Variability in pathogenicity prediction programs: impact on clinical diagnostics. Issue 2 (3rd December 2014)
- Record Type:
- Journal Article
- Title:
- Variability in pathogenicity prediction programs: impact on clinical diagnostics. Issue 2 (3rd December 2014)
- Main Title:
- Variability in pathogenicity prediction programs: impact on clinical diagnostics
- Authors:
- Walters‐Sen, Lauren C.
Hashimoto, Sayaka
Thrush, Devon Lamb
Reshmi, Shalini
Gastier‐Foster, Julie M.
Astbury, Caroline
Pyatt, Robert E. - Abstract:
- <abstract abstract-type="main" id="mgg3116-abs-0001"> <title>Abstract</title> <p>Current practice by clinical diagnostic laboratories is to utilize online prediction programs to help determine the significance of novel variants in a given gene sequence. However, these programs vary widely in their methods and ability to correctly predict the pathogenicity of a given sequence change. The performance of 17 publicly available pathogenicity prediction programs was assayed using a dataset consisting of 122 credibly pathogenic and benign variants in genes associated with the RASopathy family of disorders and limb‐girdle muscular dystrophy. Performance metrics were compared between the programs to determine the most accurate program for loss‐of‐function and gain‐of‐function mechanisms. No one program correctly predicted the pathogenicity of all variants analyzed. A major hindrance to the analysis was the lack of output from a significant portion of the programs. The best performer was MutPred, which had a weighted accuracy of 82.6% in the full dataset. Surprisingly, combining the results of the top three programs did not increase the ability to predict pathogenicity over the top performer alone. As the increasing number of sequence changes in larger datasets will require interpretation, the current study demonstrates that extreme caution must be taken when reporting pathogenicity based on statistical online protein prediction programs in the absence of functional studies.</p><abstract abstract-type="main" id="mgg3116-abs-0001"> <title>Abstract</title> <p>Current practice by clinical diagnostic laboratories is to utilize online prediction programs to help determine the significance of novel variants in a given gene sequence. However, these programs vary widely in their methods and ability to correctly predict the pathogenicity of a given sequence change. The performance of 17 publicly available pathogenicity prediction programs was assayed using a dataset consisting of 122 credibly pathogenic and benign variants in genes associated with the RASopathy family of disorders and limb‐girdle muscular dystrophy. Performance metrics were compared between the programs to determine the most accurate program for loss‐of‐function and gain‐of‐function mechanisms. No one program correctly predicted the pathogenicity of all variants analyzed. A major hindrance to the analysis was the lack of output from a significant portion of the programs. The best performer was MutPred, which had a weighted accuracy of 82.6% in the full dataset. Surprisingly, combining the results of the top three programs did not increase the ability to predict pathogenicity over the top performer alone. As the increasing number of sequence changes in larger datasets will require interpretation, the current study demonstrates that extreme caution must be taken when reporting pathogenicity based on statistical online protein prediction programs in the absence of functional studies.</p> </abstract> … (more)
- Is Part Of:
- Molecular genetics & genomic medicine. Volume 3:Issue 2(2015:Mar.)
- Journal:
- Molecular genetics & genomic medicine
- Issue:
- Volume 3:Issue 2(2015:Mar.)
- Issue Display:
- Volume 3, Issue 2 (2015)
- Year:
- 2015
- Volume:
- 3
- Issue:
- 2
- Issue Sort Value:
- 2015-0003-0002-0000
- Page Start:
- 99
- Page End:
- 110
- Publication Date:
- 2014-12-03
- Subjects:
- Medical genetics -- Periodicals
Genomics -- Periodicals
616.042 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2324-9269 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/mgg3.116 ↗
- Languages:
- English
- ISSNs:
- 2324-9269
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 3869.xml