Biomedical subjects

Dana Aeschliman

Publications and source records attributed to Dana Aeschliman.

3 recordsLinked to original sources

PubMed2004

ArrayPipe: a flexible processing pipeline for microarray data.

A number of microarray analysis software packages exist already; however, none combines the user-friendly features of a web-based interface with potential ability to analyse multiple arrays at once using flexible analysis steps. The ArrayPipe web server (freely available at www.pathogenomics.ca/arraypipe) allows the automated application of complex analyses to microarray data which can range from single slides to large data sets including replicates and dye-swaps. It handles output from most commonly used quantification software packages for dual-labelled arrays. Application features range from quality assessment of slides through various data visualizations to multi-step analyses including normalization, detection of differentially expressed genes, andcomparison and highlighting of gene lists. A highly customizable action set-up facilitates unrestricted arrangement of functions, which can be stored as action profiles. A unique combination of web-based and command-line functionality enables comfortable configuration of processes that can be repeatedly applied to large data sets in high throughput. The output consists of reports formatted as standard web pages and tab-delimited lists of calculated values that can be inserted into other analysis programs. Additional features, such as web-based spreadsheet functionality, auto-parallelization and password protection make this a powerful tool in microarray research for individuals and large groups alike.

Gene Expression Profiling↗

PubMed2003

A simple approach to fitting Bayesian survival models.

There has been much recent work on Bayesian approaches to survival analysis, incorporating features such as flexible baseline hazards, time-dependent covariate effects, and random effects. Some of the proposed methods are quite complicated to implement, and we argue that as good or better results can be obtained via simpler methods. In particular, the normal approximation to the log-gamma distribution yields easy and efficient computational methods in the face of simple multivariate normal priors for baseline log-hazards and time-dependent covariate effects. While the basic method applies to piecewise-constant hazards and covariate effects, it is easy to apply importance sampling to consider smoother functions.

Bayes Theorem↗

PubMed2002

Predictors of the risk of mortality in neurofibromatosis 2.

To evaluate clinical and molecular predictors of the risk of mortality in people with neurofibromatosis 2 (NF2), we analyzed the mortality experience of 368 patients from 261 families in the United Kingdom NF2 registry, using the Cox proportional-hazards model and the jackknife method. Age at diagnosis, intracranial meningiomas, and type of treatment center were informative predictors of the risk of mortality. In Cox models, the relative risk of mortality increased 1.13-fold per year decrease in age at diagnosis (95% confidence interval [CI] 1.08-1.18) and was 2.51-fold greater in people with meningiomas compared with those without meningiomas (95% CI 1.38-4.57). The relative risk of mortality in patients treated at specialty centers was 0.34 compared with those treated at nonspecialty centers (95% CI 0.12-0.98). In a separate model, the relative risk of mortality in people with constitutional NF2 missense mutations was very low compared with those with other types of mutations (nonsense or frameshift mutations, splice-site mutations, and large deletions), but the CI could not be well quantified because there was only one death among people with missense mutations. We conclude that age at diagnosis, the strongest single predictor of the risk of mortality, is a useful index for patient counseling and clinical management (as are intracranial meningiomas). To ensure optimal care, we recommend that people with NF2 be referred to specialty treatment centers.

Adolescent↗