Empirical null conditioning

D. R. Bickel, “Estimating the null distribution for conditional inference and genome-scale screening,” Technical Report, Ottawa Institute of Systems Biology, arXiv.org:0910.0745 (2009). Full preprint

Graduate studies in statistical lipidomics

Scientific breakthroughs from genome-sequencing projects brought the realization that reliable interpretation of the resulting information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Statomics Lab of the Ottawa Institute of Systems Biology (http://www.statomics.com). For the CIHR Training Program in Neurodegenerative Lipidomics, the Statomics Lab seeks a graduate student who will develop novel methods of statistical inference and collaboratively use them to discover or validate changes in lipid concentration.

Intellectual curiosity and high mathematical aptitude are essential, as is the ability to quickly code and debug computer programs. Strong self motivation, good communication skills, and a degree in bioinformatics, computer science, mathematics, physics, statistics, any field of engineering, or an equally quantitative field are also absolutely necessary. The following qualities are desirable but not required: coursework in computer science, numerical methods, numerical analysis, software engineering, statistics, and/or biology; familiarly with BUGS, R, S-PLUS, C, Fortran, and/or LaTeX; experience with UNIX or Linux.

To be considered, send a PDF CV that has your GPA and contact information of two references to dbickel0@uottawa.ca (without the zero) with “statistical lipidomics graduate student” in the Subject line of the message. In the message body, specify the graduate program in which you wish to take courses (either Biochemistry or Mathematics and Statistics) and the degree sought (MSc or PhD). Only those students selected for further consideration will receive a response.

OISB in the news

See Systems Biology in Action on the Ottawa Institute of Systems Biology, home of the Statomics Lab.

Shrinkage estimation vs. testing

Z. Montazeri, C. M. Yanofsky, and D. R. Bickel [the first two authors contributed equally], “Shrinkage estimation of gene expression fold change as an alternative to testing hypotheses of equivalent expression,” Technical Report, Ottawa Institute of Systems Biology, COBRA Preprint Series, Article 60, available at tinyurl.com/mwhnj2 (2009). Full preprint

Statomics the class: Coming this fall

The Department of Mathematics and Statistics of the University of Ottawa offers the following special topics class in the fall of 2009.
Statistical Genomics: MAT 4376/5313 (MATH 6507)

Coherent frequentism

D. R. Bickel, “Coherent frequentism,” Technical Report, Ottawa Institute of Systems Biology, arXiv.org:0907.0139 (2009). Full preprint

Postdoctoral training in Bayesian genomics

Scientific breakthroughs from genome-sequencing projects brought the realization that reliable interpretation of the resulting information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Statistical Inference and Computation in Genomics Laboratory of the Ottawa Institute of Systems Biology. The Statomics Lab (http://www.statomics.com) seeks a postdoctoral fellow who will collaboratively develop and apply Bayesian methods of statistical inference to attack current problems in analyzing transcriptomics, proteomics, metabolomics, lipidomics, and/or genome-wide association data.

A thorough knowledge of Bayesian theory is essential, as is the ability to quickly develop reliable software for approximating posterior distributions using complex models. Strong initiative, excellent communication skills, and reception of a PhD or equivalent doctorate in biostatistics, statistics, or a closely related field within the four years prior to the start date are also absolutely necessary. The following qualities are desirable but not required: expertise in one or more methods of frequentist inference; a working knowledge of biology; familiarly with R, S-PLUS, Mathematica, C, Fortran, and/or LaTeX; experience in a UNIX or Linux environment.

To apply, send a PDF CV that has contact information of three references to dbickel0@uottawa.ca (without the zero), with “Bayesian Genomics” and the year of your graduation or anticipated graduation in the subject field of the message. In the message body, concisely present evidence that you meet each requirement for the position and describe your most significant papers and software packages with summaries of how you contributed to them. All applicants are thanked in advance; only those selected for further consideration will receive a response.

Gene network reconstruction from transcriptional dynamics

D. R. Bickel, Z. Montazeri, P.-C. Hsieh, M. Beatty, S. J. Lawit, and N. J. Bate, “Gene network reconstruction from transcriptional dynamics under kinetic model uncertainty: A case for the second derivative,” Bioinformatics 25, 772-779 (2009).

Open access (PDF) | Supplement & software | Data

Statistics abused

On Probability As a Basis For Action (PDF) is recommended as a corrective for over-emphasizing p-values at the expense of estimated effect sizes.

Fold change estimation versus hypothesis testing

D. R. Bickel and C. M. Yanofsky, “Validation of differential gene expression algorithms: Application comparing fold change estimation to hypothesis testing,” Preprint, Ottawa Institute of Systems Biology, COBRA Preprint Series, Article 50, available at tinyurl.com/bw9jod (2009).