, substructures, and chemically distinct stellar components. The impact of dwarf galaxy mergers on the content and morphology of the Galactic disk is still being explored. Recent studies have identified kinematically distinct stellar substructures and moving groups, which may have extragalactic origin. However, there is mounting evidence that stellar overdensities at the outer disk/halo interface could have been caused by the interaction of a dwarf galaxy with the disk. Here we report detailed spectroscopic analysis of 14 stars drawn from two stellar overdensities, each lying about 5 kiloparsecs above and below the Galactic plane - locations suggestive of association with the stellar halo. However, we find that the chemical compositions of these stars are almost identical, both within and between these groups, and closely match the abundance patterns of the Milky Way disk stars. This study hence provides compelling evidence that these stars originate from the disk and the overdensities they are part of were created by tidal interactions of the disk with passing or merging dwarf galaxies.Comment: accepted for publication in Natur

Detecting inertial effects with airborne matter-wave interferometry

Inertial sensors relying on atom interferometry offer a breakthrough advance in a variety of applications, such as inertial navigation, gravimetry or ground- and space-based tests of fundamental physics. These instruments require a quiet environment to reach their performance and using them outside the laboratory remains a challenge. Here we report the first operation of an airborne matter-wave accelerometer set up aboard a 0g plane and operating during the standard gravity (1g) and microgravity (0g) phases of the flight. At 1g, the sensor can detect inertial effects more than 300 times weaker than the typical acceleration fluctuations of the aircraft. We describe the improvement of the interferometer sensitivity in 0g, which reaches 2 x 10-4 ms-2 / \surdHz with our current setup. We finally discuss the extension of our method to airborne and spaceborne tests of the Universality of free fall with matter waves.Comment: 7 pages, 6 figures. The final version of this article is available in OPEN access (free) from the editor website at http://www.nature.com/ncomms/journal/v2/n9/full/ncomms1479.htm

A statistical method for excluding non-variable CpG sites in high-throughput DNA methylation profiling

<p>Abstract</p> <p>Background</p> <p>High-throughput DNA methylation arrays are likely to accelerate the pace of methylation biomarker discovery for a wide variety of diseases. A potential problem with a standard set of probes measuring the methylation status of CpG sites across the whole genome is that many sites may not show inter-individual methylation variation among the biosamples for the disease outcome being studied. Inclusion of these so-called "non-variable sites" will increase the risk of false discoveries and reduce statistical power to detect biologically relevant methylation markers.</p> <p>Results</p> <p>We propose a method to estimate the proportion of non-variable CpG sites and eliminate those sites from further analyses. Our method is illustrated using data obtained by hybridizing DNA extracted from the peripheral blood mononuclear cells of 311 samples to an array assaying 1505 CpG sites. Results showed that a large proportion of the CpG sites did not show inter-individual variation in methylation.</p> <p>Conclusions</p> <p>Our method resulted in a substantial improvement in association signals between methylation sites and outcome variables while controlling the false discovery rate at the same level.</p

Oxidative Stress in Zebrafish (Danio rerio) Sperm

Laboratories around the world have produced tens of thousands of mutant and transgenic zebrafish lines. As with mice, maintaining all of these valuable zebrafish genotypes is expensive, risky, and beyond the capacity of even the largest stock centers. Because reducing oxidative stress has become an important aspect of reducing the variability in mouse sperm cryopreservation, we examined whether antioxidants might improve cryopreservation of zebrafish sperm. Four experiments were conducted in this study. First, we used the xanthine-xanthine oxidase (X-XO) system to generate reactive oxygen species (ROS). The X-XO system was capable of producing a stress reaction in zebrafish sperm reducing its sperm motility in a concentration dependent manner (P<0.05). Second, we examined X-XO and the impact of antioxidants on sperm viability, ROS and motility. Catalase (CAT) mitigated stress and maintained viability and sperm motility (P>0.05), whereas superoxide dismutase (SOD) and vitamin E did not (P<0.05). Third, we evaluated ROS in zebrafish spermatozoa during cryopreservation and its effect on viability and motility. Methanol (8%) reduced viability and sperm motility (P<0.05), but the addition of CAT mitigated these effects (P>0.05), producing a mean 2.0 to 2.9-fold increase in post-thaw motility. Fourth, we examined the effect of additional cryoprotectants and CAT on fresh sperm motility. Cryoprotectants, 8% methanol and 10% dimethylacetamide (DMA), reduced the motility over the control value (P<0.5), whereas 10% dimethylformamide (DMF) with or without CAT did not (P>0.05). Zebrafish sperm protocols should be modified to improve the reliability of the cryopreservation process, perhaps using a different cryoprotectant. Regardless, the simple addition of CAT to present-day procedures will significantly improve this process, assuring increased and less variable fertilization success and allowing resource managers to dependably plan how many straws are needed to safely cryopreserve a genetic line