Phenotype-aware prioritisation of rare Mendelian disease variants
A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic o...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Kelly, Catherine [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022transfer abstract |
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| Umfang: |
13 |
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| Übergeordnetes Werk: |
Enthalten in: Degrading chlorinated aliphatics by reductive dechlorination of groundwater samples from the Santa Susana Field Laboratory - Dutta, Nalok ELSEVIER, 2022, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:38 ; year:2022 ; number:12 ; pages:1271-1283 ; extent:13 |
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| DOI / URN: |
10.1016/j.tig.2022.07.002 |
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| 520 | |a A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. | ||
| 520 | |a A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. | ||
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10.1016/j.tig.2022.07.002 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001965.pica (DE-627)ELV059485981 (ELSEVIER)S0168-9525(22)00179-2 DE-627 ger DE-627 rakwb eng 333.7 VZ 43.00 bkl Kelly, Catherine verfasserin aut Phenotype-aware prioritisation of rare Mendelian disease variants 2022transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. Szabo, Anita oth Pontikos, Nikolas oth Arno, Gavin oth Robinson, Peter N. oth Jacobsen, Jules O.B. oth Smedley, Damian oth Cipriani, Valentina oth Enthalten in Elsevier Science Dutta, Nalok ELSEVIER Degrading chlorinated aliphatics by reductive dechlorination of groundwater samples from the Santa Susana Field Laboratory 2022 Amsterdam [u.a.] (DE-627)ELV00781545X volume:38 year:2022 number:12 pages:1271-1283 extent:13 https://doi.org/10.1016/j.tig.2022.07.002 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 38 2022 12 1271-1283 13 |
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10.1016/j.tig.2022.07.002 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001965.pica (DE-627)ELV059485981 (ELSEVIER)S0168-9525(22)00179-2 DE-627 ger DE-627 rakwb eng 333.7 VZ 43.00 bkl Kelly, Catherine verfasserin aut Phenotype-aware prioritisation of rare Mendelian disease variants 2022transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. Szabo, Anita oth Pontikos, Nikolas oth Arno, Gavin oth Robinson, Peter N. oth Jacobsen, Jules O.B. oth Smedley, Damian oth Cipriani, Valentina oth Enthalten in Elsevier Science Dutta, Nalok ELSEVIER Degrading chlorinated aliphatics by reductive dechlorination of groundwater samples from the Santa Susana Field Laboratory 2022 Amsterdam [u.a.] (DE-627)ELV00781545X volume:38 year:2022 number:12 pages:1271-1283 extent:13 https://doi.org/10.1016/j.tig.2022.07.002 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 38 2022 12 1271-1283 13 |
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10.1016/j.tig.2022.07.002 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001965.pica (DE-627)ELV059485981 (ELSEVIER)S0168-9525(22)00179-2 DE-627 ger DE-627 rakwb eng 333.7 VZ 43.00 bkl Kelly, Catherine verfasserin aut Phenotype-aware prioritisation of rare Mendelian disease variants 2022transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. Szabo, Anita oth Pontikos, Nikolas oth Arno, Gavin oth Robinson, Peter N. oth Jacobsen, Jules O.B. oth Smedley, Damian oth Cipriani, Valentina oth Enthalten in Elsevier Science Dutta, Nalok ELSEVIER Degrading chlorinated aliphatics by reductive dechlorination of groundwater samples from the Santa Susana Field Laboratory 2022 Amsterdam [u.a.] (DE-627)ELV00781545X volume:38 year:2022 number:12 pages:1271-1283 extent:13 https://doi.org/10.1016/j.tig.2022.07.002 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 38 2022 12 1271-1283 13 |
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10.1016/j.tig.2022.07.002 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001965.pica (DE-627)ELV059485981 (ELSEVIER)S0168-9525(22)00179-2 DE-627 ger DE-627 rakwb eng 333.7 VZ 43.00 bkl Kelly, Catherine verfasserin aut Phenotype-aware prioritisation of rare Mendelian disease variants 2022transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. Szabo, Anita oth Pontikos, Nikolas oth Arno, Gavin oth Robinson, Peter N. oth Jacobsen, Jules O.B. oth Smedley, Damian oth Cipriani, Valentina oth Enthalten in Elsevier Science Dutta, Nalok ELSEVIER Degrading chlorinated aliphatics by reductive dechlorination of groundwater samples from the Santa Susana Field Laboratory 2022 Amsterdam [u.a.] (DE-627)ELV00781545X volume:38 year:2022 number:12 pages:1271-1283 extent:13 https://doi.org/10.1016/j.tig.2022.07.002 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 38 2022 12 1271-1283 13 |
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10.1016/j.tig.2022.07.002 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001965.pica (DE-627)ELV059485981 (ELSEVIER)S0168-9525(22)00179-2 DE-627 ger DE-627 rakwb eng 333.7 VZ 43.00 bkl Kelly, Catherine verfasserin aut Phenotype-aware prioritisation of rare Mendelian disease variants 2022transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. Szabo, Anita oth Pontikos, Nikolas oth Arno, Gavin oth Robinson, Peter N. oth Jacobsen, Jules O.B. oth Smedley, Damian oth Cipriani, Valentina oth Enthalten in Elsevier Science Dutta, Nalok ELSEVIER Degrading chlorinated aliphatics by reductive dechlorination of groundwater samples from the Santa Susana Field Laboratory 2022 Amsterdam [u.a.] (DE-627)ELV00781545X volume:38 year:2022 number:12 pages:1271-1283 extent:13 https://doi.org/10.1016/j.tig.2022.07.002 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 38 2022 12 1271-1283 13 |
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333.7 VZ 43.00 bkl Phenotype-aware prioritisation of rare Mendelian disease variants |
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Degrading chlorinated aliphatics by reductive dechlorination of groundwater samples from the Santa Susana Field Laboratory |
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Degrading chlorinated aliphatics by reductive dechlorination of groundwater samples from the Santa Susana Field Laboratory |
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Phenotype-aware prioritisation of rare Mendelian disease variants |
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Phenotype-aware prioritisation of rare Mendelian disease variants |
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Kelly, Catherine |
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Degrading chlorinated aliphatics by reductive dechlorination of groundwater samples from the Santa Susana Field Laboratory |
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Degrading chlorinated aliphatics by reductive dechlorination of groundwater samples from the Santa Susana Field Laboratory |
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phenotype-aware prioritisation of rare mendelian disease variants |
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Phenotype-aware prioritisation of rare Mendelian disease variants |
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A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. |
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A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. |
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A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices. |
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Phenotype-aware prioritisation of rare Mendelian disease variants |
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Szabo, Anita Pontikos, Nikolas Arno, Gavin Robinson, Peter N. Jacobsen, Jules O.B. Smedley, Damian Cipriani, Valentina |
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