Abstract
In this paper we use meta-data packages from the Bioconductor Project to carry out statistical analyses of gene expression data. But would like to note that the potential scope of these applications is much broader and many of the methods described here could be applied to other types of high-throughput data. To provide context we make use of data from an investigation into acute lymphoblastic leukemia.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Camon E., Magrane M., Barrell D., Lee V., Dimmer E., Binns D., Maslen J., Harte N., Lopez R., Apweiler R. (2004). The gene ontology annotation (goa) database: sharing knowledge in uniprot with gene ontology. Nucleic Acids Research 32, D262–D266.
Chiaretti S., Li X., Gentleman R., Vitale A., Vignetti M., Mandelli F., Ritz J., Foa R. (2004). Gene expression profile of adult t-cell acute lymphocytic leukemia identifies distinct subsets of patients with different response to therapy and survival. Blood 103, 2771–2778.
Gentleman R., Temple Lang D. (2003). Statistical analyses and reproducible research.
Irizarry R.A., Hobbs B., Collin F., Beazer-Barclay, Y.D., Antonellis K.J., Scherf U., Speed T.P. (2003). Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4 249–264.
von Heydebreck A., Huber W., Gentleman R. (2004). Differential expression with the bioconductor project. In Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. John Wiley and Sons.
Zhou X., Kao M.-C.J., Wong W.H. (2002). Transitive functional annotation by shortest-path analysis of gene expression data. PNAS 99, 12783–12788.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gentleman, R. (2004). Using Go for Statistical Analyses. In: Antoch, J. (eds) COMPSTAT 2004 — Proceedings in Computational Statistics. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-2656-2_13
Download citation
DOI: https://doi.org/10.1007/978-3-7908-2656-2_13
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1554-2
Online ISBN: 978-3-7908-2656-2
eBook Packages: Springer Book Archive