OPENMENDEL: a cooperative programming project for statistical genetics.

Statistical methods for genome-wide association studies (GWAS) continue to improve. However, the increasing volume and variety of genetic and genomic data make computational speed and ease of data manipulation mandatory in future software. In our view, a collaborative effort of statistical geneticists is required to develop open source software targeted to genetic epidemiology. Our attempt to meet this need is called the OPENMENDEL project (https://openmendel.github.io). It aims to (1) enable interactive and reproducible analyses with informative intermediate results, (2) scale to big data analytics, (3) embrace parallel and distributed computing, (4) adapt to rapid hardware evolution, (5) allow cloud computing, (6) allow integration of varied genetic data types, and (7) foster easy communication between clinicians, geneticists, statisticians, and computer scientists. This article reviews and makes recommendations to the genetic epidemiology community in the context of the OPENMENDEL project.

Fitting First Order Kinetic Models Quickly and Easily.

Kinetic models described by systems of linear differential equations can be fitted to data quickly and easily by taking advantage of the special properties of such systems. The estimation situation can be greatly improved when multiresponse data are available, since one can then automatically determine starting values and better discriminate between rival models.

Expression of interleukin-5- and granulocyte macrophage-colony-stimulating factor-responsive genes in blood and airway eosinophils.

Because interleukin (IL)-5 family cytokines are critical regulators of eosinophil development, recruitment, and activation, this study was initiated to identify proteins induced by these cytokines in eosinophils. Using oligonucleotide microarrays, numerous transcripts were identified as responsive to both IL-5 and granulocyte macrophage-colony-stimulating factor (GM-CSF), but no transcripts were markedly affected by one cytokine and not the other. Expression of several gene products were seen to be increased following in vitro stimulation of human blood eosinophils, including the IL-3 receptor alpha subunit, lymphotoxin beta, Pim-1, and cyclin D3. Given that eosinophils recovered from the bronchoalveolar lavage fluid of allergic patients after antigen challenge are exposed to IL-5 or GM-CSF in the airway prior to isolation, the hypothesis was tested that selected IL-5- and GM-CSF-responsive genes are upregulated in airway eosinophils relative to the expression in blood cells. Airway eosinophils displayed greater cell surface expression of the IL-3 receptor alpha subunit, CD44, CD25, and CD66e, suggesting that these proteins may be markers of eosinophil activation by IL-5 family cytokines in airway eosinophils. Other genes that were induced by both IL-5 and GM-CSF showed protein expression at similar or decreased levels in airway eosinophils relative to their circulating counterparts (i.e., lymphotoxin beta and CD24). These studies have identified several transcriptional targets of IL-5 and GM-CSF in human eosinophils and suggest that a number of protein products are critical to the responsiveness of airway eosinophils.

Bioconductor: open software development for computational biology and bioinformatics.

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples.