Document Type

Article

Publication Date

2005

Abstract

Massive amounts of data are being generated in an effort to represent for the brain the expression of all genes at cellular resolution. Critical to exploiting this effort is the ability to place these data into a common frame of reference. Here we have developed a computational method for annotating gene expression patterns in the context of a digital atlas to facilitate custom user queries and comparisons of this type of data. This procedure has been applied to 200 genes in the postnatal mouse brain. As an illustration of utility, we identify candidate genes that may be related to Parkinson disease by using the expression of a dopamine transporter in the substantia nigra as a search query pattern. In addition, we discover that transcription factor Rorb is down-regulated in the barrelless mutant relative to control mice by quantitative comparison of expression patterns in layer IV somatosensory cortex. The semi-automated annotation method developed here is applicable to a broad spectrum of complex tissues and data modalities.

Publication Title

PLoS Computational Biology

Volume

1

Issue

4

First Page

289

Last Page

296

Comments

This article was published in PLoS Computational Biology, Volume 1, Issue 4, Pages 289-296.

The published version is available at http://dx.doi.org/10.1371/journal.pcbi.0010041.

Copyright © 2005 Carson et al. and distributed CC-BY.

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