TY - JOUR
T1 - Positional artifacts in microarrays
T2 - Experimental verification and construction of COP, an automated detection tool
AU - Yu, Haiyuan
AU - Nguyen, Katherine
AU - Royce, Tom
AU - Qian, Jiang
AU - Nelson, Kenneth
AU - Snyder, Michael
AU - Gerstein, Mark
N1 - Funding Information:
Funding to pay the Open Access publication charges for this article was provided by NIH.
PY - 2007/1
Y1 - 2007/1
N2 - Microarray technology is currently one of the most widely-used technologies in biology. Many studies focus on inferring the function of an unknown gene from its co-expressed genes. Here, we are able to show that there are two types of positional artifacts in microarray data introducing spurious correlations between genes. First, we find that genes that are close on the microarray chips tend to have higher correlations between their expression profiles. We call this the 'chip artifact'. Our calculations suggest that the carry-over during the printing process is one of the major sources of this type of artifact, which is later confirmed by our experiments. Based on our experiments, the measured intensity of a microarray spot contains 0.1% (for fully-hybridized spots) to 93% (for un-hybridized ones) of noise resulting from this artifact. Secondly, we, for the first time, show that genes that are close on the microtiter plates in microarray experiments also tend to have higher correlations. We call this the 'plate artifact'. Both types of artifacts exist with different severity in all cDNA microarray experiments that we analyzed. Therefore, we develop an automated web tool - COP (COrrelations by Positional artifacts) to detect these artifacts in microarray experiments. COP has been integrated with the microarray data normalization tool, ExpressYourself, which is available at http://bioinfo.mbb.yale.edu/ ExpressYourself/. Together, the two can eliminate most of the common noises in microarray data.
AB - Microarray technology is currently one of the most widely-used technologies in biology. Many studies focus on inferring the function of an unknown gene from its co-expressed genes. Here, we are able to show that there are two types of positional artifacts in microarray data introducing spurious correlations between genes. First, we find that genes that are close on the microarray chips tend to have higher correlations between their expression profiles. We call this the 'chip artifact'. Our calculations suggest that the carry-over during the printing process is one of the major sources of this type of artifact, which is later confirmed by our experiments. Based on our experiments, the measured intensity of a microarray spot contains 0.1% (for fully-hybridized spots) to 93% (for un-hybridized ones) of noise resulting from this artifact. Secondly, we, for the first time, show that genes that are close on the microtiter plates in microarray experiments also tend to have higher correlations. We call this the 'plate artifact'. Both types of artifacts exist with different severity in all cDNA microarray experiments that we analyzed. Therefore, we develop an automated web tool - COP (COrrelations by Positional artifacts) to detect these artifacts in microarray experiments. COP has been integrated with the microarray data normalization tool, ExpressYourself, which is available at http://bioinfo.mbb.yale.edu/ ExpressYourself/. Together, the two can eliminate most of the common noises in microarray data.
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U2 - 10.1093/nar/gkl871
DO - 10.1093/nar/gkl871
M3 - Article
C2 - 17158151
AN - SCOPUS:33846938060
SN - 0305-1048
VL - 35
JO - Nucleic acids research
JF - Nucleic acids research
IS - 2
M1 - e8
ER -