formatomatic: a program for converting diploid allelic data between common formats for population genetic analysis

There has been a great increase in both the number of population genetic analysis programs and the size of data sets being studied with them. Since the file formats required by the most popular and useful programs are variable, automated reformatting or conversion between them is desirable. formatomatic is an easy to use program that can read allelic data files in genepop , raw (csv ) or convert formats and create data files in nine formats: raw (csv ), arlequin , genepop , immanc /bayesass +, migrate , newhybrids , msvar , baps and structure . Use of formatomatic should greatly reduce time spent reformatting data sets and avoid unnecessary errors.     

PFA: Program for the Quantitative Assessment of Cell Metabolism by Spectral Data Analysis

Assessment of mitochondrial oxidative metabolism has wide-ranging importance, from pharmacokinetic analysis to studies in cell viability and apoptosis. Here we present the Perfusion File Analyzer (PFA) application for the real-time analysis of spectral data to measure cytochrome c reduction, cytochrome a3 reduction, and other parameters important to cellular metabolism, which are collected during tissue perfusion experiments. Our current efforts are focused on quantitating changes in mitochondrial function by normalizing baseline drift of spectral data while addressing two major challenges: (1) a lack of real-time feedback from the system when aiming is compromised, and (2) an inability to adjust calculated data in the event of spectral shift. PFA has been developed to address these issues, and is currently used for quality assessment of human islets prior to clinical transplantation.     

Simulating tick distributions over sub-Saharan Africa: the use of observed and simulated climate surfaces

Aim A broad suit of climate data sets is becoming available for use in predictive species modelling. We compare the efficacy of using interpolated climate surfaces [Center for Resource and Environmental Studies (CRES) and Climate Research Unit (CRU)] or high‐resolution model‐derived climate data [Division of Atmospheric Research limited‐area model (DARLAM)] for predictive species modelling, using tick distributions from sub‐Saharan Africa. Location The analysis is restricted to sub‐Saharan Africa. The study area was subdivided into 3000 grids cells with a resolution of 60 × 60 km. Methods Species distributions were predicted using an established multivariate climate envelope modelling approach and three very different climate data sets. The recorded variance in the climate data sets was quantified by employing omnidirectional variograms. To further compare the interpolated tick distributions that flowed from using three climate data sets, we calculated true positive (TP) predictions, false negative (FN) predictions as well as the proportional overlaps between observed and modelled tick distributions. In addition, the effect of tick data set size on the performance of the climate data sets was evaluated by performing random draws of known tick distribution records without replacement. Results The predicted distributions were consistently wider ranging than the known records when using any of the three climate data sets. However, the proportional overlap between predicted and known distributions varied as follows: for Rhipicephalus appendiculatus Neumann (Acari: Ixodidae), these were 60%, 60% and 70%; for Rhipicephalus longus Neumann (Acari: Ixodidae) 60%, 57% and 75%; for Rhipicephalus zambeziensis Walker, Norval & Corwin (Acari: Ixodidae) 57%, 51% and 62%, and for Rhipicephalus capensis Koch (Acari: Ixodidae) 70%, 60% and 60% using the CRES, CRU and DARLAM climate data sets, respectively. All data sets were sensitive to data size but DARLAM performed better when using smaller species data sets. At a 20% data subsample level, DARLAM was able to capture more than 50% of the known records and captured more than 60% of known records at higher subsample levels. Main conclusions The use of data derived from high‐resolution nested climate models (e.g. DARLAM) provided equal or even better species distribution modelling performance. As the model is dynamic and process based, the output data are available at the modelled resolution, and are not hamstrung by the sampling intensity of observed climate data sets (c. one sample per 30,000 km² for Africa). In addition, when exploring the biodiversity consequences of climate change, these modelled outputs form a more useful basis for comparison with modelled future climate scenarios.     

Analysis of data captured by an on-line image capture system from an analytical ultracentrifuge using schlieren optics

The recent development in this laboratory of an automated data capture system, for refractometric optics on the analytical ultracentrifuge has removed the requirement for tedious and time consuming manual acquisition which had led to a decline in the use of schlieren optics. At the same time this system has increased the amount of data easily available from such an optical system with maintained or increased precision. From the advent of such a system has arisen the need for a package to facilitate the analysis of these data and to extend the range of analytical methods used. Using the improved data sets now available has also enabled us to successfully use methods which have lapsed in popularity over the last two decades. We have also been able to successfully apply radial derivative methods (Bridgman 1942) which have not routinely been applied to the analysis of sedimentation velocity experiments using schlieren optics. In this paper we describe the methods we have so far used to analyse data and present results for previously well defined molecules to demonstrate that the results obtained are reliable. Received: 1 November 1996 / Accepted: 15 January 1997     

Climate and the evolution of skull metrics in man.

Two types of data, anthropometric and gene frequencies, may be used to reconstruct human evolution. Previous research, reconstructing the history of racial differentiation on the basis of gene frequencies, indicated that the major separation between human groups was that between Africans and Europeans on one side and peoples from Australia, East Asia and Americas on the other. A similar attempt by Howells ('73b), based on skull measurements in 17 ancient populations, in agreement with earlier anthropometric data, showed the major separation to be between Africans and Australians on one side and Europeans, Asians and Americans on the other. Climate could be a contributing factor to the observed differences in skull and anthropometric measurements. Howells' data showed high correlations with several climatic indicators. Carrying out the phylogenetic analysis after elimination by linear regression of the effects of climate has resolved to a great extent the discrepancy between anthropometric and gene frequency data.     

Delaying conservation actions for improved knowledge: how long should we wait?

Decisions about where conservation actions are implemented are based on incomplete knowledge about biodiversity. The Protea Atlas is a comprehensive database, containing information collated over a decade. Using this data set in a series of retrospective simulations, we compared the outcome from different scenarios of information gain, and habitat protection and loss, over a 20-year period. We assumed that there was no information on proteas at the beginning of the simulation but knowledge improved each year. Our aim was to find out how much time we should spend collecting data before protecting habitat when there is ongoing loss of habitat. We found that, in this case, surveying for more than 2 years rarely increased the effectiveness of conservation decisions in terms of representation of proteas in protected areas and retention within the landscape. If the delay is too long, it can sometimes be more effective just using a readily available habitat map. These results reveal the opportunity costs of delaying conservation action to improve knowledge.     

Examining and Fine-tuning the Selection of Glycan Compositions with GlyConnect Compozitor

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Highlights

• •New comparative tool to assess the relevance of a glycan composition file to be used in a glycoproteomic study.
• •User-friendly and web-based interface to explore glycoproteomics data.
• •Detection of glycan compositional trends within and across protein(s) or tissues.