Testing for treatment effects on gene ontology

In studies that use DNA arrays to assess changes in gene expression, it is preferable to measure the significance of treatment effects on a group of genes from a pathway or functional category such as gene ontology terms (GO terms, ) because this facilitates the interpretation of effects and may markedly increase significance. A modified meta-analysis method to combine p-values was developed to measure the significance of an overall treatment effect on such functionally-defined groups of genes, taking into account the correlation structure among genes. For hypothesis testing that allows gene expression to change in both directions, p-values are calculated under the null distribution generated by a Monte Carlo method

Designing Toxicogenomics Studies that use DNA Array Technology

Background: Bioassays are routinely used to evaluate the toxicity of test agents. Experimental designs for bioassays are largely encompassed by fixed effects linear models. In toxicogenomics studies where DNA arrays measure mRNA levels, the tissue samples are typically generated in a bioassay. These measurements introduce additional sources of variation, which must be properly managed to obtain valid tests of treatment effects.Results: An analysis of covariance model is developed which combines a fixed-effects linear model for the bioassay with important variance components associated with DNA array measurements. These models can accommodate the dominant characteristics of measurements from DNA arrays, and they account for technical variation associated with normalization, spots, dyes, and batches as well as the biological variation associated with the bioassay. An example illustrates how the model is used to identify valid designs and to compare competing designs.Conclusions: Many toxicogenomics studies are bioassays which measure gene expression using DNA arrays. These studies can be designed and analyzed using standard methods with a few modifications to account for characteristics of array measurements, such as multiple endpoints and normalization. As much as possible, technical variation associated with probes, dyes, and batches are managed by blocking treatments within these sources of variation. An example shows how some practical constraints can be accommodated by this modelling and how it allows one to objectively compare competing designs

Genome-wide estimation of gender differences in the gene expression of human livers: Statistical design and analysis

BACKGROUND: Gender differences in gene expression were estimated in liver samples from 9 males and 9 females. The study tested 31,110 genes for a gender difference using a design that adjusted for sources of variation associated with cDNA arrays, normalization, hybridizations and processing conditions. RESULTS: The genes were split into 2,800 that were clearly expressed (expressed genes) and 28,310 that had expression levels in the background range (not expressed genes). The distribution of p-values from the 'not expressed' group was consistent with no gender differences. The distribution of p-values from the 'expressed' group suggested that 8 % of these genes differed by gender, but the estimated fold-changes (expression in males / expression in females) were small. The largest observed fold-change was 1.55. The 95 % confidence bounds on the estimated fold-changes were less than 1.4 fold for 79.3 %, and few (1.1%) exceed 2-fold. CONCLUSION: Observed gender differences in gene expression were small. When selecting genes with gender differences based upon their p-values, false discovery rates exceed 80 % for any set of genes, essentially making it impossible to identify any specific genes with a gender difference

Approaching disorder-free transport in high-mobility conjugated polymers.

Conjugated polymers enable the production of flexible semiconductor devices that can be processed from solution at low temperatures. Over the past 25 years, device performance has improved greatly as a wide variety of molecular structures have been studied. However, one major limitation has not been overcome; transport properties in polymer films are still limited by pervasive conformational and energetic disorder. This not only limits the rational design of materials with higher performance, but also prevents the study of physical phenomena associated with an extended π-electron delocalization along the polymer backbone. Here we report a comparative transport study of several high-mobility conjugated polymers by field-effect-modulated Seebeck, transistor and sub-bandgap optical absorption measurements. We show that in several of these polymers, most notably in a recently reported, indacenodithiophene-based donor-acceptor copolymer with a near-amorphous microstructure, the charge transport properties approach intrinsic disorder-free limits at which all molecular sites are thermally accessible. Molecular dynamics simulations identify the origin of this long sought-after regime as a planar, torsion-free backbone conformation that is surprisingly resilient to side-chain disorder. Our results provide molecular-design guidelines for 'disorder-free' conjugated polymers.We gratefully acknowledge financial support from the Engineering and Physical Sciences Research Council (EPSRC) through a programme grant (EP/G060738/1) and the Technology Strategy Board (TSB) (PORSCHED project). D. Venkateshvaran acknowledges financial support from the Cambridge Commonwealth Trust through a Cambridge International Scholarship. K. Broch acknowledges post-doctoral fellowship support from the German Research Foundation (DFG). Mateusz Zelazny acknowledges funding from the NanoDTC in Cambridge. The work in Mons was supported by the European Commission / Région Wallonne (FEDER – Smartfilm RF project), the Interuniversity Attraction Pole program of the Belgian Federal Science Policy Office (PAI 7/05), Programme d’Excellence de la Région Wallonne (OPTI2MAT project) and FNRS-FRFC. D.B. and J.C. are FNRS Research Fellows.This is the accepted manuscript. The final version's available from Nature at http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13854.html

Reproducibility of microarray data: a further analysis of microarray quality control (MAQC) data

