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Probabilistic Analysis of Probe Reliability in Differential Gene Expression Studies with Short Oligonucleotide Arrays
January-February 2011 (vol. 8 no. 1)
pp. 217-225
ASCII Text
x 
 
Leo Lahti, Laura L. Elo, Tero Aittokallio, Samuel Kaski, "Probabilistic Analysis of Probe Reliability in Differential Gene Expression Studies with Short Oligonucleotide Arrays," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. 1, pp. 217-225, January-February, 2011.
 
 
BibTex
x
 
@article{ 10.1109/TCBB.2009.38,
author = {Leo Lahti and Laura L. Elo and Tero Aittokallio and Samuel Kaski},
title = {Probabilistic Analysis of Probe Reliability in Differential Gene Expression Studies with Short Oligonucleotide Arrays},
journal ={IEEE/ACM Transactions on Computational Biology and Bioinformatics},
volume = {8},
number = {1},
issn = {1545-5963},
year = {2011},
pages = {217-225},
doi = {http://doi.ieeecomputersociety.org/10.1109/TCBB.2009.38},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE/ACM Transactions on Computational Biology and Bioinformatics
TI - Probabilistic Analysis of Probe Reliability in Differential Gene Expression Studies with Short Oligonucleotide Arrays
IS - 1
SN - 1545-5963
SP217
EP225
EPD - 217-225
A1 - Leo Lahti,
A1 - Laura L. Elo,
A1 - Tero Aittokallio,
A1 - Samuel Kaski,
PY - 2011
KW - Applications
KW - biology and genetics
KW - parameter learning
KW - probabilistic algorithms.
VL - 8
JA - IEEE/ACM Transactions on Computational Biology and Bioinformatics
ER -
 
Leo Lahti, Helsinki University of Technology, TKK
Laura L. Elo, University of Turku, Turku
Tero Aittokallio, University of Turku, Turku
Samuel Kaski, Helsinki University of Technology, TKK
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.

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Index Terms:
Applications, biology and genetics, parameter learning, probabilistic algorithms.
Citation:
Leo Lahti, Laura L. Elo, Tero Aittokallio, Samuel Kaski, "Probabilistic Analysis of Probe Reliability in Differential Gene Expression Studies with Short Oligonucleotide Arrays," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. 1, pp. 217-225, Jan.-Feb. 2011, doi:10.1109/TCBB.2009.38
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