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Match-only integral distribution (MOID) algorithm for high-density oligonucleotide array analysis.

Zhou Y, Abagyan R - BMC Bioinformatics (2002)

Bottom Line: While MOID gave similar performance to MAS4 in the spiking experiments, better performance was observed in the no-change experiments.MOID also provides a set of alternative statistical analysis tools to MAS4.There are two main features that distinguish MOID from MAS4.The results show that by using MOID, Affymetrix GeneChip arrays may need as little as ten probes per gene without compromising analysis accuracy.

View Article: PubMed Central - HTML - PubMed

Affiliation: Genomics Institute of the Novartis Research Foundation, 3115 Merryfield Row, San Diego, CA 92121, USA. zhou@gnf.org

ABSTRACT

Background: High-density oligonucleotide arrays have become a valuable tool for high-throughput gene expression profiling. Increasing the array information density and improving the analysis algorithms are two important computational research topics.

Results: A new algorithm, Match-Only Integral Distribution (MOID), was developed to analyze high-density oligonucleotide arrays. Using known data from both spiking experiments and no-change experiments performed with Affymetrix GeneChip arrays, MOID and the Affymetrix algorithm implemented in Microarray Suite 4.0 (MAS4) were compared. While MOID gave similar performance to MAS4 in the spiking experiments, better performance was observed in the no-change experiments.MOID also provides a set of alternative statistical analysis tools to MAS4. There are two main features that distinguish MOID from MAS4. First, MOID uses continuous P values for the likelihood of gene presence, while MAS4 resorts to discrete absolute calls. Secondly, MOID uses heuristic confidence intervals for both gene expression levels and fold change values, while MAS4 categorizes the significance of gene expression level changes into discrete fold change calls.

Conclusions: The results show that by using MOID, Affymetrix GeneChip arrays may need as little as ten probes per gene without compromising analysis accuracy.

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Related in: MedlinePlus

Noise test for two human lung samples replicated previously described. During a test, a certain number of perfect matches were randomly selected, and their intensities were multiplied by ten. The computations were otherwise done in the same way as in Figure 2. The MAS4 and MOID calculations are in blue and red filled circles, respectively. The error bars represent the widths of intensity ranges where 80 percent of the fold change data fall. Both methods are robust enough to stand for two noisy probes; MOID is slightly in favor for larger noise.
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Figure 6: Noise test for two human lung samples replicated previously described. During a test, a certain number of perfect matches were randomly selected, and their intensities were multiplied by ten. The computations were otherwise done in the same way as in Figure 2. The MAS4 and MOID calculations are in blue and red filled circles, respectively. The error bars represent the widths of intensity ranges where 80 percent of the fold change data fall. Both methods are robust enough to stand for two noisy probes; MOID is slightly in favor for larger noise.

Mentions: Computer simulations also enable us to study the behaviors of both algorithms under noise disturbance. In simulations, a subset of nn probes were randomly chosen, their PM values were multiplied by ten to mimic the effect of serious noise effect. We repeated the calculations for both spiking experiments and no-change experiments, while gradually increasing nn. Figure 5 and figure 6 show the results for spiking calculation and no-change calculation, respectively. As the graph suggested, both MAS4 and MOID can resist noise perturbation up to 2 cells out of 16, the test favors MOID slightly.


Match-only integral distribution (MOID) algorithm for high-density oligonucleotide array analysis.

Zhou Y, Abagyan R - BMC Bioinformatics (2002)

Noise test for two human lung samples replicated previously described. During a test, a certain number of perfect matches were randomly selected, and their intensities were multiplied by ten. The computations were otherwise done in the same way as in Figure 2. The MAS4 and MOID calculations are in blue and red filled circles, respectively. The error bars represent the widths of intensity ranges where 80 percent of the fold change data fall. Both methods are robust enough to stand for two noisy probes; MOID is slightly in favor for larger noise.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC65509&req=5

Figure 6: Noise test for two human lung samples replicated previously described. During a test, a certain number of perfect matches were randomly selected, and their intensities were multiplied by ten. The computations were otherwise done in the same way as in Figure 2. The MAS4 and MOID calculations are in blue and red filled circles, respectively. The error bars represent the widths of intensity ranges where 80 percent of the fold change data fall. Both methods are robust enough to stand for two noisy probes; MOID is slightly in favor for larger noise.
Mentions: Computer simulations also enable us to study the behaviors of both algorithms under noise disturbance. In simulations, a subset of nn probes were randomly chosen, their PM values were multiplied by ten to mimic the effect of serious noise effect. We repeated the calculations for both spiking experiments and no-change experiments, while gradually increasing nn. Figure 5 and figure 6 show the results for spiking calculation and no-change calculation, respectively. As the graph suggested, both MAS4 and MOID can resist noise perturbation up to 2 cells out of 16, the test favors MOID slightly.

Bottom Line: While MOID gave similar performance to MAS4 in the spiking experiments, better performance was observed in the no-change experiments.MOID also provides a set of alternative statistical analysis tools to MAS4.There are two main features that distinguish MOID from MAS4.The results show that by using MOID, Affymetrix GeneChip arrays may need as little as ten probes per gene without compromising analysis accuracy.

View Article: PubMed Central - HTML - PubMed

Affiliation: Genomics Institute of the Novartis Research Foundation, 3115 Merryfield Row, San Diego, CA 92121, USA. zhou@gnf.org

ABSTRACT

Background: High-density oligonucleotide arrays have become a valuable tool for high-throughput gene expression profiling. Increasing the array information density and improving the analysis algorithms are two important computational research topics.

Results: A new algorithm, Match-Only Integral Distribution (MOID), was developed to analyze high-density oligonucleotide arrays. Using known data from both spiking experiments and no-change experiments performed with Affymetrix GeneChip arrays, MOID and the Affymetrix algorithm implemented in Microarray Suite 4.0 (MAS4) were compared. While MOID gave similar performance to MAS4 in the spiking experiments, better performance was observed in the no-change experiments.MOID also provides a set of alternative statistical analysis tools to MAS4. There are two main features that distinguish MOID from MAS4. First, MOID uses continuous P values for the likelihood of gene presence, while MAS4 resorts to discrete absolute calls. Secondly, MOID uses heuristic confidence intervals for both gene expression levels and fold change values, while MAS4 categorizes the significance of gene expression level changes into discrete fold change calls.

Conclusions: The results show that by using MOID, Affymetrix GeneChip arrays may need as little as ten probes per gene without compromising analysis accuracy.

Show MeSH
Related in: MedlinePlus