Fig. 1

An overview of variant filtering (method 1) and variant flagging (method 2). A. method 1: In a sequencing study, a hypothetical list of 7 variants was discovered, with variant 4 being the causal variant and the other ones harmless co-inherited mutations. Inside the variant database, 5 out of 7 variants discovered during sequencing (including variant 4) are already represented with varying allele frequencies f (allele frequency db-column). Three different approaches for variant filtering can be used. Candidate variants that are filtered out, are denoted with an X. Candidate variants that are retained after filtering are denoted with a ✓. By assuming absence of disease-causing variants from variant databases (absence-approach), the disease-causing variant was erroneously filtered out. The same issue was encountered by using a static 1% threshold. The quantile-based approach was used to calculate a suitable allelic frequency threshold Tv. Based on the disease prevalence P _d of 1 in 10,000 individuals and an autosomal recessive mode of inheritance, the population allele frequency q is 0.01. For a variant database of 50 individuals (= 100 chromosomes, situation a), the Tv associated with the 95th quantile equals 0.03 (3/100). While the allele frequency f of the disease-causing variant in the variant database (= 0.02) is slightly higher than the theoretically expected population allele frequency (= 0.01) due to sampling variability, the Tv cut-off (0.03) has made it possible to discover the true disease-causing variant, while this was not the case for the other two approaches. B. method 2: this analysis determines how likely it is that a disease-causing variant (variant 4) occurs at least twice in a variant database of 50 individuals (= 100 chromosomes, situation a), given P _d equals 1 in 10,000 and an autosomal mode of inheritance. Based on the binomial distribution, this probability equals 0.26. As such, there is insufficient evidence to conclude that this model is inappropriate