| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 305 DDD exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: DDD 305 solved probands (Yuan et al. selection) | 1.6% Top-1 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on DDD 305 rare-ranking-20261009-protocol-yuan2022-ddd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 3 (DDD, DeepPVP), column 'TOP 1(%)' |
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| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 305 DDD exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: DDD 305 solved probands (Yuan et al. selection) | 5.6% Top-10 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on DDD 305 rare-ranking-20261009-protocol-yuan2022-ddd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 3 (DDD, DeepPVP), column 'TOP 10(%)' |
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| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 305 DDD exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: DDD 305 solved probands (Yuan et al. selection) | 7.2% Top-20 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on DDD 305 rare-ranking-20261009-protocol-yuan2022-ddd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 3 (DDD, DeepPVP), column 'TOP 20(%)' |
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| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 305 DDD exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: DDD 305 solved probands (Yuan et al. selection) | 8.2% Top-30 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on DDD 305 rare-ranking-20261009-protocol-yuan2022-ddd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 3 (DDD, DeepPVP), column 'TOP 30(%)' |
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| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 305 DDD exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: DDD 305 solved probands (Yuan et al. selection) | 8.9% Top-40 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on DDD 305 rare-ranking-20261009-protocol-yuan2022-ddd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 3 (DDD, DeepPVP), column 'TOP 40(%)' |
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| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 305 DDD exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: DDD 305 solved probands (Yuan et al. selection) | 3.9% Top-5 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on DDD 305 rare-ranking-20261009-protocol-yuan2022-ddd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 3 (DDD, DeepPVP), column 'TOP 5(%)' |
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| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 305 DDD exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: DDD 305 solved probands (Yuan et al. selection) | 8.9% Top-50 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on DDD 305 rare-ranking-20261009-protocol-yuan2022-ddd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 3 (DDD, DeepPVP), column 'TOP 50(%)' |
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| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 209 in-house exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: KingMed Changsha in-house cohort, 209 solved cases (Yuan et al. 2022) | 6.2% Top-1 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on KMCGD 209 rare-ranking-20261009-protocol-yuan2022-kmcgd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 14 (KMCGD, DeepPVP), column 'TOP 1(%)' |
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| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 209 in-house exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: KingMed Changsha in-house cohort, 209 solved cases (Yuan et al. 2022) | 12.9% Top-10 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on KMCGD 209 rare-ranking-20261009-protocol-yuan2022-kmcgd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 14 (KMCGD, DeepPVP), column 'TOP 10(%)' |
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| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 209 in-house exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: KingMed Changsha in-house cohort, 209 solved cases (Yuan et al. 2022) | 15.3% Top-20 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on KMCGD 209 rare-ranking-20261009-protocol-yuan2022-kmcgd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 14 (KMCGD, DeepPVP), column 'TOP 20(%)' |
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| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 209 in-house exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: KingMed Changsha in-house cohort, 209 solved cases (Yuan et al. 2022) | 18.2% Top-30 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on KMCGD 209 rare-ranking-20261009-protocol-yuan2022-kmcgd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 14 (KMCGD, DeepPVP), column 'TOP 30(%)' |
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| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 209 in-house exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: KingMed Changsha in-house cohort, 209 solved cases (Yuan et al. 2022) | 18.2% Top-40 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on KMCGD 209 rare-ranking-20261009-protocol-yuan2022-kmcgd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 14 (KMCGD, DeepPVP), column 'TOP 40(%)' |
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| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 209 in-house exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: KingMed Changsha in-house cohort, 209 solved cases (Yuan et al. 2022) | 10.5% Top-5 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on KMCGD 209 rare-ranking-20261009-protocol-yuan2022-kmcgd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 14 (KMCGD, DeepPVP), column 'TOP 5(%)' |
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| Configuration: DeepPVP default, singleton (Yuan et al. 2022) | Protocol: Causal-gene rank in 209 in-house exomes, default singleton runs (Yuan et al. 2022 SM Table 3) Dataset: KingMed Changsha in-house cohort, 209 solved cases (Yuan et al. 2022) | 18.7% Top-50 accuracy (proportion of solved cases with the causal gene within the tool's top-ranked genes) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepPVP default singleton on KMCGD 209 rare-ranking-20261009-protocol-yuan2022-kmcgd-singleton-default Aggregation: Not reported Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases; Yuan et al. 2022, SM Table 3 (accuracy in each top level experiment) · SM Table 3 row 14 (KMCGD, DeepPVP), column 'TOP 50(%)' |
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