Perturbation analysis: a simple method for filtering SNPs with erroneous genotyping in genome-wide association studies.
We introduce a simple and yet scientifically objective criterion for identifying SNPs with genotyping errors due to poor clustering. This yields a metric for assessing the stability of the assigned genotypes by evaluating the extent of discordance between the calls made with the unperturbed and pert...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
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2008
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| _version_ | 1826278525716398080 |
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| author | Teo, Y Small, K Clark, T Kwiatkowski, D |
| author_facet | Teo, Y Small, K Clark, T Kwiatkowski, D |
| author_sort | Teo, Y |
| collection | OXFORD |
| description | We introduce a simple and yet scientifically objective criterion for identifying SNPs with genotyping errors due to poor clustering. This yields a metric for assessing the stability of the assigned genotypes by evaluating the extent of discordance between the calls made with the unperturbed and perturbed intensities. The efficacy of the metric is evaluated by: (1) estimating the extent of over-dispersion of the Hardy-Weinberg equilibrium chi-square test statistics; (2) an interim case-control study, where we investigated the efficacy of the introduced metric and standard quality control filters in reducing the number of SNPs with evidence of phenotypic association which are attributed to genotyping errors; (3) investigating the call and concordance rates of SNPs identified by perturbation analysis which have been genotyped on both Affymetrix and Illumina platforms. Removing SNPs identified by the extent of discordance can reduce the degree of over-dispersion of the HWE test statistic. Sensible use of perturbation analysis in an association study can correctly identify SNPs with problematic genotyping, reducing the number required for visual inspection. SNPs identified by perturbation analysis had lower call and concordance rates, and removal of these SNPs significantly improved the performance for the remaining SNPs. |
| first_indexed | 2024-03-06T23:45:13Z |
| format | Journal article |
| id | oxford-uuid:70abde2b-59bf-437f-a0fb-aa987b8f562d |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T23:45:13Z |
| publishDate | 2008 |
| record_format | dspace |
| spelling | oxford-uuid:70abde2b-59bf-437f-a0fb-aa987b8f562d2022-03-26T19:38:39ZPerturbation analysis: a simple method for filtering SNPs with erroneous genotyping in genome-wide association studies.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:70abde2b-59bf-437f-a0fb-aa987b8f562dEnglishSymplectic Elements at Oxford2008Teo, YSmall, KClark, TKwiatkowski, DWe introduce a simple and yet scientifically objective criterion for identifying SNPs with genotyping errors due to poor clustering. This yields a metric for assessing the stability of the assigned genotypes by evaluating the extent of discordance between the calls made with the unperturbed and perturbed intensities. The efficacy of the metric is evaluated by: (1) estimating the extent of over-dispersion of the Hardy-Weinberg equilibrium chi-square test statistics; (2) an interim case-control study, where we investigated the efficacy of the introduced metric and standard quality control filters in reducing the number of SNPs with evidence of phenotypic association which are attributed to genotyping errors; (3) investigating the call and concordance rates of SNPs identified by perturbation analysis which have been genotyped on both Affymetrix and Illumina platforms. Removing SNPs identified by the extent of discordance can reduce the degree of over-dispersion of the HWE test statistic. Sensible use of perturbation analysis in an association study can correctly identify SNPs with problematic genotyping, reducing the number required for visual inspection. SNPs identified by perturbation analysis had lower call and concordance rates, and removal of these SNPs significantly improved the performance for the remaining SNPs. |
| spellingShingle | Teo, Y Small, K Clark, T Kwiatkowski, D Perturbation analysis: a simple method for filtering SNPs with erroneous genotyping in genome-wide association studies. |
| title | Perturbation analysis: a simple method for filtering SNPs with erroneous genotyping in genome-wide association studies. |
| title_full | Perturbation analysis: a simple method for filtering SNPs with erroneous genotyping in genome-wide association studies. |
| title_fullStr | Perturbation analysis: a simple method for filtering SNPs with erroneous genotyping in genome-wide association studies. |
| title_full_unstemmed | Perturbation analysis: a simple method for filtering SNPs with erroneous genotyping in genome-wide association studies. |
| title_short | Perturbation analysis: a simple method for filtering SNPs with erroneous genotyping in genome-wide association studies. |
| title_sort | perturbation analysis a simple method for filtering snps with erroneous genotyping in genome wide association studies |
| work_keys_str_mv | AT teoy perturbationanalysisasimplemethodforfilteringsnpswitherroneousgenotypingingenomewideassociationstudies AT smallk perturbationanalysisasimplemethodforfilteringsnpswitherroneousgenotypingingenomewideassociationstudies AT clarkt perturbationanalysisasimplemethodforfilteringsnpswitherroneousgenotypingingenomewideassociationstudies AT kwiatkowskid perturbationanalysisasimplemethodforfilteringsnpswitherroneousgenotypingingenomewideassociationstudies |