Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases.
Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases.
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DOI：
10.1093/bib/bbac188
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发表时间：
2022-09-20
影响因子：
9.5
通讯作者：
中科院分区：
文献类型：
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作者：
袁等人。最近描述了在两个独立的临床数据集上对孟德尔疾病的几种表型驱动的基因优先排序方法进行的独立评估。尽管他们尝试对每个工具使用默认设置，但我们描述了与当前为 Exomiser 和 PhenIX 工具推荐的设置的三个主要区别。这些影响如何使用变异频率、质量和预测的致病性进行过滤和优先排序。我们认为，这些差异在很大程度上解释了他们报告的结果（Exomiser 的诊断结果为 15-26%）与我们和其他人之前发布的报告（72-77%）之间的性能差异。在一组 161 个单例样本中，我们显示使用这些设置可将性能从 34% 提高到 72%，并建议使用这些设置重新评估 Exomiser 和 PhenIX 在其数据集上的表现，也会显示出类似的提升。
Yuan et al. recently described an independent evaluation of several phenotype-driven gene prioritization methods for Mendelian disease on two separate, clinical datasets. Although they attempted to use default settings for each tool, we describe three key differences from those we currently recommend for our Exomiser and PhenIX tools. These influence how variant frequency, quality and predicted pathogenicity are used for filtering and prioritization. We propose that these differences account for much of the discrepancy in performance between that reported by them (15–26% diagnoses ranked top by Exomiser) and previously published reports by us and others (72–77%). On a set of 161 singleton samples, we show using these settings increases performance from 34% to 72% and suggest a reassessment of Exomiser and PhenIX on their datasets using these would show a similar uplift.
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评估孟德尔疾病的表型驱动基因优先方法。
影响因子：
9.5
作者：
Yuan X;Wang J;Dai B;Sun Y;Zhang K;Chen F;Peng Q;Huang Y;Zhang X;Chen J;Xu X;Chuan J;Mu W;Li H;Fang P;Gong Q;Zhang P
通讯作者：
Zhang P
影响因子：
3.5
作者：
Cipriani, Valentina;Pontikos, Nikolas;Smedley, Damian
通讯作者：
Smedley, Damian
DOI：
10.1056/nejmoa2035790
发表时间：
2021-11-11
期刊：
The New England journal of medicine
影响因子：
--
作者：
100,000 Genomes Project Pilot Investigators;Smedley D;Smith KR;Martin A;Thomas EA;McDonagh EM;Cipriani V;Ellingford JM;Arno G;Tucci A;Vandrovcova J;Chan G;Williams HJ;Ratnaike T;Wei W;Stirrups K;Ibanez K;Moutsianas L;Wielscher M;Need A;Barnes MR;Vestito L;Buchanan J;Wordsworth S;Ashford S;Rehmström K;Li E;Fuller G;Twiss P;Spasic-Boskovic O;Halsall S;Floto RA;Poole K;Wagner A;Mehta SG;Gurnell M;Burrows N;James R;Penkett C;Dewhurst E;Gräf S;Mapeta R;Kasanicki M;Haworth A;Savage H;Babcock M;Reese MG;Bale M;Baple E;Boustred C;Brittain H;de Burca A;Bleda M;Devereau A;Halai D;Haraldsdottir E;Hyder Z;Kasperaviciute D;Patch C;Polychronopoulos D;Matchan A;Sultana R;Ryten M;Tavares ALT;Tregidgo C;Turnbull C;Welland M;Wood S;Snow C;Williams E;Leigh S;Foulger RE;Daugherty LC;Niblock O;Leong IUS;Wright CF;Davies J;Crichton C;Welch J;Woods K;Abulhoul L;Aurora P;Bockenhauer D;Broomfield A;Cleary MA;Lam T;Dattani M;Footitt E;Ganesan V;Grunewald S;Compeyrot-Lacassagne S;Muntoni F;Pilkington C;Quinlivan R;Thapar N;Wallis C;Wedderburn LR;Worth A;Bueser T;Compton C;Deshpande C;Fassihi H;Haque E;Izatt L;Josifova D;Mohammed S;Robert L;Rose S;Ruddy D;Sarkany R;Say G;Shaw AC;Wolejko A;Habib B;Burns G;Hunter S;Grocock RJ;Humphray SJ;Robinson PN;Haendel M;Simpson MA;Banka S;Clayton-Smith J;Douzgou S;Hall G;Thomas HB;O'Keefe RT;Michaelides M;Moore AT;Malka S;Pontikos N;Browning AC;Straub V;Gorman GS;Horvath R;Quinton R;Schaefer AM;Yu-Wai-Man P;Turnbull DM;McFarland R;Taylor RW;O'Connor E;Yip J;Newland K;Morris HR;Polke J;Wood NW;Campbell C;Camps C;Gibson K;Koelling N;Lester T;Németh AH;Palles C;Patel S;Roy NBA;Sen A;Taylor J;Cacheiro P;Jacobsen JO;Seaby EG;Davison V;Chitty L;Douglas A;Naresh K;McMullan D;Ellard S;Temple IK;Mumford AD;Wilson G;Beales P;Bitner-Glindzicz M;Black G;Bradley JR;Brennan P;Burn J;Chinnery PF;Elliott P;Flinter F;Houlden H;Irving M;Newman W;Rahman S;Sayer JA;Taylor JC;Webster AR;Wilkie AOM;Ouwehand WH;Raymond FL;Chisholm J;Hill S;Bentley D;Scott RH;Fowler T;Rendon A;Caulfield M
通讯作者：
Caulfield M
影响因子：
1.8
作者：
Ji, Jianling;Shen, Lishuang;Gai, Xiaowu
通讯作者：
Gai, Xiaowu