1:缺失比例(Missing
rates)：(
GENO > 0.05 )
Shortly we will
apply more stringent criteria, such that GENO > 0.05. In this
case, 0.05*89 = 4.45 samples, meaning that if a SNP is missing in
4.45 more more samples, that SNP will be removed from the
dataset.
2:最小等位基因频率(Minor
Allele frequencies)(
MAF< 0.03 如果SNP较多可以设置为MAF<0.05)
MAF
is the Minor Allele Frequency. It can be used to exclude SNPs which
are not informative because they show little variation in the
sample set being analyzed. For instance, if a SNP shows variation
in only 1 of the 89 individuals, it is not useful statistically and
should be removed.
3:Removing SNPs
out of Hardy-Weinberg equilibrium(p-value > 10−6 -
10−4
)
Population
genetic theory suggests that under ‘normal’ conditions, there is a
predictable relationship between allele frequencies and genotype
frequencies. In cases where the genotype distribution is different
from what one would expect based on the allele frequencies, one
potential explanation for this is genotyping error. Natural
selection is another explanation. For this reason, we typically
check for deviation from Hardy-Weinberg equilibrium in the controls
for a case- control study. For a quantitative trait, PLINK just
uses everyone. The following command generates p-values for
deviation from HWE for each SNP. Low p-values indicate that a SNP
is out of HWE.
4:如果你有vcf文件，可以先用vcftools转换为plink的输入形势，输出结果为：.bed与.map文件，然后以此作为输入进行过滤：
vcftools --vcf
my.vcf --plink --out plink
plink
--noweb --file plink --geno 0.05 --maf 0.05 --hwe 0.0001 --make-bed
--out QC
参考文献：
Roshyara N R,
Kirsten H, Horn K, et al. Impact of pre-imputation SNP-filtering on
genotype imputation results[J]. BMC genetics, , 15(1):
1.
Pongpanich M,
Sullivan P F, Tzeng J Y. A quality control algorithm for filtering
SNPs in genome-wide association studies[J]. Bioinformatics, ,
26(14): 1731-1737.
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