‘Gene shaving’ as a method for identifying distinct sets of genes with similar expression patterns

Background: Large gene expression studies, such as those conducted using DNA arrays, often provide millions of different pieces of data. To address the problem of analyzing such data, we describe a statistical method, which we have called ‘gene shaving’. The method identifies subsets of genes with coherent expression patterns and large variation across conditions. Gene shaving differs from hierarchical clustering and other widely used methods for analyzing gene expression studies in that genes may belong to more than one cluster, and the clustering may be supervised by an outcome measure. The technique can be ‘unsupervised’, that is, the genes and samples are treated as unlabeled, or partially or fully supervised by using known properties of the genes or samples to assist in finding meaningful groupings. Results: We illustrate the use of the gene shaving method to analyze gene expression measurements made on samples from patients with diffuse large B-cell lymphoma. The method identifies a small cluster of genes whose expression is highly predictive of survival. Conclusions: The gene shaving method is a potentially useful tool for exploration of gene expression data and identification of interesting clusters of genes worth further investigation.

Provisioning Strategies of Antarctic Fur Seals and Chinstrap Penguins Produce Different Responses to Distribution of Common Prey and Habitat

Central-place foragers that must return to a breeding site to deliver food to offspring are faced with trade-offs between prey patch quality and distance from the colony. Among colonial animals, pinnipeds and seabirds may have different provisioning strategies, due to differences in their ability to travel and store energy. We compared the foraging areas of lactating Antarctic fur seals and chinstrap penguins breeding at Seal Island, Antarctica, to investigate whether they responded differently to the distribution of their prey (Antarctic krill and myctophid fish) and spatial heterogeneity in their habitat. Dense krill concentrations occurred in the shelf region near the colony. However, only brooding penguins, which are expected to be time-minimizers because they must return frequently with whole food for their chicks, foraged mainly in this proximal shelf region. Lactating fur seals and incubating penguins, which can make longer trips to increase energy gain per trip, and so are expected to be energy-maximizers, foraged in the more distant (>20 km from the island) slope and oceanic regions. The shelf region was characterized by more abundant, but lower-energy-content immature krill, whereas the slope and oceanic regions had less abundant but higher-energy-content gravid krill, as well as high-energy-content myctophids. Furthermore, krill in the shelf region undertook diurnal vertical migration, whereas those in the slope and oceanic regions stayed near the surface throughout the day, which may enhance the capture rate for visual predators. Therefore, we sug- gest that the energy-maximizers foraged in distant, but potentially more profitable feeding regions, while the time-minimizers foraged in closer, but potentially less profitable regions. Thus, time and energy constraints derived from different provisioning strategies may result in sympatric colonial predator species using different foraging areas, and as a result, some central-place foragers use sub- optimal foraging habitats, in terms of the quality or quantity of available prey.