RMA with quantile normalization mixes biological signals between different sample groups in microarray data analysis

Quantile normalization (QN) is a technique for microarray data processing and is the default normalization method in the Robust Multi-array Average (RMA) procedure, which was primarily designed for analysing gene expression data from Affymetrix arrays. Given the abundance of Affymetrix microarrays and the popularity of the RMA method, it is crucially important that the normalization procedure is applied appropriately. In this study we carried out simulation experiments and also analysed real microarray data to investigate the suitability of RMA when it is applied to dataset with different groups of biological samples. From our experiments, we showed that RMA with QN does not preserve the biological signal included in each group, but rather it would mix the signals between the groups. We also showed that the Median Polish method in the summarization step of RMA has similar mixing effect. RMA is one of the most widely used methods in microarray data processing and has been applied to a vast volume of data in biomedical research. The problematic behaviour of this method suggests that previous studies employing RMA could have been misadvised or adversely affected. Therefore we think it is crucially important that the research community recognizes the issue and starts to address it. The two core elements of the RMA method, quantile normalization and Median Polish, both have the undesirable effects of mixing biological signals between different sample groups, which can be detrimental to drawing valid biological conclusions and to any subsequent analyses. Based on the evidence presented here and that in the literature, we recommend exercising caution when using RMA as a method of processing microarray gene expression data, particularly in situations where there are likely to be unknown subgroups of samples.

GERMAN WORKS COUNCILS AND THE ANATOMY OF WAGES

Using matched employer-employee data from the German LIAB for 2001, the authors found that German works councils are in general associated with higher earnings, even after accounting for establishment- and worker heterogeneity. Works Council wage premia exceed those of collective bargaining and are higher, in fact, where both institutions are present in the workplace. The authors also found evidence indicating that works councils benefit women relative to men and appear to favor foreign, east-German, and service-sector workers as well. Separate evidence from quantile regressions suggests that the conjunction of works council presence and collective bargaining is important to the narrowing process. In smaller plants even the presence of a works council markup depends on the coexistence of the works council entity With the machinery of collective bargaining.

DNA hypermethylation and DNA hypomethylation is present at different loci in chronic kidney disease

Genetic risk factors for chronic kidney disease (CKD) are being identified through international collaborations. By comparison, epigenetic risk factors for CKD have only recently been considered using population-based approaches. DNA methylation is a major epigenetic modification that is associated with complex diseases, so we investigated methylome-wide loci for association with CKD. A total of 485,577 unique features were evaluated in 255 individuals with CKD (cases) and 152 individuals without evidence of renal disease (controls). Following stringent quality control, raw data were quantile normalized and β values calculated to reflect the methylation status at each site. The difference in methylation status was evaluated between cases and controls with resultant P values adjusted for multiple testing. Genes with significantly increased and decreased levels of DNA methylation were considered for biological relevance by functional enrichment analysis using KEGG pathways in Partek Genomics Suite. Twenty-three genes, where more than one CpG per loci was identified with Padjusted < 10−8, demonstrated significant methylation changes associated with CKD and additional support for these associated loci was sought from published literature. Strong biological candidates for CKD that showed statistically significant differential methylation include CUX1, ELMO1, FKBP5, INHBA-AS1, PTPRN2, and PRKAG2 genes; several genes are differentially methylated in kidney tissue and RNA-seq supports a functional role for differential methylation in ELMO1 and PRKAG2 genes. This study reports the largest, most comprehensive, genome-wide quantitative evaluation of DNA methylation for association with CKD. Evidence confirming methylation sites influence development of CKD would stimulate research to identify epigenetic therapies that might be clinically useful for CKD.

Ecological impacts of invasive alien species along temperature gradients: testing the role of environmental matching

Invasive alien species (IAS) can cause substantive ecological impacts, and the role of temperature in mediating these impacts may become increasingly significant in a changing climate. Habitat conditions and physiological optima offer predictive information for IAS impacts in novel environments. Here, using meta-analysis and laboratory experiments, we tested the hypothesis that the impacts of IAS in the field are inversely correlated with the difference in their ambient and optimal temperatures. A meta-analysis of 29 studies of consumptive impacts of IAS in inland waters revealed that the impacts of fishes and crustaceans are higher at temperatures that more closely match their thermal growth optima. In particular, the maximum impact potential was constrained by increased differences between ambient and optimal temperatures, as indicated by the steeper slope of a quantile regression on the upper 25th percentile of impact data compared to that of a weighted linear regression on all data with measured variances. We complemented this study with an experimental analysis of the functional response - the relationship between predation rate and prey supply - of two invasive predators (freshwater mysid shrimp, Hemimysis anomala and Mysis diluviana) across relevant temperature gradients; both of these species have previously been found to exert strong community-level impacts that are corroborated by their functional responses to different prey items. The functional response experiments showed that maximum feeding rates of H. anomala and M. diluviana have distinct peaks near their respective thermal optima. Although variation in impacts may be caused by numerous abiotic or biotic habitat characteristics, both our analyses point to temperature as a key mediator of IAS impact levels in inland waters and suggest that IAS management should prioritize habitats in the invaded range that more closely match the thermal optima of targeted invaders.

