[show abstract][hide abstract] ABSTRACT: We present PEER (probabilistic estimation of expression residuals), a software package implementing statistical models that improve the sensitivity and interpretability of genetic associations in population-scale expression data. This approach builds on factor analysis methods that infer broad variance components in the measurements. PEER takes as input transcript profiles and covariates from a set of individuals, and then outputs hidden factors that explain much of the expression variability. Optionally, these factors can be interpreted as pathway or transcription factor activations by providing prior information about which genes are involved in the pathway or targeted by the factor. The inferred factors are used in genetic association analyses. First, they are treated as additional covariates, and are included in the model to increase detection power for mapping expression traits. Second, they are analyzed as phenotypes themselves to understand the causes of global expression variability. PEER extends previous related surrogate variable models and can be implemented within hours on a desktop computer.
[show abstract][hide abstract] ABSTRACT: Active user involvement and customer collaboration are es- sential yet hard to achieve in software development projects. Therefore, tools that eectively support communication and collaboration between customers and developers have a real need. In this paper we describe a requirements management tool, AgileTool, which eectively supports customer collaboration in agile web application development projects. Requirements can be attached directly into web pages under develop- ment by navigating the pages with a browser. AgileTool is a communica- tion platform that improves product quality by facilitating requirements consistency, traceability, and testability.