Limits...
Large scale analysis of positional effects of single-base mismatches on microarray gene expression data.

Duan F, Pauley MA, Spindel ER, Zhang L, Norgren RB - BioData Min (2010)

Bottom Line: A cross study comparison of the effect of mismatch types revealed that results were not in good agreement among different reports.However, if the mismatch types were consolidated to purine or pyrimidine mismatches, cross study conclusions could be generated.The comprehensive assessment of the effects of single-base mismatches on microarrays provided in this report can be useful for improving future versions of microarray platform design and the corresponding data analysis algorithms.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Statistical Sciences, Brown University, Providence, RI, USA. fduan@stat.brown.edu.

ABSTRACT

Background: Affymetrix GeneChips utilize 25-mer oligonucleotides probes linked to a silica surface to detect targets in solution. Mismatches due to single nucleotide polymorphisms (SNPs) can affect the hybridization between probes and targets. Previous research has indicated that binding between probes and targets strongly depends on the positions of these mismatches. However, there has been substantial variability in the effect of mismatch type across studies.

Methods: By taking advantage of naturally occurring mismatches between rhesus macaque transcripts and human probes from the Affymetrix U133 Plus 2 GeneChip, we collected the largest 25-mer probes dataset with single-base mismatches at each of the 25 positions on the probe ever used in this type of analysis.

Results: A mismatch at the center of a probe led to a greater loss in signal intensity than a mismatch at the ends of the probe, regardless of the mismatch type. There was a slight asymmetry between the ends of a probe: effects of mismatches at the 3' end of a probe were greater than those at the 5' end. A cross study comparison of the effect of mismatch types revealed that results were not in good agreement among different reports. However, if the mismatch types were consolidated to purine or pyrimidine mismatches, cross study conclusions could be generated.

Conclusion: The comprehensive assessment of the effects of single-base mismatches on microarrays provided in this report can be useful for improving future versions of microarray platform design and the corresponding data analysis algorithms.

No MeSH data available.


Average of log2(PM/MMi) versus the variability of log2(PM/MMi) across 25 mismatch positions. The values of the median and the median absolute deviation (MAD) of log2(PM/MMi), representing the robust versions of the average and variability, were calculated for each mismatch position. The number inside the circle indicates the mismatch position. R- square measures the strength of the linear relationship between two variables.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2877042&req=5

Figure 3: Average of log2(PM/MMi) versus the variability of log2(PM/MMi) across 25 mismatch positions. The values of the median and the median absolute deviation (MAD) of log2(PM/MMi), representing the robust versions of the average and variability, were calculated for each mismatch position. The number inside the circle indicates the mismatch position. R- square measures the strength of the linear relationship between two variables.

Mentions: The average difference between PM and MM depended on the position of the mismatch on the probe. Both the average and variability (represented by the interquantile range) of log2(PM/MMi) increased from both ends of the probes (positions 1 and 25) towards the center, and became relatively steady between positions 7 - 16 (Figure 2). The peak value of the average of log2(PM/MMi) was reached when i was equal to 12. For example, there was a 24% decrease in the value of PM/MM when the position changed from 12 to 1, and a 29% decrease in the value of PM/MM when the position changed from 12 to 25. In addition, we observed a strong linear association between the average and the variability of log2(PM/MMi)(R2 = 0.95) (Figure 3).


Large scale analysis of positional effects of single-base mismatches on microarray gene expression data.

Duan F, Pauley MA, Spindel ER, Zhang L, Norgren RB - BioData Min (2010)

Average of log2(PM/MMi) versus the variability of log2(PM/MMi) across 25 mismatch positions. The values of the median and the median absolute deviation (MAD) of log2(PM/MMi), representing the robust versions of the average and variability, were calculated for each mismatch position. The number inside the circle indicates the mismatch position. R- square measures the strength of the linear relationship between two variables.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2877042&req=5

Figure 3: Average of log2(PM/MMi) versus the variability of log2(PM/MMi) across 25 mismatch positions. The values of the median and the median absolute deviation (MAD) of log2(PM/MMi), representing the robust versions of the average and variability, were calculated for each mismatch position. The number inside the circle indicates the mismatch position. R- square measures the strength of the linear relationship between two variables.
Mentions: The average difference between PM and MM depended on the position of the mismatch on the probe. Both the average and variability (represented by the interquantile range) of log2(PM/MMi) increased from both ends of the probes (positions 1 and 25) towards the center, and became relatively steady between positions 7 - 16 (Figure 2). The peak value of the average of log2(PM/MMi) was reached when i was equal to 12. For example, there was a 24% decrease in the value of PM/MM when the position changed from 12 to 1, and a 29% decrease in the value of PM/MM when the position changed from 12 to 25. In addition, we observed a strong linear association between the average and the variability of log2(PM/MMi)(R2 = 0.95) (Figure 3).

Bottom Line: A cross study comparison of the effect of mismatch types revealed that results were not in good agreement among different reports.However, if the mismatch types were consolidated to purine or pyrimidine mismatches, cross study conclusions could be generated.The comprehensive assessment of the effects of single-base mismatches on microarrays provided in this report can be useful for improving future versions of microarray platform design and the corresponding data analysis algorithms.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Statistical Sciences, Brown University, Providence, RI, USA. fduan@stat.brown.edu.

ABSTRACT

Background: Affymetrix GeneChips utilize 25-mer oligonucleotides probes linked to a silica surface to detect targets in solution. Mismatches due to single nucleotide polymorphisms (SNPs) can affect the hybridization between probes and targets. Previous research has indicated that binding between probes and targets strongly depends on the positions of these mismatches. However, there has been substantial variability in the effect of mismatch type across studies.

Methods: By taking advantage of naturally occurring mismatches between rhesus macaque transcripts and human probes from the Affymetrix U133 Plus 2 GeneChip, we collected the largest 25-mer probes dataset with single-base mismatches at each of the 25 positions on the probe ever used in this type of analysis.

Results: A mismatch at the center of a probe led to a greater loss in signal intensity than a mismatch at the ends of the probe, regardless of the mismatch type. There was a slight asymmetry between the ends of a probe: effects of mismatches at the 3' end of a probe were greater than those at the 5' end. A cross study comparison of the effect of mismatch types revealed that results were not in good agreement among different reports. However, if the mismatch types were consolidated to purine or pyrimidine mismatches, cross study conclusions could be generated.

Conclusion: The comprehensive assessment of the effects of single-base mismatches on microarrays provided in this report can be useful for improving future versions of microarray platform design and the corresponding data analysis algorithms.

No MeSH data available.