Prediction of surface roughness during hard turning of AISI 4340 steel (69 HRC)

In this study, 39 sets of hard turning (HT) experimental trials were performed on a Mori-Seiki SL-25Y (4-axis) computer numerical controlled (CNC) lathe to study the effect of cutting parameters in influencing the machined surface roughness. In all the trials, AISI 4340 steel workpiece (hardened up to 69 HRC) was machined with a commercially available CBN insert (Warren Tooling Limited, UK) under dry conditions. The surface topography of the machined samples was examined by using a white light interferometer and a reconfirmation of measurement was done using a Form Talysurf. The machining outcome was used as an input to develop various regression models to predict the average machined surface roughness on this material. Three regression models - Multiple regression, Random Forest, and Quantile regression were applied to the experimental outcomes. To the best of the authors’ knowledge, this paper is the first to apply Random Forest or Quantile regression techniques to the machining domain. The performance of these models was compared to each other to ascertain how feed, depth of cut, and spindle speed affect surface roughness and finally to obtain a mathematical equation correlating these variables. It was concluded that the random forest regression model is a superior choice over multiple regression models for prediction of surface roughness during machining of AISI 4340 steel (69 HRC).

Still Unequal at Birth: Birth Weight, Socioeconomic Status and Outcomes at Age 9

The prevalence of low birth weight is an important aspect of public health which has been linked to increased risk of infant death, increased cost of care, and a range of later life outcomes. Using data from a new Irish cohort study, I document the relationship between birth weight and socio-economic status. The association of maternal education with birth weight does not appear to be due to the timing of birth or complications during pregnancy, even controlling for a wide range of background characteristics. However, results do suggest intergenerational persistence in the transmission of poor early life conditions. Birth weight predicts a number of outcomes at age 9, including test scores, hospital stays and health. An advantage of the data is that I am able to control for a number of typically unmeasured variables. I determine whether parental investments (as measured by the quality of interaction with the child, parenting style, or school quality) mediate the association between birth weight and later indicators. For test scores, there is evidence of non-linearity, and boys are more adversely affected than girls. I also consider whether there are heterogeneous effects by ability using quantile regression. These results are consistent with a literature which finds that there is a causal relationship between early life conditions and later outcomes.

Shared common variants in prostate cancer and blood lipids

BACKGROUND: Epidemiological and clinical studies suggest comorbidity between prostate cancer (PCA) and cardiovascular disease (CVD) risk factors. However, the relationship between these two phenotypes is still not well understood. Here we sought to identify shared genetic loci between PCA and CVD risk factors.

METHODS: We applied a genetic epidemiology method based on conjunction false discovery rate (FDR) that combines summary statistics from different genome-wide association studies (GWAS), and allows identification of genetic overlap between two phenotypes. We evaluated summary statistics from large, multi-centre GWA studies of PCA (n=50 000) and CVD risk factors (n=200 000) [triglycerides (TG), low-density lipoprotein (LDL) cholesterol and high-density lipoprotein (HDL) cholesterol, systolic blood pressure, body mass index, waist-hip ratio and type 2 diabetes (T2D)]. Enrichment of single nucleotide polymorphisms (SNPs) associated with PCA and CVD risk factors was assessed with conditional quantile-quantile plots and the Anderson-Darling test. Moreover, we pinpointed shared loci using conjunction FDR.

RESULTS: We found the strongest enrichment of P-values in PCA was conditional on LDL and conditional on TG. In contrast, we found only weak enrichment conditional on HDL or conditional on the other traits investigated. Conjunction FDR identified altogether 17 loci; 10 loci were associated with PCA and LDL, 3 loci were associated with PCA and TG and additionally 4 loci were associated with PCA, LDL and TG jointly (conjunction FDR <0.01). For T2D, we detected one locus adjacent to HNF1B.

CONCLUSIONS: We found polygenic overlap between PCA predisposition and blood lipids, in particular LDL and TG, and identified 17 pleiotropic gene loci between PCA and LDL, and PCA and TG, respectively. These findings provide novel pathobiological insights and may have implications for trials using targeting lipid-lowering agents in a prevention or cancer setting.

Modelling the effectiveness of grass buffer strips in managing muddy floods under a changing climate

Muddy floods occur when rainfall generates runoff on agricultural land, detaching and transporting sediment into the surrounding natural and built environment. In the Belgian Loess Belt, muddy floods occur regularly and lead to considerable economic costs associated with damage to property and infrastructure. Mitigation measures designed to manage the problem have been tested in a pilot area within Flanders and were found to be cost-effective within three years. This study assesses whether these mitigation measures will remain effective under a changing climate. To test this, the Water Erosion Prediction Project (WEPP) model was used to examine muddy flooding diagnostics (precipitation, runoff, soil loss and sediment yield) for a case study hillslope in Flanders where grass buffer strips are currently used as a mitigation measure. The model was run for present day conditions and then under 33 future site-specific climate scenarios. These future scenarios were generated from three earth system models driven by four representative concentration pathways and downscaled using quantile mapping and the weather generator CLIGEN. Results reveal that under the majority of future scenarios, muddy flooding diagnostics are projected to increase, mostly as a consequence of large scale precipitation events rather than mean changes. The magnitude of muddy flood events for a given return period is also generally projected to increase. These findings indicate that present day mitigation measures may have a reduced capacity to manage muddy flooding given the changes imposed by a warming climate with an enhanced hydrological cycle. Revisions to the design of existing mitigation measures within existing policy frameworks are considered the most effective way to account for the impacts of climate change in future mitigation planning.