Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO
Identifying individuals who are at high risk of cancer due to inherited germline mutations is critical for effective implementation of personalized prevention strategies. Most existing models focus on a few specific syndromes; however, recent evidence from multi-gene panel testing shows that many sy...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
eLife Sciences Publications Ltd
2021-08-01
|
| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/68699 |
| _version_ | 1811180164917231616 |
|---|---|
| author | Gavin Lee Jane W Liang Qing Zhang Theodore Huang Christine Choirat Giovanni Parmigiani Danielle Braun |
| author_facet | Gavin Lee Jane W Liang Qing Zhang Theodore Huang Christine Choirat Giovanni Parmigiani Danielle Braun |
| author_sort | Gavin Lee |
| collection | DOAJ |
| description | Identifying individuals who are at high risk of cancer due to inherited germline mutations is critical for effective implementation of personalized prevention strategies. Most existing models focus on a few specific syndromes; however, recent evidence from multi-gene panel testing shows that many syndromes are overlapping, motivating the development of models that incorporate family history on several cancers and predict mutations for a comprehensive panel of genes.
We present PanelPRO, a new, open-source R package providing a fast, flexible back-end for multi-gene, multi-cancer risk modeling with pedigree data. It includes a customizable database with default parameter values estimated from published studies and allows users to select any combinations of genes and cancers for their models, including well-established single syndrome BayesMendel models (BRCAPRO and MMRPRO). This leads to more accurate risk predictions and ultimately has a high impact on prevention strategies for cancer and clinical decision making. The package is available for download for research purposes at https://projects.iq.harvard.edu/bayesmendel/panelpro. |
| first_indexed | 2024-04-11T06:46:40Z |
| format | Article |
| id | doaj.art-30151eb9e9c3417ebd4c31b84536a3e7 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-11T06:46:40Z |
| publishDate | 2021-08-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-30151eb9e9c3417ebd4c31b84536a3e72022-12-22T04:39:20ZengeLife Sciences Publications LtdeLife2050-084X2021-08-011010.7554/eLife.68699Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPROGavin Lee0https://orcid.org/0000-0003-2659-1163Jane W Liang1https://orcid.org/0000-0002-2302-3809Qing Zhang2Theodore Huang3Christine Choirat4Giovanni Parmigiani5Danielle Braun6https://orcid.org/0000-0002-5177-8598Swiss Data Science Center, ETH Zürich and EPFL, Lausanne, SwitzerlandDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, United States; Department of Data Sciences, Dana-Farber Cancer Institute, Boston, United StatesBroad Institute of MIT and Harvard, Cambridge, United StatesDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, United States; Department of Data Sciences, Dana-Farber Cancer Institute, Boston, United StatesSwiss Data Science Center, ETH Zürich and EPFL, Lausanne, SwitzerlandDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, United States; Department of Data Sciences, Dana-Farber Cancer Institute, Boston, United StatesDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, United States; Department of Data Sciences, Dana-Farber Cancer Institute, Boston, United StatesIdentifying individuals who are at high risk of cancer due to inherited germline mutations is critical for effective implementation of personalized prevention strategies. Most existing models focus on a few specific syndromes; however, recent evidence from multi-gene panel testing shows that many syndromes are overlapping, motivating the development of models that incorporate family history on several cancers and predict mutations for a comprehensive panel of genes. We present PanelPRO, a new, open-source R package providing a fast, flexible back-end for multi-gene, multi-cancer risk modeling with pedigree data. It includes a customizable database with default parameter values estimated from published studies and allows users to select any combinations of genes and cancers for their models, including well-established single syndrome BayesMendel models (BRCAPRO and MMRPRO). This leads to more accurate risk predictions and ultimately has a high impact on prevention strategies for cancer and clinical decision making. The package is available for download for research purposes at https://projects.iq.harvard.edu/bayesmendel/panelpro.https://elifesciences.org/articles/68699mendelian modelingcancer riskstatistical softwarepedigree data |
| spellingShingle | Gavin Lee Jane W Liang Qing Zhang Theodore Huang Christine Choirat Giovanni Parmigiani Danielle Braun Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO eLife mendelian modeling cancer risk statistical software pedigree data |
| title | Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO |
| title_full | Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO |
| title_fullStr | Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO |
| title_full_unstemmed | Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO |
| title_short | Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO |
| title_sort | multi syndrome multi gene risk modeling for individuals with a family history of cancer with the novel r package panelpro |
| topic | mendelian modeling cancer risk statistical software pedigree data |
| url | https://elifesciences.org/articles/68699 |
| work_keys_str_mv | AT gavinlee multisyndromemultigeneriskmodelingforindividualswithafamilyhistoryofcancerwiththenovelrpackagepanelpro AT janewliang multisyndromemultigeneriskmodelingforindividualswithafamilyhistoryofcancerwiththenovelrpackagepanelpro AT qingzhang multisyndromemultigeneriskmodelingforindividualswithafamilyhistoryofcancerwiththenovelrpackagepanelpro AT theodorehuang multisyndromemultigeneriskmodelingforindividualswithafamilyhistoryofcancerwiththenovelrpackagepanelpro AT christinechoirat multisyndromemultigeneriskmodelingforindividualswithafamilyhistoryofcancerwiththenovelrpackagepanelpro AT giovanniparmigiani multisyndromemultigeneriskmodelingforindividualswithafamilyhistoryofcancerwiththenovelrpackagepanelpro AT daniellebraun multisyndromemultigeneriskmodelingforindividualswithafamilyhistoryofcancerwiththenovelrpackagepanelpro |