PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Probabilistic analysis of probe reliability in differential gene expression studies with short oligonucleotide arrays
Leo Lahti, Laura Elo, Tero Aittokallio and Samuel Kaski
IEEE/ACM Transactions on Computational Biology and Bioinformatics Volume 8, Number 1, pp. 217-225, 2011.


Probe defects are a major source of noise in gene expression studies. While existing approaches detect noisy probes based on external information such as genomic alignments, we introduce and validate a targeted probabilistic method for analyzing probe reliability directly from expression data and independently of the noise source. This provides insights into the various sources of probe-level noise and gives tools to guide probe design.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
ID Code:7590
Deposited By:Samuel Kaski
Deposited On:17 March 2011