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An additive model was used to code SNPs for the 'risk' allele, the allele that increased the probability of being a case.
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Currently, there are many efforts to use coding SNP information from WES data to facilitate genetic linkage mapping.
Ensembl annotations were used to classify SNPs as putative coding or non-coding mutations and for coding variants, as synonymous, non-synonymous (missense), STOP-gained, STOP-lost, splice-site, or frameshift.
It must be noted that a majority of the SNPs of health relevance used to annotate the coding SNPs were derived from studies involving western populations.
Over 500,000 public bovine expressed sequence tagged (EST) sequences were used to search for coding SNPs (cSNPs).
However, the method used to detect potential SNP-SNP interaction still requires improvement.
For SNPs detected in coding regions, the "diffseq" program within EMBOSS was used to detect SNPs resulting in nonsynonymous or synonymous changes (Rice et al. 2000).
IMPUTE2 program version 2.3.0 was used to impute SNPs not covered by Affymetrix SNP array 6.0 [12] 12].
SNPs (243,963, 97.8%) with only a single variant base, i.e., biallelic, were used to calculate the SNP frequency within the coding regions as well as the frequencies of synonymous and non-synonymous SNPs.
Reads overlapping exonic SNP positions were identified, and HTSeq was used to count these SNP-containing reads for each transcript.
New SNPs were identified in four high AAC accessions and used to develop new SNP-based molecular markers.
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