<p>Abstract</p> <p>Background</p> <p>Many researchers are concerned with the comparability and reliability of microarray gene expression data. Recent completion of the MicroArray Quality Control (MAQC) project provides a unique opportunity to assess reproducibility across multiple sites and the comparability across multiple platforms. The MAQC analysis presented for the conclusion of inter- and intra-platform comparability/reproducibility of microarray gene expression measurements is inadequate. We evaluate the reproducibility/comparability of the MAQC data for 12901 common genes in four titration samples generated from five high-density one-color microarray platforms and the TaqMan technology. We discuss some of the problems with the use of correlation coefficient as metric to evaluate the inter- and intra-platform reproducibility and the percent of overlapping genes (POG) as a measure for evaluation of a gene selection procedure by MAQC.</p> <p>Results</p> <p>A total of 293 arrays were used in the intra- and inter-platform analysis. A hierarchical cluster analysis shows distinct differences in the measured intensities among the five platforms. A number of genes show a small fold-change in one platform and a large fold-change in another platform, even though the correlations between platforms are high. An analysis of variance shows thirty percent of gene expressions of the samples show inconsistent patterns across the five platforms. We illustrated that POG does not reflect the accuracy of a selected gene list. A non-overlapping gene can be truly differentially expressed with a stringent cut, and an overlapping gene can be non-differentially expressed with non-stringent cutoff. In addition, POG is an unusable selection criterion. POG can increase or decrease irregularly as cutoff changes; there is no criterion to determine a cutoff so that POG is optimized.</p> <p>Conclusion</p> <p>Using various statistical methods we demonstrate that there are differences in the intensities measured by different platforms and different sites within platform. Within each platform, the patterns of expression are generally consistent, but there is site-by-site variability. Evaluation of data analysis methods for use in regulatory decision should take no treatment effect into consideration, when there is no treatment effect, "a fold-change cutoff with a non-stringent p-value cutoff" could result in 100% false positive error selection.</p

Childhood cancer in the offspring born in 1921–1984 to US radiologic technologists

We examined the risk of childhood cancer (<20 years) among 105 950 offspring born in 1921–1984 to US radiologic technologist (USRT) cohort members. Parental occupational in utero and preconception ionising radiation (IR) testis or ovary doses were estimated from work history data, badge dose data, and literature doses (the latter doses before 1960). Female and male RTs reported a total of 111 and 34 haematopoietic malignancies and 115 and 34 solid tumours, respectively, in their offspring. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional hazards regression. Leukaemia (n=63) and solid tumours (n=115) in offspring were not associated with maternal in utero or preconception radiation exposure. Risks for lymphoma (n=44) in those with estimated doses of <0.2, 0.2–1.0, and >1.0 mGy vs no exposure were non-significantly elevated with HRs of 2.3, 1.8, and 2.7. Paternal preconception exposure to estimated cumulative doses above the 95th percentile (⩾82 mGy, n=6 cases) was associated with a non-significant risk of childhood cancer of 1.8 (95% CI 0.7–4.6). In conclusion, we found no convincing evidence of an increased risk of childhood cancer in the offspring of RTs in association with parental occupational radiation exposure

Electrode Materials, Thermal Annealing Sequences, and Lateral/Vertical Phase Separation of Polymer Solar Cells from Multiscale Molecular Simulations

The nanomorphologies of the bulk heterojunction (BHJ) layer of polymer solar cells are extremely sensitive to the electrode materials and thermal annealing conditions. In this work, the correlations of electrode materials, thermal annealing sequences, and resultant BHJ nanomorphological details of P3HT:PCBM BHJ polymer solar cell are studied by a series of large-scale, coarse-grained (CG) molecular simulations of system comprised of PEDOT:PSS/P3HT:PCBM/Al layers. Simulations are performed for various configurations of electrode materials as well as processing temperature. The complex CG molecular data are characterized using a novel extension of our graph-based framework to quantify morphology and establish a link between morphology and processing conditions. Our analysis indicates that vertical phase segregation of P3HT:PCBM blend strongly depends on the electrode material and thermal annealing schedule. A thin P3HT-rich film is formed on the top, regardless of bottom electrode material, when the BHJ layer is exposed to the free surface during thermal annealing. In addition, preferential segregation of P3HT chains and PCBM molecules toward PEDOT:PSS and Al electrodes, respectively, is observed. Detailed morphology analysis indicated that, surprisingly, vertical phase segregation does not affect the connectivity of donor/acceptor domains with respective electrodes. However, the formation of P3HT/PCBM depletion zones next to the P3HT/PCBM-rich zones can be a potential bottleneck for electron/hole transport due to increase in transport pathway length. Analysis in terms of fraction of intra- and interchain charge transports revealed that processing schedule affects the average vertical orientation of polymer chains, which may be crucial for enhanced charge transport, nongeminate recombination, and charge collection. The present study establishes a more detailed link between processing and morphology by combining multiscale molecular simulation framework with an extensive morphology feature analysis, providing a quantitative means for process optimization