SNP: Difference between revisions
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** Accuracy can be improved from single(Ref vs one sample) to multi samples (Ref vs several samles) | ** Accuracy can be improved from single(Ref vs one sample) to multi samples (Ref vs several samles) | ||
** Possible accuracy by read depth based SNP calling is 85% | ** Possible accuracy by read depth based SNP calling is 85% | ||
** '''Possible accuracy by LD (linkage disequilibrium) is >95%''' | ** '''Possible accuracy by LD (linkage disequilibrium) is >95%''' | ||
*** Possible only when multi samples are used | |||
*** Software that uses LD for SNP calling is Beagle, IMPUTE2, QCall, MaCH | |||
Revision as of 09:22, 17 May 2016
SNP Filtering Plans
Base Calling
- Minimum Read depth
- Based on Phred scores
- 1% error rate
- Alignment (Trade off between accuracy and read depth)
- Recalibration of Pherd scores
- Essential
- Phred score of Q should be = 10 to the power Q by 10 or less. This is done by alignning with the reference with the known SNPs
- Homo and Heterozgous SNPs in a diploid
- Homozygous -> If an SNP (different than ref) base is counted across the read depth to be more than 80%
- Hetorozygous -> If an SNP (different than ref) base is counted across the read depth to be less than 80%
- Sequence/alignment Error -> If an SNP based is counted to be less than 10%
- This is true of the depth is minimum of 20x
- Accuracy in SNP calling
- Accuracy can be improved from single(Ref vs one sample) to multi samples (Ref vs several samles)
- Possible accuracy by read depth based SNP calling is 85%
- Possible accuracy by LD (linkage disequilibrium) is >95%
- Possible only when multi samples are used
- Software that uses LD for SNP calling is Beagle, IMPUTE2, QCall, MaCH