Comparisons in Gender Wage Differentials and Discrimination between Germany and the United Kingdom

Due to the lack of consistent data, direct and robust comparisons of cross-country labour markets have been virtually impossible. This study uses a new panel data series that controls for inconsistencies, thus overcoming this problem. This study estimates gender wage differentials and gender discrimination in the German and United Kingdom labour markets. Panel estimates are used to identify general wage differences between the two countries, with cross-sectional comparisons undertaken to identify changes that have occurred between 1991 and 1993, that are consistent with known labour market policies. It is found that gender wage differentials are greater in the UK than Germany with employer discrimination against females attributed with the majority of the difference in both countries.

viRome: an R package for the visualization and analysis of viral small RNA sequence datasets

Summary: RNA interference (RNAi) is known to play an important part in defence against viruses in a range of species. Second-generation sequencing technologies allow us to assay these systems and the small RNAs that play a key role with unprecedented depth. However, scientists need access to tools that can condense, analyse and display the resulting data. Here, we present viRome, a package for R that takes aligned sequence data and produces a range of essential plots and reports

CoXpress: differential co-expression in gene expression data

<p>Abstract</p> <p>Background</p> <p>Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find groups of genes that behave similarly across a dataset. However, these methods may miss groups of genes which form differential co-expression patterns under different subsets of experimental conditions. Here we describe coXpress, an R package that allows researchers to identify groups of genes that are differentially co-expressed.</p> <p>Results</p> <p>We have developed coXpress as a means of identifying groups of genes that are differentially co-expressed. The utility of coXpress is demonstrated using two publicly available microarray datasets. Our software identifies several groups of genes that are highly correlated under one set of biologically related experiments, but which show little or no correlation in a second set of experiments. The software uses a re-sampling method to calculate a p-value for each group, and provides several methods for the visualisation of differentially co-expressed genes.</p> <p>Conclusion</p> <p>coXpress can be used to find groups of genes that display differential co-expression patterns in microarray datasets.</p

Assembly of hundreds of novel bacterial genomes from the chicken caecum

BACKGROUND: Chickens are a highly important source of protein for a large proportion of the human population. The caecal microbiota plays a crucial role in chicken nutrition through the production of short-chain fatty acids, nitrogen recycling, and amino acid production. In this study, we sequence DNA from caecal content samples taken from 24 chickens belonging to either a fast or a slower growing breed consuming either a vegetable-only diet or a diet containing fish meal. RESULTS: We utilise 1.6 T of Illumina data to construct 469 draft metagenome-assembled bacterial genomes, including 460 novel strains, 283 novel species, and 42 novel genera. We compare our genomes to data from 9 European Union countries and show that these genomes are abundant within European chicken flocks. We also compare the abundance of our genomes, and the carbohydrate active enzymes they produce, between our chicken groups and demonstrate that there are both breed- and diet-specific microbiomes, as well as an overlapping core microbiome. CONCLUSIONS: This data will form the basis for future studies examining the composition and function of the chicken caecal microbiota

Investigating the impact of database choice on the accuracy of metagenomic read classification for the rumen microbiome

The Roslin Institute forms part of the Royal (Dick) School of Veterinary Studies, University of Edinburgh. This project was supported by the Biotechnology and Biological Sciences Research Council (BBSRC; BB/S006680/1, BB/R015023/1), including institute strategic program grant BBS/E/D/30002276. R.H.S. is supported by an EASTBIO studentship funded by BBSRC (BB/M010996/1). A.W.W. and the Rowett Institute receive core financial support from the Scottish Government Rural and Environmental Sciences and Analytical Services (SG-RESAS). We would like to thank all of those who were involved in creating and publicly sharing both the Hungate Collection data and the RUG data.Peer reviewedPostprin