Event models for tumor classification with SAGE gene expression data

Serial Analysis of Gene Expression (SAGE) is a relatively new method for monitoring gene expression levels and is expected to contribute significantly to the progress in cancer treatment by enabling a precise and early diagnosis. A promising application of SAGE gene expression data is classification of tumors. In this paper, we build three event models (the multivariate Bernoulli model, the multinomial model and the normalized multinomial model) for SAGE data classification. Both binary classification and multicategory classification are investigated. Experiments on two SAGE datasets show that the multivariate Bernoulli model performs well with small feature sizes, but the multinomial performs better at large feature sizes, while the normalized multinomial performs well with medium feature sizes. The multinomial achieves the highest overall accuracy.

Statistical Procedure For Estimating Grey Seal Pup Production From A Single Census

The variable start and duration of the Grey seal breeding season makes the estimation of total pup production from a single census very difficult. Classifying the count into morphological age classes enables the form and timing of the birth rate curve and estimates of pup mortality rates to be elucidated. A simulation technique is described which enables the duration of each morphological stage to be determined from a series of such classified counts taken over one season. A further statistical technique uses these estimates to calculate the mean timing and duration of the breeding season from a single classified count taken from similar populations in subsequent years. This information allows total pup production to be calculated for any appropriate breeding colony. Some guidance is given as to the optimal timing of that single census which would yield the best estimate of production, although the precise date is not critical to the success of the technique. Results from single census estimates obtained in this way are compared with known production data from more detailed surveys for a number of different colonies.

Consequences of a simulated rapid ocean acidification event for benthic ecosystem processes and functions

Whilst the biological consequences of long-term, gradual changes in acidity associated with the oceanic uptake of atmospheric carbon dioxide (CO2) are increasingly studied, the potential effects of rapid acidification associated with a failure of sub-seabed carbon storage infrastructure have received less attention. This study investigates the effects of severe short-term (8 days) exposure to acidified seawater on infaunal mediation of ecosystem processes (bioirrigation and sediment particle redistribution) and functioning (nutrient concentrations). Following acidification, individuals of Amphiura filiformis exhibited emergent behaviour typical of a stress response, which resulted in altered bioturbation, but limited changes in nutrient cycling. Under acidified conditions, A. filiformis moved to shallower depths within the sediment and the variability in occupancy depth reduced considerably. This study indicated that rapid acidification events may not be lethal to benthic invertebrates, but may result in behavioural changes that could have longer-term implications for species survival, ecosystem structure and functioning.

A new procedure to optimize the selection of groups in a classification tree

Agglomerative cluster analyses encompass many techniques, which have been widely used in various fields of science. In biology, and specifically ecology, datasets are generally highly variable and may contain outliers, which increase the difficulty to identify the number of clusters. Here we present a new criterion to determine statistically the optimal level of partition in a classification tree. The criterion robustness is tested against perturbated data (outliers) using an observation or variable with values randomly generated. The technique, called Random Simulation Test (RST), is tested on (1) the well-known Iris dataset [Fisher, R.A., 1936. The use of multiple measurements in taxonomic problems. Ann. Eugenic. 7, 179–188], (2) simulated data with predetermined numbers of clusters following Milligan and Cooper [Milligan, G.W., Cooper, M.C., 1985. An examination of procedures for determining the number of clusters in a data set. Psychometrika 50, 159–179] and finally (3) is applied on real copepod communities data previously analyzed in Beaugrand et al. [Beaugrand, G., Ibanez, F., Lindley, J.A., Reid, P.C., 2002. Diversity of calanoid copepods in the North Atlantic and adjacent seas: species associations and biogeography. Mar. Ecol. Prog. Ser. 232, 179–195]. The technique is compared to several standard techniques. RST performed generally better than existing algorithms on simulated data and proved to be especially efficient with highly variable datasets.

Genotyping an Emiliania huxleyi (Prymnesiophyceae) bloom event in the North Sea reveals evidence of asexual reproduction

Due to the unprecedented rate at which our climate is changing, the ultimate consequence for many species is likely to be either extinction or migration to an alternate habitat. Certain species might, however, evolve at a rate that could make them resilient to the effects of a rapidly changing environment. This scenario is most likely to apply to species that have large population sizes and rapid generation times, such that the genetic variation required for adaptive evolution can be readily supplied. Emiliania huxleyi (Lohm.) Hay and Mohler (Prymnesiophyceae) is likely to be such a species as it is the most conspicuous extant calcareous phytoplankton species in our oceans with generation times of 1 day−1. Here we report on a validated set of microsatellites, in conjunction with the coccolithophore morphology motif genetic marker, to genotype 93 clonal isolates collected from across the world. Of these, 52 came from a single bloom event in the North Sea collected on the D366 UK Ocean Acidification cruise in June-July 2011. There were 26 multilocus genotypes (MLGs) encountered only once in the North Sea bloom and 8 MLGs encountered twice or up to six times. Each of these repeated MLGs exhibited Psex values of less than 0.05 indicating each repeated MLG was the product of asexual reproduction and not separate meiotic events. In addition, we show that the two most polymorphic microsatellite loci, EHMS37 and P01E05, are reporting on regions likely undergoing rapid genetic drift during asexual reproduction. Despite the small sample size, there were many more repeated genotypes than previously reported for other bloom-forming phytoplankton species, including a previously genotyped E. huxleyi bloom event. This study challenges our current assumption that sex is the predominant mode of reproduction during bloom events. Whilst genetic diversity is high amongst extant populations of E. huxleyi, the root cause for this diversity and ultimate fate of these populations still requires further examination. Nonetheless, we show that certain CMM genotypes are found everywhere; while others appear to have a regional bias.