Robustly detecting differential expression in RNA sequencing data using observation weights

A popular approach for comparing gene expression levels between (replicated) conditions of RNA sequencing data relies on counting reads that map to features of interest. Within such count-based methods, many flexible and advanced statistical approaches now exist and offer the ability to adjust for covariates (e.g. batch effects). Often, these methods include some sort of ‘sharing of information' across features to improve inferences in small samples. It is important to achieve an appropriate tradeoff between statistical power and protection against outliers. Here, we study the robustness of existing approaches for count-based differential expression analysis and propose a new strategy based on observation weights that can be used within existing frameworks. The results suggest that outliers can have a global effect on differential analyses. We demonstrate the effectiveness of our new approach with real data and simulated data that reflects properties of real datasets (e.g. dispersion-mean trend) and develop an extensible framework for comprehensive testing of current and future methods. In addition, we explore the origin of such outliers, in some cases highlighting additional biological or technical factors within the experiment. Further details can be downloaded from the project website: http://imlspenticton.uzh.ch/robinson_lab/edgeR_robus

Do count-based differential expression methods perform poorly when genes are expressed in only one condition?

A response to 'Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data' by Rapaport F, Khanin R, Liang Y, Pirun M, Krek A, Zumbo P, Mason CE, Socci ND and Betel D in Genome Biology, 2013, 14:R95

Pilot Design for Enhanced Channel Estimation in Doubly Selective Channels

This paper investigates pilot design for enhanced channel estimation in single carrier communication systems over doubly-selective channels (DSC). Our contribution is twofold: first, we propose to use Huffman sequences as pilot clusters with low peak-to-average power ratio (PAPR), yet with good channel estimation performance when periodic pilot placement is adopted; second, we propose a low-complexity pilot placement strategy based on the analysis of the complex-exponential basis expansion model (CE-BEM) of the DSC. The latter leads to improved channel estimation performance with useful insights for pilot placement

Collaborative HRM, climate for cooperation, and employee intra-organizational social ties in high-technology firms in China: A cross-level analysis

Individual social ties have been an important source of competitive advantages for hightech firms in the knowledge economy. However, the existing cross-level studies have mainly investigated the impact of HRM systems on traditional individual attitudinal or behavioral outcomes, and few studies have examined the effect of SHRM on individual social ties. Based on the data collected from 363 knowledge employees working in 64 high-tech firms in China, we examine the cross-level relationships among collaborative HRM practices, climate for cooperation and employee intra-organizational social ties. The hierarchical linear model results show that organizational-level collaborative HRM practices have significant positive effects on the number and strength of individual-level intra-organizational social ties, and the climate for cooperation mediates the positive cross-level relationship between collaborative HRM and individual intra-organizational social ties. This study makes three contributions to the literature. First, with a cross-level model, this study helps us better understand how collaborative HRM acts as an approach to manage individuals’ social capital formation. Second, this study makes contribution to the social network literature by showing how organizational contextual factors (HRM practices and organizational climate) affect employee individual social ties. Third, based on the AMO model, this paper developed a more clear construct and a three-dimension measurement of the collaborative HRM

Aberrant GlyRS-HDAC6 interaction linked to axonal transport deficits in Charcot-Marie-Tooth neuropathy.

Dominant mutations in glycyl-tRNA synthetase (GlyRS) cause a subtype of Charcot-Marie-Tooth neuropathy (CMT2D). Although previous studies have shown that GlyRS mutants aberrantly interact with Nrp1, giving insight into the disease\u27s specific effects on motor neurons, these cannot explain length-dependent axonal degeneration. Here, we report that GlyRS mutants interact aberrantly with HDAC6 and stimulate its deacetylase activity on α-tubulin. A decrease in α-tubulin acetylation and deficits in axonal transport are observed in mice peripheral nerves prior to disease onset. An HDAC6 inhibitor used to restore α-tubulin acetylation rescues axonal transport deficits and improves motor functions of CMT2D mice. These results link the aberrant GlyRS-HDAC6 interaction to CMT2D pathology and suggest HDAC6 as an effective therapeutic target. Moreover, the HDAC6 interaction differs from Nrp1 interaction among GlyRS mutants and correlates with divergent clinical presentations, indicating the existence of multiple and different mechanisms in CMT2D. Nat Commun 2018 Mar 8; 9(1):1007

Robustly detecting differential expression in RNA sequencing data using observation weights

A popular approach for comparing gene expression levels between (replicated) conditions of RNA sequencing data relies on counting reads that map to features of interest. Within such count-based methods, many flexible and advanced statistical approaches now exist and offer the ability to adjust for covariates (e.g. batch effects). Often, these methods include some sort of 'sharing of information' across features to improve inferences in small samples. It is important to achieve an appropriate tradeoff between statistical power and protection against outliers. Here, we study the robustness of existing approaches for count-based differential expression analysis and propose a new strategy based on observation weights that can be used within existing frameworks. The results suggest that outliers can have a global effect on differential analyses. We demonstrate the effectiveness of our new approach with real data and simulated data that reflects properties of real datasets (e.g. dispersion-mean trend) and develop an extensible framework for comprehensive testing of current and future methods. In addition, we explore the origin of such outliers, in some cases highlighting additional biological or technical factors within the experiment. Further details can be downloaded from the project website: http://imlspenticton.uzh.ch/robinson_lab/edgeR_robust/

Additional file 2 of Do count-based differential expression methods perform poorly when genes are expressed in only one condition?

Supplementary figures. This file contains the mentioned supplementary figures. (PDF 712 kb

Common features of regulatory T cell specialization during Th1 responses

CD4+Foxp3+ Treg cells are essential for maintaining self-tolerance and preventing excessive immune responses. In the context of Th1 immune responses, co-expression of the Th1 transcription factor T-bet with Foxp3 is essential for Treg cells to control Th1 responses. T-bet-dependent expression of CXCR3 directs Treg cells to the site of inflammation. However, the suppressive mediators enabling effective control of Th1 responses at this site are unknown. In this study, we determined the signature of CXCR3+ Treg cells arising in Th1 settings and defined universal features of Treg cells in this context using multiple Th1-dominated infection models. Our analysis defined a set of Th1-specific co-inhibitory receptors and cytotoxic molecules that are specifically expressed in Treg cells during Th1 immune responses in mice and humans. Among these, we identified the novel co-inhibitory receptor CD85k as a functional predictor for Treg-mediated suppression specifically of Th1 responses, which could be explored therapeutically for selective immune suppression in autoimmunity