Table 1.
Total number of 3290 exomes by predominant phenotypes.
Fig 1.
Phenogenon profiling workflow.
A) The distribution of frequency vs CADD Phred score for variants of a single gene were binned according to empirically chosen cut-offs. B) Variants within each binned area are further analysed. Individuals carrying these variants are identified and then filtered on the basis of whether they have a selected HPO term. C) Fisher’s Exact test is then used to determine the significance of the gene-phenotype relationship. D) A Phenogenon heatmap is produced using the Fisher Exact P-Values for each binned area. E) Fisher Exact Scores for each of the binned area in the first column are collapsed into a single HPO goodness of fit score (HGF) using a Scaled Stouffer transformation.
Table 2.
Known HPO-gene-MOI relationships used to benchmark Phenogenon.
Fig 2.
Using phenogenon to predict gene-HPO-mode of inheritance (MOI) relationships for the 12 known genes.
A. Examples of using Phenogenon to profile known relationships: ABCA4—Macular dystrophy (HP:0007754) -recessive, and SCN1A—Seizures (HP:0001250)—dominant. The color scales represent the HGF score. The majority of high-scoring bins are for rare variants (HGF < 0.00025). B. Error rate in predicting HPO when number of patients selected per gene is higher than ‘HPO NP cut-off’. The lines give the trend of error rates for each prediction model. C. Error rate for MOI when HPO selected per gene is higher than HGF cut-off. The lines give the trend of error rates for each prediction model. Orange line: model using gnomAD allele frequency instead of estimated homozygote frequency for recessive MOI; Red line: model using HGF for both HPO association and MOI prediction; Blue line: model using Fisher method to combine p values; Green line: our current model for Phenogenon.
Table 3.
Top-ranked gene-phenotype-MOI relations reported by phenogenon.