Improved gene co-expression network quality through expression dataset down-sampling and network aggregation

International audienceLarge-scale gene co-expression networks are an effective methodology to analyze sets of co-expressed genes and discover new gene functions or associations. Distances between genes are estimated according to their expression profiles and are visualized in networks that may be further partitioned to reveal communities of co-expressed genes. Creating expression profiles is now eased by the large amounts of publicly available expression data (microarrays and RNA-seq). Although many distance calculation methods have been intensively compared and reviewed in the past, it is unclear how to proceed when many samples reflecting a wide range of different conditions are available. Should as many samples as possible be integrated into network construction or be partitioned into smaller sets of more related samples? Previous studies have indicated a saturation in network performances to capture known associations once a certain number of samples is included in distance calculations. Here, we examined the influence of sample size on co-expression network construction using microarray and RNA-seq expression data from three plant species. We tested different down-sampling methods and compared network performances in recovering known gene associations to networks obtained from full datasets. We further examined how aggregating networks may help increase this performance by testing six aggregation methods

The influence of adaptation and standardization of the marketing mix on performance: a meta-analysis

This article analyzes the relationship between strategies of standardization and adaptation of the marketing mix and performance in an international context. We carried out a meta-analysis on a sample of 23 studies published between 1992 and 2010. The sample was analyzed based on measures of the effect size (ES) – or the strength of the relation (Wolf, 1986) – between standardization/adaptation and performance. The results suggest the existence of a medium strength (ES ranging from .133 to .209) for the relationship considered. The results support the existence of a positive impact of both marketing mix adaptation and standardization on performance. However, our results suggest that companies should slightly emphasize the marketing mix adaptation (ES mean = .168) instead of standardizing it (ES mean = .134) when entering in a new international market. Results also indicate that, among the adaptation choices, price (ES = .209) should be the first element of the marketing mix to be adapted, followed by promotion (ES = .155), product (ES = .154), and distribution (ES = .141). Finally, we suggest some new research paths, such as the use of quantitative methods to compare degrees of adaptation to be applied to different segments, regions, and sectors, among other suggestions