Limits...
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.

Show MeSH

Related in: MedlinePlus

Reduced probe set test for 366 known spiking data. The method is the same as described in Figure 1. The red and blue filled circles are the results for MAS4 and MOID, respectively. The error bars were derived from three independent simulations. As indicated, there is no significant deterioration in the performance of both methods down to 10 probe cells.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC65509&req=5

Figure 3: Reduced probe set test for 366 known spiking data. The method is the same as described in Figure 1. The red and blue filled circles are the results for MAS4 and MOID, respectively. The error bars were derived from three independent simulations. As indicated, there is no significant deterioration in the performance of both methods down to 10 probe cells.

Mentions: In the simulation, for each probe set, a subset of nr probes were randomly chosen to be used in the calculation. Both the spiking and no-change calculations presented above were repeated with the selected subset, as we gradually reduced nr. Figure 3 and figure 4 show the results for the spiking calculation and no-change calculation, respectively. As the graph suggested, accuracy of MOID is essentially unaffected while reducing the number of probes down to ten. This result enables us to almost triple the amount of clusters one can put on a gene chip using MOID design. Combined with other new design ideas, MOID lays the foundation for the first universal human chip that contains 75,000 UniGene clusters (release 116). The results have recently been validated and led to many interesting discoveries, which provides indirect support for MOID (to be submitted).


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

Zhou Y, Abagyan R - BMC Bioinformatics (2002)

Reduced probe set test for 366 known spiking data. The method is the same as described in Figure 1. The red and blue filled circles are the results for MAS4 and MOID, respectively. The error bars were derived from three independent simulations. As indicated, there is no significant deterioration in the performance of both methods down to 10 probe cells.
© Copyright Policy
Related In: Results  -  Collection

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

Figure 3: Reduced probe set test for 366 known spiking data. The method is the same as described in Figure 1. The red and blue filled circles are the results for MAS4 and MOID, respectively. The error bars were derived from three independent simulations. As indicated, there is no significant deterioration in the performance of both methods down to 10 probe cells.
Mentions: In the simulation, for each probe set, a subset of nr probes were randomly chosen to be used in the calculation. Both the spiking and no-change calculations presented above were repeated with the selected subset, as we gradually reduced nr. Figure 3 and figure 4 show the results for the spiking calculation and no-change calculation, respectively. As the graph suggested, accuracy of MOID is essentially unaffected while reducing the number of probes down to ten. This result enables us to almost triple the amount of clusters one can put on a gene chip using MOID design. Combined with other new design ideas, MOID lays the foundation for the first universal human chip that contains 75,000 UniGene clusters (release 116). The results have recently been validated and led to many interesting discoveries, which provides indirect support for MOID (to be submitted).

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