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Oligonucleotide single nucleotide polymorphisms arrays have been studied in genomic research with various methods for copy number alterations and genotype calling

On Design of Oligonucleotide SNP Arrays and Methods for Genotype Calling

BMEI, (2008): 453-458

Cited: 0|Views15
WOS SCOPUS EI

Abstract

The fast development of array technology has raised the density of oligonucleotide SNP arrays from 10K and 50K to 100K and 500K. However, methods for SNP genotyping have not been developed as fast. Most methods are based on sample-dependent multi-array training and may not be suitable for cross-laboratory studies and small sample studies,...More

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Introduction
  • With the fast development of high-throughout microarray technology, oligonucleotide microarray have been widely used in genomic research, especially in genome wide association studies and copy number alteration studies based on single nucleotide polymorphisms (SNPs) data [2,3,6,7,12,14,16,17,19, 25].
  • Current genotype calling methods have achieved high accuracy, many of them rely on sampledependent multi-array training and may not be suitable for cross-laboratory studies [1,4,5,9,10,11,13, 15,22]
  • These sample-dependent methods limit themselves to only large sample studies because small sample studies may not have enough training samples for the required model parameters and parameter training with different studies, such as the HapMap project, may not be appropriate and lead to severe accuracy problems [4].
  • Novel methods that are robust across samples and laboratories and do not require a large training sample need to be developed
Highlights
  • With the fast development of high-throughout microarray technology, oligonucleotide microarray have been widely used in genomic research, especially in genome wide association studies and copy number alteration studies based on single nucleotide polymorphisms (SNPs) data [2,3,6,7,12,14,16,17,19, 25]
  • It clearly indicates that the error rate increases substantially with the reduction of quartets from 10 to 4. It indicates that the elimination of mismatch probes increases the error rate by 50 folds or more, which implicates that mismatch probes contain crucial information and should not be eliminated from the array design
  • While using sense strand probes only is equivalent to reducing the number of probes by one half, using antisense probes only incurs slightly larger error rates than using sense-strand probes only, which may implicate that sense strand probes are more informative in genotyping than anti-sense strand probes
  • Oligonucleotide SNP arrays have been studied in genomic research with various methods for copy number alterations and genotype calling
  • The fast development of array technology has prompted the study of array design
  • Several works have suggested to eliminate mismatch probes in the arrays, and to further reduce the number of perfect match probes, we found that reduction of the number of probes substantially increases genotyping error rate
Methods
  • Ninety CEL files for 30 trio samples in HapMap project were downloaded from the Mapping 100K HapMap Trio Dataset on the website of the Affymetrix Inc. All data were processed by R using “affyio” and “affy” packages in Bioconductor.
  • All data were processed by R using “affyio” and “affy” packages in Bioconductor
  • Among these 90 files, the authors randomly selected 6 Xba arrays.
  • The authors used the genotype from the International HapMap project as the gold standard.
Results
  • Results and conclusion

    Table 1 lists genotyping error rate for each array by the number of randomly selected quartets.
  • It indicates that the elimination of mismatch probes increases the error rate by 50 folds or more, which implicates that mismatch probes contain crucial information and should not be eliminated from the array design.
  • Figures 2 and 3 illustrate the increase of error rate with the reduction of number of quartets by boxplots and error rate curves
  • It shows that 8 quartets or more can make the error rate lower than 0.5%, while fewer than 6 quartets will increase the error rates to 1% or larger.
  • A minimum of 6 quartets should be retained for SNP array if an error rate smaller than 1% is desirable
Conclusion
  • Oligonucleotide SNP arrays have been studied in genomic research with various methods for copy number alterations and genotype calling.
  • Several works have suggested to eliminate mismatch probes in the arrays, and to further reduce the number of perfect match probes, the authors found that reduction of the number of probes substantially increases genotyping error rate.
  • Elimination of mismatch probes increases the error rate by 50 folds or more.
  • Reduction of probes for more SNPs in one single array may sacrifice genotyping quality.
  • Elimination of mismatch probes leads to tremendous loss of information and accuracy
Tables
  • Table1: Mean percentage genotyping error rate (standard deviation) over 10 repeats of random samples out of 10 quartets of 100K SNP array. *
Download tables as Excel
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