In:
Bioinformatics, Oxford University Press (OUP), Vol. 26, No. 18 ( 2010-09-15), p. i618-i624
Kurzfassung:
Motivation: The identification of genes involved in specific phenotypes, such as human hereditary diseases, often requires the time-consuming and expensive examination of a large number of positional candidates selected by genome-wide techniques such as linkage analysis and association studies. Even considering the positive impact of next-generation sequencing technologies, the prioritization of these positional candidates may be an important step for disease-gene identification. Results: Here, we report a large-scale analysis of spatial, i.e. 3D, gene-expression data from an entire organ (the mouse brain) for the purpose of evaluating and ranking positional candidate genes, showing that the spatial gene-expression patterns can be successfully exploited for the prediction of gene–phenotype associations not only for mouse phenotypes, but also for human central nervous system-related Mendelian disorders. We apply our method to the case of X-linked mental retardation, compare the predictions to the results obtained from a previous large-scale resequencing study of chromosome X and discuss some promising novel candidates. Contact: rosario.piro@unito.it Supplementary information: Supplementary data are available at Bioinformatics online.
Materialart:
Online-Ressource
ISSN:
1367-4811
,
1367-4803
DOI:
10.1093/bioinformatics/btq396
Sprache:
Englisch
Verlag:
Oxford University Press (OUP)
Publikationsdatum:
2010
ZDB Id:
1468345-3
SSG:
12
Bookmarklink