Functional algorithms, MutationAssessor, PolyPhen2, and PROVEAN, predict the majority of somatic mutations identified to significantly impact protein function.
- Haley M. Simpson (821867)
- Rashid Z. Khan (821868)
- Chang Song (172416)
- Deva Sharma (821869)
- Kavitha Sadashivaiah (821870)
- Aki Furusawa (821871)
- Xinyue Liu (170148)
- Sushma Nagaraj (821872)
- Naomi Sengamalay (41920)
- Lisa Sadzewicz (427790)
- Luke J. Tallon (170168)
- Qing C. Chen (821873)
- Ferenc Livak (218587)
- Aaron P. Rapoport (821874)
- Amy Kimball (821875)
- Arnob Banerjee (821876)
Publication date
November 2015
DOIAbstract
<p>(A) Bar graph shows percent of non-synonymous somatic mutations and their probability to impact protein function, as predicted by MutationAssessor, PolyPhen2, and PROVEAN. (B) Venn diagram shows number of non-synonymous somatic mutations predicted to significantly impact protein function by each algorithm or combination of algorithms: MutationAssessor, PolyPhen2, and PROVEAN. Mutations were considered significant if selected as “high” or “medium”, “probably damaging” or “possibly damaging,” and “deleterious,” respectively.</p
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