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

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

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

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

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).

D. R. Bickel, “The strength of statistical evidence for composite hypotheses with an application to multiple comparisons,” Preprint, Ottawa Institute of Systems Biology, COBRA Preprint Series, Article 49, available at tinyurl.com/7yaysp (2008).

The COBRA Preprint Series was selected for the dissemination of the Statomics Lab’s working papers because it offers more flexibility than the other main services for statistical genomics preprints:

• Unlike arXiv, COBRA accepts PDF files generated by LaTeX. Preparing LaTeX source code specifically for a preprint server can require large time investments.
• Unlike Nature Precedings, COBRA does not require authors to irrevocably license their work for commercial reuse. Such licenses might conflict with the interests of some commercial publishers since they allow competitors to distribute the preprints for profit.

Zahra Montazeri and David Bickel developed empiricalBayes, an R software bundle that provides a simple solution to the extreme multiple testing problem. It contains two packages:

• localFDR estimates local false discovery rates given a vector of p-values.
• HighProbability determines which p-values are low enough that their alternative hypotheses can be considered highly probable.

M. Guo, S. Yang, M. Rupe, B. Hu, D. R. Bickel, L. Arthur, and O. Smith, “Genome-wide allele-specific expression analysis using Massively Parallel Signature Sequencing (MPSS) reveals cis- and trans-effects on gene expression in maize hybrid meristem tissue,” Plant Molecular Biology 66, 551-563 (2008).

Related statistical genomics papers

D. R. Bickel, “Correcting the estimated level of differential expression for gene selection bias: Application to a microarray study,” Statistical Applications in Genetics and Molecular Biology 7 (1) 10, http://www.bepress.com/sagmb/vol7/iss1/art10 (2008).

Related statistical genomics papers